## Matthew Anderson Bsge Homework

## Package Index

### Packages in the standard library

ACCLMA | ACC & LMA Graph Plotting |

ADGofTest | Anderson-Darling GoF test |

AER | Applied Econometrics with R |

AGSDest | Estimation in adaptive group sequential trials |

AICcmodavg | Model selection and multimodel inference based on (Q)AIC(c) |

AIGIS | Areal Interpolation for GIS data |

AIM | AIM: adaptive index model |

ALS | multivariate curve resolution alternating least squares (MCR-ALS) |

AMORE | A MORE flexible neural network package |

AcceptanceSampling | Creation and evaluation of Acceptance Sampling Plans |

AdMit | Adaptive Mixture of Student-t distributions |

AdaptFit | Adaptive Semiparametic Regression |

AlgDesign | Algorithmic Experimental Design |

AllPossibleSpellings | Computes all of a word's possible spellings. |

Amelia | Amelia II: A Program for Missing Data |

AnalyzeFMRI | Functions for analysis of fMRI datasets stored in the ANALYZE or NIFTI format. |

Animal | Analyze time-coded animal behavior data |

AnnotLists | Data extraction tool from annotations files. |

AnnotationDbi | Annotation Database Interface |

AquaEnv | AquaEnv - an integrated development toolbox for aquatic chemical model generation |

ArDec | Time series autoregressive-based decomposition |

B2Z | Bayesian Two-Zone Model |

BACCO | Bayesian Analysis of Computer Code Output (BACCO) |

BAMD | Bayesian Association Model for Genomic Data with Missing Covariates |

BARD | Better Automated ReDistricting |

BAS | Bayesian Model Averaging using Bayesian Adaptive Sampling |

BAYSTAR | On Bayesian analysis of Threshold autoregressive model (BAYSTAR) |

BB | Solving and Optimizing Large-Scale Nonlinear Systems |

BBMM | Brownian bridge movement model for estimating the movement path of an animal using discrete location data. |

BCE | Bayesian composition estimator: estimating sample (taxonomic) composition from biomarker data |

BGSIMD | Block Gibbs Sampler with Incomplete Multinomial Distribution |

BHH2 | Useful Functions for Box, Hunter and Hunter II |

BLCOP | Black-Litterman and copula-opinion pooling frameworks |

BLR | Bayesian Linear Regression |

BMA | Bayesian Model Averaging |

BMN | The pseudo-likelihood method for pairwise binary markov networks |

BMS | Bayesian Model Averaging Library |

BPHO | Bayesian Prediction with High-order Interactions |

BSDA | Basic Statistics and Data Analysis |

BSagri | Statistical methods for safety assessment in agricultural field trials |

BSgenome | Infrastructure for Biostrings-based genome data packages |

BaBooN | The Bayesian Bootstrap Predictive Mean Matching Package - Multiple and single imputation for discrete data |

BaM | Functions and datasets for books by Jeff Gill. |

BayHap | Bayesian analysis of haplotype association using Markov Chain Monte Carlo |

BayHaz | R Functions for Bayesian Hazard Rate Estimation |

BayesDA | Functions and Datasets for the book "Bayesian Data Analysis" |

BayesPeak | Bayesian Analysis of ChIP-seq Data |

BayesQTLBIC | Bayesian multi-locus QTL analysis based on the BIC criterion |

BayesTree | Bayesian Methods for Tree Based Models |

BayesValidate | BayesValidate Package |

BayesX | R Utilities Accompanying the Software Package BayesX |

Bergm | Bayesian inference for exponential random graph models |

Bhat | General likelihood exploration |

BiasedUrn | Biased Urn model distributions |

BioIDMapper | Mapping between BioIDs |

BioPhysConnectoR | BioPhysConnectoR |

BioStatR | Initiation la Statistique avec R |

Biobase | Biobase: Base functions for Bioconductor |

Biodem | Biodemography functions |

BiodiversityR | GUI for biodiversity and community ecology analysis |

Biograph | Explore life histories |

Biostrings | String objects representing biological sequences, and matching algorithms |

BlakerCI | Blaker's binomial confidence limits |

Bmix | Bayesian Sampling for Stick-breaking Mixtures |

BoSSA | a Bunch of Structure and Sequence Analysis |

Bolstad | Bolstad functions |

Bolstad2 | Bolstad functions |

BoolNet | Generation, reconstruction, simulation and analysis of synchronous, asynchronous, and probabilistic Boolean networks |

BootPR | Bootstrap Prediction Intervals and Bias-Corrected Forecasting |

Boruta | Boruta -- a tool for finding significant attributes in information systems |

BradleyTerry | Bradley-Terry Models -- this package is now deprecated in favour of 'BradleyTerry2' |

BradleyTerry2 | Bradley-Terry models |

Brobdingnag | Very large numbers in R |

BsMD | Bayes Screening and Model Discrimination |

CADFtest | Hansen's Covariate-Augmented Dickey-Fuller (CADF) Test |

CAVIAR | Cambial Activity and wood formation data processing, visualisation and analysis using R |

CCA | Canonical correlation analysis |

CCMtools | Clustering through "Correlation Clustering Model" (CCM) and cluster analysis tools. |

CCP | Significance Tests for Canonical Correlation Analysis (CCA) |

CDFt | Statistical downscaling through CDF-transform |

CDNmoney | Components of Canadian Monetary and Credit Aggregates |

CFL | Compensatory Fuzzy Logic |

CGIwithR | CGI Programming in R |

CGene | Causal Genetic Analysis |

CHNOSZ | Chemical Thermodynamics and Activity Diagrams |

CHsharp | Choi and Hall Clustering in 3d |

CMC | Cronbach-Mesbah Curve |

CNVassoc | Association analysis of CNV data |

COMPoissonReg | Conway-Maxwell Poisson (COM-Poisson) Regression |

COP | Variables selection for index models via correlation pursuit |

CORElearn | CORElearn - classification, regression, feature evaluation and ordinal evaluation |

CORREP | Multivariate Correlation Estimator and Statistical Inference Procedures. |

COSINE | COndition SpecIfic sub-NEtwork |

COUNT | Functions, data and code for count data. |

COZIGAM | Constrained and Unconstrained Zero-Inflated Generalized Additive Models with Model Selection Criterion |

