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Matthew Anderson Bsge Homework

Package Index

Packages in the standard library

ACCLMAACC & LMA Graph Plotting
ADGofTestAnderson-Darling GoF test
AERApplied Econometrics with R
AGSDestEstimation in adaptive group sequential trials
AICcmodavgModel selection and multimodel inference based on (Q)AIC(c)
AIGISAreal Interpolation for GIS data
AIMAIM: adaptive index model
ALSmultivariate curve resolution alternating least squares (MCR-ALS)
AMOREA MORE flexible neural network package
AcceptanceSamplingCreation and evaluation of Acceptance Sampling Plans
AdMitAdaptive Mixture of Student-t distributions
AdaptFitAdaptive Semiparametic Regression
AlgDesignAlgorithmic Experimental Design
AllPossibleSpellingsComputes all of a word's possible spellings.
AmeliaAmelia II: A Program for Missing Data
AnalyzeFMRIFunctions for analysis of fMRI datasets stored in the ANALYZE or NIFTI format.
AnimalAnalyze time-coded animal behavior data
AnnotListsData extraction tool from annotations files.
AnnotationDbiAnnotation Database