CPE | Concordance Probability Estimates in Survival Analysis |

CRTSize | Sample Size Estimation Functions for Cluster Randomized Trials |

CTT | Classical Test Theory Functions |

CVThresh | Level-Dependent Cross-Validation Thresholding |

Cairo | R graphics device using cairo graphics library for creating high-quality bitmap (PNG, JPEG, TIFF), vector (PDF, SVG, PostScript) and display (X11 and Win32) output. |

CalciOMatic | Automatic Calcium Imaging Analysis |

CarbonEL | Carbon Event Loop |

CausalGAM | Estimation of Causal Effects with Generalized Additive Models |

CellularAutomaton | One-Dimensional Cellular Automata |

ChainLadder | Mack, Bootstrap, Munich, Multivariate-chain-ladder and Clark methods for insurance claims reserving |

CircNNTSR | CircNNTSR: An R package for the statistical analysis of circular data using nonnegative trigonometric sums (NNTS) models |

CircSpatial | Functions For Circular Spatial Data |

CircStats | Circular Statistics, from "Topics in circular Statistics" (2001) |

Ckmeans.1d.dp | Optimal distance-based clustering for one-dimensional data |

ClinicalRobustPriors | Robust Bayesian Priors in Clinical Trials: An R Package for Practitioners |

ClustOfVar | Clustering of variables |

CoCo | Graphical modelling by log-linear models (an interface from R to CoCo) |

CoCoCg | Graphical modelling by CG regressions |

CoCoGraph | Interactive and dynamic graphs for the CoCo objects |

CollocInfer | Collocation Inference for Dynamic Systems |

CombMSC | Combined Model Selection Criteria |

CompQuadForm | Distribution function of quadratic forms in normal variables |

CompRandFld | Composite-likelihood based Analysis of Random Fields |

CompetingRiskFrailty | Competing Risk Model with Frailties for Right Censored Survival Data |

ConvCalendar | Converts dates between calendars |

ConvergenceConcepts | Seeing convergence concepts in action |

CorrBin | Nonparametrics with clustered binary data |

CoxBoost | Cox models by likelihood based boosting for a single survival endpoint or competing risks |

Cprob | Conditional probability function of a competing event |

CreditMetrics | Functions for calculating the CreditMetrics risk model |

CvM2SL1Test | L1-version of Cramer-von Mises Two Sample Tests |

CvM2SL2Test | Cramer-von Mises Two Sample Tests |

DAAG | Data Analysis And Graphics data and functions |

DAAGbio | Data Sets and Functions, for demonstrations with expression arrays and gene sequences |

DAAGxtras | Data Sets and Functions, supplementary to DAAG |

DAKS | Data Analysis and Knowledge Spaces |

DAMisc | Dave Armstrong's Miscellaneous Functions |

DBI | R Database Interface |

DCGL | Differential Coexpression Analysis of Gene Expression Microarray Data |

DCluster | Functions for the detection of spatial clusters of diseases |

DDHFm | Variance Stabilization by Data-Driven Haar-Fisz (for Microarrays) |

DECIDE | DEComposition of Indirect and Direct Effects |

DEMEtics | Evaluating the genetic differentiation between populations based on Gst and D values. |

DESeq | Digital gene expresion analysis based on the negative binomial distribution |

DEoptim | Global optimization by differential evolution |

DMwR | Functions and data for "Data Mining with R" |

DNAtools | Tools for analysing forensic genetic DNA data |

DOBAD | Analysis of Discretely Observed linear Birth-And-Death(-and-immigration) Markov Chains |

DPpackage | Bayesian Nonparametric and Semiparametric Analysis |

DRI | DR-Integrator |

DSpat | Spatial modelling for distance sampling data |

DTDA | Doubly truncated data analysis |

DTK | Dunnett-Tukey-Kramer Pairwise Multiple Comparison Test Adjusted for Unequal Variances and Unequal Sample Sizes |

Daim | Diagnostic accuracy of classification models. |

DatABEL | file-based access to large matrices stored on HDD in binary format |

Davies | The Davies quantile function |

Defaults | Create Global Function Defaults |

Depela | Depela |

DescribeDisplay | R interface to DescribeDisplay (GGobi plugin) |

Design | Design Package |

DesignPatterns | Design Patterns in R to build reusable object-oriented software |

Devore5 | Data sets from Devore's "Prob and Stat for Eng (5th ed)" |

Devore6 | Data sets from Devore's "Prob and Stat for Eng (6th ed)" |

Devore7 | Data sets from Devore's "Prob and Stat for Eng (7th ed)" |

DiagnosisMed | Diagnostic test accuracy evaluation for medical professionals. |

DiceDesign | Designs of Computer Experiments |

DiceEval | Construction and evaluation of metamodels |

DiceKriging | Kriging methods for computer experiments |

DiceOptim | Kriging-based optimization for computer experiments |

DierckxSpline | R companion to "Curve and Surface Fitting with Splines" |

DistributionUtils | Distribution Utilities |

DiversitySampler | Functions for re-sampling a community matrix to compute diversity indices at different sampling levels. |

DoE.base | Full factorials, orthogonal arrays and base utilities for DoE packages |

DoE.wrapper | Wrapper package for design of experiments functionality |

DoseFinding | Planning and Analyzing Dose Finding experiments |

DynDoc | Dynamic document tools |

EDR | Estimation of the effective dimension reduction (EDR) space |

EMC | Evolutionary Monte Carlo (EMC) algorithm |

EMCC | Evolutionary Monte Carlo (EMC) methods for clustering |

EMD | Empirical Mode Decomposition and Hilbert Spectral Analysis |

EMJumpDiffusion | EM-Algorithm for Jump Diffusion processes |

EMT | Exact Multinomial Test: Goodness-of-Fit Test for Discrete Multivariate data |

ENmisc | Neuwirth miscellaenous |

EQL | Extended-Quasi-Likelihood-Function (EQL) |

ETC | Equivalence to control |

EVER | Estimation of Variance by Efficient Replication |

EbayesThresh | Empirical Bayes Thresholding and Related Methods |

Ecdat | Data sets for econometrics |

EffectiveDose | Estimation of the Effective Dose including Bootstrap confidence intervals |

ElectroGraph | Enhanced routines for plotting and analyzing valued relational data. |

ElemStatLearn | Data sets, functions and examples from the book: "The Elements of Statistical Learning, Data Mining, Inference, and Prediction" by Trevor Hastie, Robert Tibshirani and Jerome Friedman. |

EmpLikeGOF | Goodness of Fit Test for Empirical Likelihood |

EnQuireR | A package dedicated to questionnaires |

EngrExpt | Data sets from "Introductory Statistics for Engineering Experimentation" |

Epi | A package for statistical analysis in epidemiology. |

EquiNorm | Normalize expression data using equivalently expressed genes |

EvalEst | Dynamic Systems Estimation - extensions |

ExPD2D | Exact Computation of Bivariate Projection Depth Based on Fortran Code |

FAMT | Factor Analysis for Multiple Testing (FAMT) : simultaneous tests under dependence in high-dimensional data |

FAwR | Functions and Datasets for "Forest Analytics with R". |

FBN | FISH Based Normalization and Copy Number inference of SNP microarray data |

FD | Measuring functional diversity (FD) from multiple traits, and other tools for functional ecology |

FGN | Fractional Gaussian Noise, estimation and simulaton |

FITSio | FITS (Flexible Image Transport System) utilities |

FKF | Fast Kalman Filter |

FME | A Flexible Modelling Environment for Inverse Modelling, Sensitivity, Identifiability, Monte Carlo Analysis. |

FNN | Fast Nearest Neighbor Search Algorithms and Applications |

FRB | Fast and Robust Bootstrap |

FTICRMS | Programs for Analyzing Fourier Transform-Ion Cyclotron Resonance Mass Spectrometry Data |

FactoClass | Combination of Factorial Methods and Cluster Analysis |

FactoMineR | Multivariate Exploratory Data Analysis and Data Mining with R |

Fahrmeir | Data from the book "Multivariate Statistical Modelling Based on Generalized Linear Models", first edition, by Ludwig Fahrmeir and Gerhard Tutz |

FeaLect | Scores features for Feature seLection |

FinTS | Companion to Tsay (2005) Analysis of Financial Time Series |

FitAR | Subset AR Model Fitting |

FitARMA | FitARMA: Fit ARMA or ARIMA using fast MLE algorithm |

Flury | Data Sets from Flury, 1997 |

Formula | Extended Model Formulas |

FourierDescriptors | Generate images using Fourier descriptors. |

FrF2 | Fractional Factorial designs with 2-level factors |

FrF2.catlg128 | Complete catalogues of resolution IV 128 run 2-level fractional factorials up to 24 factors |

FracSim | Simulation of Lvy motions |

FunCluster | Functional Profiling of Microarray Expression Data |

FunNet | Integrative Functional Analysis of Transcriptional Networks |

FuncMap | Hive Plots of R Package Function Calls |

FunctSNP | FunctSNP - SNP annotation data methods and species specific database builder |

G1DBN | A package performing Dynamic Bayesian Network inference. |

GAD | General ANOVA Design (GAD): Analysis of variance from general principles |

GAMBoost | Generalized linear and additive models by likelihood based boosting |

GAMens | Applies GAMbag, GAMrsm and GAMens ensemble classifiers for binary classification |

GB2 | Generalized Beta Distribution of the Second Kind: properties, likelihood, estimation. |

GEOmap | Topographic and Geologic Mapping |

GEVcdn | GEV conditonal density estimation network |

GExMap | A visual, intuitive, easy to use software giving access to a new type of information buried into your microarray data. |

GGMselect | Gaussian Graphs Models selection |

GGally | Extension to ggplot2. |

GLDEX | Fitting Single and Mixture of Generalised Lambda Distributions (RS and FMKL) using Various Methods |

GLMMarp | Generalized Linear Multilevel Model with AR(p) Errors Package |

GO.db | A set of annotation maps describing the entire Gene Ontology |

GOFSN | Goodness-of-fit tests for the family of skew-normal models |

GPArotation | GPA Factor Rotation |

GPseq | gpseq: Using the generalized Poisson distribution to model sequence read counts from high throughput sequencing experiments |

GRRGI | Gauge R and R Confidence Intervals |

GSA | Gene set analysis |

GSM | Gamma Shape Mixture |

GWAF | Genome-Wide Association analyses with Family data |

GWASExactHW | Exact Hardy-Weinburg testing for Genome Wide Association Studies |

GWRM | GWRM |

GenABEL | genome-wide SNP association analysis |

GenKern | Functions for generating and manipulating binned kernel density estimates |

GeneCycle | Identification of Periodically Expressed Genes |

GeneF | Package for Generalized F-statistics |

GeneNet | Modeling and Inferring Gene Networks |

GeneReg | Construct time delay gene regulatory network |

Geneclust | Simulation and analysis of spatial structure of population genetics data |

Geneland | Detection of structure from multilocus genetic data. |

GeneralizedHyperbolic | The generalized hyperbolic distribution |

GenomicRanges | Representation and manipulation of genomic intervals |

GillespieSSA | Gillespie's Stochastic Simulation Algorithm (SSA) |

GrapheR | A multiplatform GUI for drawing highly customizable common graphs in R |

GrassmannOptim | Grassmann Manifold Optimization |

GridR | Executes functions on remote hosts, clusters or grids. |

GroupSeq | Performing computations related to group sequential designs. |

Guerry | Guerry: maps, data and methods related to Guerry (1833) "Moral Statistics of France" |

HAPim | HapIM |

HDMD | Statistical Analysis Tools for High Dimension Molecular Data (HDMD) |

HDclassif | High Dimensionnal Classification. |

HFWutils | csv import, csv export, garbage collection,string matching and passing by reference |

HGLMMM | Hierarchical Generalized Linear Models |

HH | Statistical Analysis and Data Display: Heiberger and Holland |

HI | Simulation from distributions supported by nested hyperplanes |

HMM | HMM - Hidden Markov Models |

HMR | Flux estimation with static chamber data |

HPbayes | Heligman Pollard mortality model parameter estimation using Bayesian Melding with Incremental Mixture Importance Sampling |

HSAUR | A Handbook of Statistical Analyses Using R |

HSAUR2 | A Handbook of Statistical Analyses Using R (2nd Edition) |

HTMLUtils | Facilitates automated HTML report creation |

HWEBayes | Bayesian investigation of Hardy-Weinberg Equilibrium via estimation and testing. |

HWEintrinsic | Objective Bayesian Testing for the Hardy-Weinberg Equilibrium Problem |

HadoopStreaming | Utilities for using R scripts in Hadoop streaming |

HapEstXXR | HapEstXXR |

Haplin | Analyzing case-parent triad and/or case-control data with SNP haplotypes |

HaploSim | HaploSim |

HardyWeinberg | Graphical tests for Hardy-Weinberg equilibrium |

HiddenMarkov | Hidden Markov Models |

HistData | Data sets from the history of statistics and data visualization |

Hmisc | Harrell Miscellaneous |

HybridMC | Implementation of the Hybrid Monte Carlo and Multipoint Hybrid Monte Carlo sampling techniques |

HydroMe | Estimation of Soil Hydraulic Parameters from Experimental Data |

HyperbolicDist | The hyperbolic distribution |

IBrokers | R API to Interactive Brokers Trader Workstation |

ICE | Iterated Conditional Expectation |

ICEinfer | Incremental Cost-Effectiveness (ICE) Statistical Inference from Two Unbiased Samples |

ICS | Tools for Exploring Multivariate Data via ICS/ICA |

ICSNP | Tools for Multivariate Nonparametrics |

IDPmisc | Utilities of Institute of Data Analyses and Process Design (www.idp.zhaw.ch) |

IFP | Identifying functional polymorphisms in genetic association studies |

IMIS | Increamental Mixture Importance Sampling |

IPSUR | Introduction to Probability and Statistics Using R |

IQCC | Improved Quality Control Charts |

IRanges | Infrastructure for manipulating intervals on sequences |

ISA | INTRODUZIONE ALLA STATISTICA APPLICATA con esempi in R |

ISOcodes | Selected ISO codes |

ISwR | Introductory Statistics with R |

Icens | NPMLE for Censored and Truncated Data |

Imap | Interactive Mapping |

ImpactIV | Identifying Causal Effect for Multi-Component Intervention Using Instrumental Variable Method |

IniStatR | Initiation la Statistique avec R |

Interpol | Interpolation of amino acid sequences |

Iso | Functions to perform isotonic regression. |

IsoGene | Testing for monotonic relationship between gene expression and doses in a microarray experiment. |

JADE | JADE and ICA performance criteria |

JJcorr | Calculates polychorical correlations for several copula families. |

JM | Joint Modelling of Longitudinal and Survival Data |

JOP | Joint Optimization Plot |

JointModeling | Joint Modelling of Mean and Dispersion |

JudgeIt | JudgeIt |

KEGG.db | A set of annotation maps for KEGG |

KFAS | Kalman filter and smoothers for exponential family state space models. |

KMsurv | Data sets from Klein and Moeschberger (1997), Survival Analysis |

Kendall | Kendall rank correlation and Mann-Kendall trend test |

KernSmooth | Functions for kernel smoothing for Wand & Jones (1995) |

KrigInv | Kriging-based Inversion for Deterministic and Noisy Computer Experiments |

LCAextend | Latent Class Analysis (LCA) with familial dependence in extended pedigrees |

LDdiag | Link Function and Distribution Diagnostic Test for Social Science Researchers |

LDheatmap | Graphical display of pairwise linkage disequilibria between SNPs |

LDtests | Exact tests for Linkage Disequilibrium and Hardy-Weinberg Equilibrium |

LIM | Linear Inverse Model examples and solution methods. |

LIStest | Longest Increasing Subsequence Independence Test |

LLAhclust | Hierarchical clustering of variables or objects based on the likelihood linkage analysis method |

LLdecomp | Decomposes a set of variables into cliques and separators. |

LMERConvenienceFunctions | An assortment of functions to facilitate modeling with linear mixed-effects regression (LMER). |

LMGene | LMGene Software for Data Transformation and Identification of Differentially Expressed Genes in Gene Expression Arrays |

LPCM | Local principal curve methods |

LS2W | Locally stationary two-dimensional wavelet process estimation scheme |

LSD | Lots of Superior Depictions |

LVQTools | Learning Vector Quantization Tools |

LambertW | Gaussianize and analyze skewed, heavy-tailed data |

LaplacesDemon | Laplace's Demon: Software for Bayesian Inference |

LearnBayes | Functions for Learning Bayesian Inference |

LearnEDA | Functions for Learning Exploratory Data Analysis |

LiblineaR | Linear Predictive Models Based On The Liblinear C/C++ Library. |

Lmoments | L-moments and quantile mixtures |

LogConcDEAD | Log-concave Density Estimation in Arbitrary Dimensions |

LogicForest | Logic Forest |

LogicReg | Logic Regression |

LogitNet | Infer network based on binary arrays using regularized logistic regression |

LoopAnalyst | A collection of tools to conduct Levins' Loop Analysis |

LowRankQP | Low Rank Quadratic Programming |

MAMSE | Calculation of Minimum Averaged Mean Squared Error (MAMSE) weights. |

MARSS | Multivariate Autoregressive State-Space Modeling |

MASS | Support Functions and Datasets for Venables and Ripley's MASS |

MAT | Multidimensional Adaptive Testing (MAT) |

MAc | Meta-Analysis with Correlations |

MAclinical | Class prediction based on microarray data and clinical parameters |

MAd | Meta-Analysis with Mean Differences |

MBESS | MBESS |

MCAPS | MCAPS data and results |

MCE | Tools for evaluating Monte Carlo Error |

MCLIME | Simultaneous Estimation of the Regression Coefficients and Precision Matrix |

MCMCglmm | MCMC Generalised Linear Mixed Models |

MCMChybridGP | Hybrid Markov chain Monte Carlo using Gaussian Processes |

MCMCpack | Markov chain Monte Carlo (MCMC) Package |

MCPAN | Multiple comparisons using normal approximation |

MCPMod | Design and Analysis of Dose-Finding Studies (see also DoseFinding package) |

MChtest | Monte Carlo hypothesis tests with Sequential Stopping |

MDR | Detect gene-gene interactions using multifactor dimensionality reduction |

MEMSS | Data sets from Mixed-effects Models in S |

MFDA | Model Based Functional Data Analysis |

MFDF | Modeling Functional Data in Finance |

MIfuns | Pharmacometric tools for data preparation, modeling, simulation, and reporting |

MImix | Mixture summary method for multiple imputation |

MKLE | Maximum kernel likelihood estimation. |

MKmisc | Miscellaneous Functions from M. Kohl |

MLCM | Maximum Likelihood Conjoint Measurement |

MLDA | Methylation Linear Discriminant Analysis (MLDA) |

MLDS | Maximum Likelihood Difference Scaling |

MLEcens | Computation of the MLE for bivariate (interval) censored data |

MLPAstats | MLPA analysis to detect gains and loses in genes |

MMG | Mixture Model on Graphs |

MMIX | Model selection uncertainty and model mixing |

MMST | DATASETS FROM MMST |

MNM | Multivariate Nonparametric Methods. An Approach Based on Spatial Signs and Ranks |

MNP | R Package for Fitting the Multinomial Probit Model |

MOCCA | Multi-objective optimization for collecting cluster alternatives |

MPV | Data Sets from Montgomery, Peck and Vining's Book |

MSBVAR | Markov-Switching, Bayesian, Vector Autoregression Models |

MSToolkit | The MSToolkit library for clinical trial design |

MTSKNN | Multivariate two-sample tests based on K-nearest-neighbors |

MVpower | Give power for a given effect size using multivariate classification methods |

MaXact | Exact max-type Cochran-Armitage trend test(CATT) |

MarkedPointProcess | Analysis of Marks of Marked Point Processes |

MasterBayes | ML and MCMC Methods for Pedigree Reconstruction and Analysis |

MatchIt | MatchIt |

Matching | Multivariate and Propensity Score Matching with Balance Optimization |

Matrix | Sparse and Dense Matrix Classes and Methods |

MatrixModels | Modelling with Sparse And Dense Matrices |

Mcomp | Data from the M-competitions |

MeDiChI | MeDiChI ChIP-chip deconvolution library |

MetabolAnalyze | Probabilistic latent variable models for metabolomic data. |

Miney | Implementation of the Well-Known Game to Clear Bombs from a Given Field (Matrix) |

MiscPsycho | Miscellaneous Psychometric Analyses |

MixSim | Simulating Data to Study Performance of Clustering Algorithms. |

Modalclust | Hierarchical Modal Clustering |

ModelGood | Validation of prediction models |

MortalitySmooth | Smoothing Poisson counts with P-splines |

MplusAutomation | Automating Mplus Model Estimation and Interpretation |

MsatAllele | Visualizes the scoring and binning of microsatellite fragment sizes |

MuMIn | Multi-model inference |

MultEq | Multiple equivalence tests and simultaneous confidence intervals |

Multiclasstesting | Performance of N-ary classification testing |

NADA | Nondetects And Data Analysis for environmental data |

NCBI2R | NCBI2R-An R package to navigate and annotate genes and SNPs |

NISTnls | Nonlinear least squares examples from NIST |

NMF | Algorithms and framework for Nonnegative Matrix Factorization (NMF). |

NMFN | Non-negative Matrix Factorization |

NMMAPSlite | NMMAPS Data Lite |

NMRS | NMR Spectroscopy |

NORMT3 | Evaluates complex erf, erfc, Faddeeva, and density of sum of Gaussian and Student's t |

NRAIA | Data sets from "Nonlinear Regression Analysis and Its Applications" |

NestedCohort | Survival Analysis for Cohorts with Missing Covariate Information |

NetCluster | Clustering for networks |

NetData | Network Data for McFarland's SNA R labs |

NetIndices | Estimating network indices, including trophic structure of foodwebs in R |

NetworkAnalysis | Statistical inference on populations of weighted or unweighted networks. |

OAIHarvester | Harvest Metadata Using OAI-PMH v2.0 |

OPE | Outer-product emulator |

ORDER2PARENT | Estimate parent distributions with data of several order statistics |

ORIClust | Order-restricted Information Criterion-based Clustering Algorithm |

ORMDR | ORMDR |

OSACC | Ordered Subset Analysis for Case-Control Studies |

Oarray | Arrays with arbitrary offsets |

OjaNP | Multivariate Methods Based on the Oja Median and Related Concepts |

OligoSpecificitySystem | Oligo Specificity System |

Oncotree | Estimating oncogenetic trees |

OrdFacReg | Least squares, logistic, and Cox-regression with ordered predictors |

OrdMonReg | Compute least squares estimates of one bounded or two ordered isotonic regression curves |

OrgMassSpecR | Organic Mass Spectrometry |

PASWR | PROBABILITY and STATISTICS WITH R |

PBSadmb | PBS ADMB |

PBSddesolve | Solver for Delay Differential Equations |

PBSmapping | Mapping Fisheries Data and Spatial Analysis Tools |

PBSmodelling | GUI Tools Made Easy: Interact with Models, Explore Data, Give Dynamic Presentations |

PCIT | PCIT algorithm - Partial Correlation Coefficient with Information Theory |

PCS | Calculate the probability of correct selection (PCS) |

PERregress | Regression Functions and Datasets |

PET | Simulation and Reconstruction of PET Images |

PHYLOGR | Functions for phylogenetically based statistical analyses |

PK | Basic Non-Compartmental Pharmacokinetics |

PKfit | A Data Analysis Tool for Pharmacokinetics |

PKreport | A reporting pipeline for checking population pharmacokinetic model assumption |

PKtools | unified computational interfaces for pop PK |

PLIS | Multiplicity control using Pooled LIS statisitcs |

PMA | Penalized Multivariate Analysis |

POT | Generalized Pareto Distribution and Peaks Over Threshold |

PSAgraphics | Propensity Score Analysis Graphics |

PSM | Non-Linear Mixed-Effects modelling using Stochastic Differential Equations. |

PTAk | Principal Tensor Analysis on k modes |

PairViz | Visualization using Eulerian tours and Hamiltonian decompositions |

Peaks | Peaks |

PearsonDS | Pearson Distribution System |

PearsonICA | Independent component analysis using score functions from the Pearson system |

PerformanceAnalytics | Econometric tools for performance and risk analysis. |

PermAlgo | Permutational algorithm to simulate survival data |

PermuteNGS | PermuteNGS |

PhysicalActivity | Process Physical Activity Accelerometer Data |

PolynomF | Polynomials in R |

Pomic | Pattern Oriented Modelling Information Criterion |

PowerTOST | Power and Sample size based on two one-sided t-tests (TOST) for bioequivalence studies |

PredictiveRegression | Prediction Intervals for Three Basic Statistical Models |

PresenceAbsence | Presence-Absence Model Evaluation. |

ProDenICA | Product Density Estimation for ICA using tilted Gaussian density estimates |

ProbForecastGOP | Probabilistic weather forecast using the GOP method |

ProfessR | Grades Setting and Exam Maker |

ProfileLikelihood | Profile Likelihood for a Parameter in Commonly Used Statistical Models |

ProjectTemplate | Automates the creation of new statistical analysis projects. |

PropCIs | Computes confidence intervals for single proportions, for differences in proportions, for an odds-ratio and for the relative risk in a 2x2 table |

PtProcess | Time Dependent Point Process Modelling |

PwrGSD | Power in a Group Sequential Design |

QCA | Qualitative Comparative Analysis |

QCA3 | Yet another package for Qualitative Comparative Analysis |

QCAGUI | QCA Graphical User Interface |

QRMlib | Provides R-language code to examine Quantitative Risk Management concepts |

QSARdata | Quantitative Structure Activity Relationship (QSAR) Data Sets |

QT | QT Knowledge Management System |

QTLRel | Tools for mapping of quantitative traits of genetically related individuals |

QuantPsyc | Quantitative Psychology Tools |

R.cache | Fast and light-weight caching of objects |

R.filesets | Easy handling of and access to files organized in structured directories |

R.huge | Methods for accessing huge amounts of data [DEPRECATED] |

R.matlab | Read and write of MAT files together with R-to-Matlab connectivity |

R.methodsS3 | Utility function for defining S3 methods |

R.oo | R object-oriented programming with or without references |

R.rsp | R Server Pages |

R.utils | Various programming utilities |

R2Cuba | Multidimensional Numerical Integration |

R2HTML | HTML exportation for R objects |

R2WinBUGS | Running WinBUGS and OpenBUGS from R / S-PLUS |

R4dfp | 4dfp MRI Image Read and Write Routines |

RANN | Fast Nearest Neighbour Search |

RArcInfo | Functions to import data from Arc/Info V7.x binary coverages |

RBGL | An interface to the BOOST graph library |

RBerkeley | R API to Oracle Berkeley DB |

RBrownie | Continuous and discrete ancestral character reconstruction and evolutionary rate tests. |

RC | Reproducible Computing |

RColorBrewer | ColorBrewer palettes |

RCurl | General network (HTTP/FTP/...) client interface for R |

RDS | R Functions for Respondent-Driven Sampling |

REEMtree | Regression Trees with Random Effects for Longitudinal (Panel) Data |

REQS | R/EQS Interface |

RFA | Regional Frequency Analysis |

RFLPtools | Tools to analyse RFLP data |

RFOC | Graphics for Spherical Distributions and Earthquake Focal Mechanisms |

RFinanceYJ | RFinanceYJ |

RGCCA | Regularized Generalized Canonical Correlation Analysis |

RGraphics | Data and Functions from the book R Graphics |

RHRV | Heart rate variability analysis of ECG data |

RHmm | Hidden Markov Models simulations and estimations |

RInside | C++ classes to embed R in C++ applications |

RItools | Randomization inference tools |

RJSONIO | Serialize R objects to JSON, JavaScript Object Notation |

RJaCGH | Reversible Jump MCMC for the analysis of CGH arrays. |

RLMM | A Genotype Calling Algorithm for Affymetrix SNP Arrays |

RLRsim | Exact (Restricted) Likelihood Ratio tests for mixed and additive models. |

RLastFM | R interface to last.fm API |

RM2 | Revenue Management and Pricing Package |

RMC | Functions for fitting Markov models |

RMTstat | Distributions, Statistics and Tests derived from Random Matrix Theory |

RNCEP | Obtain, organize, and visualize NCEP weather data |

RNiftyReg | Medical image registration using the NiftyReg library |

ROCR | Visualizing the performance of scoring classifiers. |

ROptEst | Optimally robust estimation |

ROptEstOld | Optimally robust estimation - old version |

ROptRegTS | Optimally robust estimation for regression-type models |

RPMG | Graphical User Interface (GUI) for interactive R analysis sessions |

RPMM | Recursively Partitioned Mixture Model |

RPPanalyzer | Reads, annotates, and normalizes reverse phase protein array data |

RSAGA | SAGA Geoprocessing and Terrain Analysis in R |

RSEIS | Seismic Time Series Analysis Tools |

RSNNS | Neural Networks in R using the Stuttgart Neural Network Simulator (SNNS) |

RSQLite | SQLite interface for R |

RSQLite.extfuns | Math and String Extension Functions for RSQLite |

RSVGTipsDevice | An R SVG graphics device with dynamic tips and hyperlinks |

RSearchYJ | RSearchYJ |

RSeqMeth | Package for analysis of Sequenom EpiTYPER Data |

RSiena | Siena - Simulation Investigation for Empirical Network Analysis |

RSiteSearch | RSiteSearch |

RSvgDevice | An R SVG graphics device. |

RTOMO | Visualization for seismic tomography |

RTisean | R interface to Tisean algorithms |

RUnit | R Unit test framework |

RWebMA | RWebMA |

RXshrink | Maximum Likelihood Shrinkage via Generalized Ridge or Least Angle Regression |

RadioSonde | Tools for plotting skew-T diagrams and wind profiles |

RandVar | Implementation of random variables |

RandomFields | Simulation and Analysis of Random Fields |

RankAggreg | Weighted rank aggregation |

RaschSampler | Rasch Sampler |

Rassoc | Robust tests for case-control genetic association studies |

Ratings | Model-based Ratings Figures |

Rcapture | Loglinear Models for Capture-Recapture Experiments |

Rcgmin | Conjugate gradient minimization of nonlinear functions with box constraints |

Rcmdr | R Commander |

RcmdrPlugin.DoE | R Commander Plugin for (industrial) Design of Experiments |

RcmdrPlugin.EHESsampling | Tools for sampling in European Health Examination Surveys (EHES) |

RcmdrPlugin.Export | Graphically export output to LaTeX or HTML |

RcmdrPlugin.FactoMineR | Graphical User Interface for FactoMineR |

RcmdrPlugin.HH | Rcmdr support for the HH package |

RcmdrPlugin.IPSUR | An IPSUR Plugin for the R Commander |

RcmdrPlugin.MAc | Meta-Analysis with Correlations (MAc) Rcmdr Plug-in |

RcmdrPlugin.MAd | Meta-Analysis with Mean Differences (MAd) Rcmdr Plug-in |

RcmdrPlugin.SLC | SLC Rcmdr Plug-in |

RcmdrPlugin.SensoMineR | Graphical User Interface for SensoMineR |

RcmdrPlugin.SurvivalT | Rcmdr Survival Plug-In |

RcmdrPlugin.TeachingDemos | Rcmdr Teaching Demos Plug-In |

RcmdrPlugin.doex | Rcmdr plugin for Stat 4309 course |

RcmdrPlugin.epack | Rcmdr plugin for time series |

RcmdrPlugin.orloca | orloca Rcmdr Plug-in |

A Facebook study shows that almost 30% of married couples attended the same college. While marrying your college sweetheart might be a fairy tale for some, it's a beautiful reality for others.

Here are three couples that met in ISE and are still married today: Fred and Julie Jewell, Tim and Lynda McGrath, and Richard Henneman and Janet Fath.

## Fred and Julie Jewell

Young Fred and Julie Jewell

28 years of marriage, two children and numerous cities later, Fred and Julie Jewell are still enjoying life together.

As an undergrad, Julie ran cross-country and track and was in Phi Mu sorority, Society of Women Engineers, and Society of General Engineers. She also worked as an usher at the Assembly Hall, now known as the State Farm Center. Julie says, “I worked all the basketball games, the state high school wrestling tournaments, and concerts, so that actually was fun because I got to see a lot of things I probably never would have paid to go see.”

Julie says she decided to transfer into GE because “I liked the ability to have an engineering foundation but also have a secondary field”, which for Julie was business. She says, “I really didn’t know what I wanted to do at the time, but in the end it really turned out to be a good combination for starting out in consulting, because I had the analytical background and then the basic business fundamentals, which really served me well.”

During his time as an undergrad, Fred was a member of Sigma Phi Epsilon, Illinois Society of General Engineers, and Gamma Epsilon. He also ran his own DJ business for parties. About his time at Illinois, Fred says, “The friendships that I made at Illinois are lifelong.”

As Fred entered his sophomore year, he lost interest in computer engineering and transferred into GE, focusing on human factors and ergonomics. He says, “I was really interested in how people fit into systems… It was really cool to be able to weave people together with the engineering we were learning.”

After Professor Jerry Dobrovolny’s senior seminar class, Fred and Julie would walk to their apartments together. It wasn’t until graduation week that they started dating. Both had broken up with their long-term significant others the second half of senior year. Fred says, “We had gone out with a bunch of friends who were graduating, kind of just as a celebration outing to Bombay Bicycle Club.... Julie and I ended up standing next to each other for most of the night talking… The timing was right.”

Once they graduated, Julie and Fred went on for their Master of Science in General Engineering at ISE. While earning their MSGEs, Fred and Julie were full-time students, worked as TAs, and worked 30 hours a week off campus at Integrated Controls and Computer Systems (ICCS). Julie says that in grad school, “We thought we were really rich because we had our Teaching Assistant stipends, and it was just fun being a little bit more independent.”

Looking back at earning his master's degree, Fred says, “I remember working a lot in grad school, but I just really liked teaching.”

After earning their masters', Fred and Julie began working for Anderson Consulting, now known as Accenture. There, Fred says he worked in “process development and process improvement, and eventually change management.” Today, Fred works with Jabian Consulting and says he works “on the human capital management focus area that we’ve got and built up… within the company over the last eight years. I do a lot of strategy, organization design, change management, and leadership development work with my clients.”

The Jewell family today

Fred and Julie have enjoyed living in Atlanta for the past 20 years. Julie says “They’re calling it the Silicon Valley of the Southeast now with lots of technology companies coming here. It’s a great economy to work in.”

They have two children: Maddie, 23 and Max, 20. Maddie graduated from University of Georgia, Athens, and is working as a KPMG strategy consultant. Max is a sophomore at Ole Miss.

Giving advice to current college students, Julie says, “I think a lot of the younger employees are very uncomfortable with uncertainty. They want to be told exactly how to do everything or they want to know what the future’s going to hold for sure and that’s just not realistic. I think they’ve got to be comfortable with being uncomfortable.” She also says, “you have to look forward far enough and think about where you want to be and identify the steps that you need to take to get you there. Be proactive about your career versus just letting your it happen to you.”

Fred’s advice is, “If you have an opportunity to go an event and meet somebody who’s going to be there that’s been successful… have some guts to walk up to them, ask them some questions, and learn what you can from them. They might turn around and help you in some way that you’ve never anticipated, but you have to choose to actually get out there.”

One of Fred’s favorite quotes from a business partner at Accenture is, “You can’t shoot a moose if you’re sitting in the lodge.” Fred says, “If you really want things to happen, you have to be out there where it’s happening. That’s probably my best piece of advice.”

## Tim and Lynda McGrath

Lynda and Tim McGrath at the University of Illinois.

Today the McGraths are celebrating 33 years of marriage, two children, and successful careers.

Tim says, “I think the first time we actually met was when we were in a computer lab working in a computer programing class or a data class, and I think we helped each other out with some homework assignment we were working on.”

During their junior and senior years, Tim says “We were in a lot of the same classes together so it was nice that we were able to hang out together and that’s kind of when we started to date.”

Lynda McGrath in college and today

Tim was heavily involved in intermural sports, a champion softball team and a soccer team. He participated in the Industrial Engineering Society and was a representative to Engineering Council. Tim also worked in food services and in the library. He says, “I did what I could so I could to try to make ends meet and reduce the amount of my own student loans when I got to the end of the four years.”

After graduating from Illinois, the McGraths worked in industry for several years before going on to earn their MBAs. Tim earned his MBA from Northwestern University Kellogg School of Management. Lynda earned her MBA from the University of Chicago Booth School of Business.

Lynda went on to work at McMaster-Carr in 1986 and has been working there ever since. Tim says, “She’s got a number of different roles within that company: purchasing, merchandizing, data systems, human resource management and human resource data management within that same company.”

Tim McGrath today

At ISE, Tim says he learned valuable problem-solving skills. Now as a counselor, he says, “I problem solve with students. I look at trying to create a path… to be successful at the high school level and then beyond.” He also says ISE taught him the importance of data. He says, “it’s probably given me a little bit of an advantage to be able to analyze data in ways that are maybe different from others that have come up strictly in education or strictly in counseling.”

Today, Tim says his favorite part of his job is seeing students “setting goals, overcoming obstacles, and being able to achieve something that they never thought that they could achieve before.”

At the University of Illinois, Tim says his most memorable moment was with ISE Professor DeVor. During Tim’s senior year at Illinois, his mom became ill and passed away. He went to DeVor’s office and says, “I was nervous about talking to him and having to miss time from school.” He says DeVor “told me how to make sure that I took care of my family first and that academics and my work responsibilities or school responsibilities would come second.”

The McGrath family now

Today, Tim and Lynda have two children together. Their oldest daughter is in graduate school at Rutgers University studying to become a physician’s assistant. Their younger son earned his degree in risk management at Illinois Wesleyan University and is working in Chicago.

Giving advice to current students, Tim says students should understand their goals and realize “what their gifts are to help other human beings.”

Tim says, “I have always been grateful for the preparation that I learned at U of I, the diligence and the perseverance you have to have in order to achieve goals.”

## Richard Henneman and Janet Fath

Dick and Janet in college

Dick and Janet began working at the Engineering Library in August of 1979 and they shared a shift together. At that time, the Engineering Library was on the first and second floors of Engineering Hall. They began dating later that fall after seeing “A Christmas Carol” at Krannert Center for the Performing Arts.

Janet graduated with her bachelors in Industrial Engineering in 1981. Dick earned his bachelors in 1980 and went on to earn his master’s in 1981; both degrees were in Industrial Engineering at Illinois.

When applying to colleges, Dick says Illinois was the only school he applied to because he “knew it was a good engineering school.”

Janet visited several different schools before deciding to attend Illinois. Both of her parents attended the University of Illinois, Chicago and studied pharmacy.

Looking back at their time at Illinois, Dick says his most memorable time at Illinois was meeting Janet. He also vividly remembers “those -30°F days running between buildings on the engineering campus in an attempt to keep warm.” He also fondly recalls the times when Prof. Judith Liebman invited him over to her house to practice piano duets. “She even asked my mother to come over during Mom’s Weekend to hear us play.”

Other than meeting Dick, Janet says her most memorable time at Illinois was when she was in Professor Richard DeVor’s experimental design class and her “luck ran out.” She says Professor DeVor “would always ask other students questions. I kind of dodged it for the first couple of questions and then one day, he handed me back my paper but didn’t let go. He looked me in the eye, looked at the name on the paper, and after that, he called on me way more often. We called it Learning By Fear.”

Dick also had a Manufacturing Engineering class with Professor DeVor. He says, “During the last semester of senior year, the entire class had to give a presentation about a research project that we worked on. I remember that it was very intimidating because we had to speak in front of a group of industry professionals. It was painful at the time, but in retrospect, it was a really great experience.”

During her time at Illinois, Janet was involved in Tau Beta Pi, Alpha Pi Mu, and Phi Kappa Phi. She was awarded the American Institute of Industrial Engineering Award and was also a Knight of St. Pat.

Dick says, “Janet was involved in everything… I was less so.” When Janet got involved in something, Dick says, “Then I usually got involved in it too.”

After graduating from Illinois, Dick and Janet moved to Georgia. Dick says, “our advisor at Illinois, Bill Rouse, took a job at Georgia Tech and we followed him down here. Janet went on to earn her masters degree and PhD in Industrial and Systems Engineering at Georgia Tech. I completed my PhD in the same program.” They went on to get married in December 1983.

Today, Janet is a manager at the Centers for Disease Control in Atlanta in their immunization program. Dick has worked in various user experience management positions “in places with three-letter names like NCR, IBM and AT&T.” He now leads a multidisciplinary Master’s program in Human-Computer Interaction at Georgia Tech as a Professor of the Practice in the College of Computing. He has also served on the UIUC ISE Alumni Board for a number of years and is a past president of that organization.

Dick and Janet have two sons, Nate and Luke. They are very proud of them both. Nate is 23 years old and graduated from Bates College with a degree in Biology. He is currently doing research at Emory University and applying to graduate schools. Luke is 27 years old. He went to Johns Hopkins for his undergraduate degree and went on to earn his PhD in Environmental Engineering at Georgia Tech. He is currently completing a postdoc at Harvard.

Since they left Illinois, Dick says Industrial Engineering “has really changed a lot from when we were there. I think the ISE program is very strong through the merger of IE a few years back with GE, the increased breadth of its offerings, and the quality of its faculty.”

IE helped prepare Janet for her career by giving her “really high standards for doing your work but also contributing beyond that.” She says IE helped her learn to not get stuck in one area, but to explore as well.

Dick says his time at Illinois “gave us a really good engineering foundation along with solid problem solving skills.”

Giving advice to current students, Janet says, “the first two years are probably going to be tough but just keep at it. Once you get past that and you get into your Engineering courses you’ll really get an appreciation for what you can do beyond the basics.”

Dick and Janet with their two sons, Nate and Luke

As a freshman Janet was told to take a ballroom dancing class “because every engineer needed to take ballroom dancing to get ahead in her career.” She says, “I didn’t find that to be true, so if you want to take ballroom dancing, go ahead, but I can’t say it was an effective tool for career advancement.”

Dick suggests that students should take courses outside of their comfort zone. He says, “it really helps engineers in the long run to take an art history class or a course in Shakespeare,” because those courses “continue to benefit our lives outside of the workplace.” Dick also tells students signing up for classes to focus not only on course content, but also the professor teaching the course. He says that with time, “You may not remember the details of the course content, but you will remember the professor and the energy and enthusiasm for the material.”

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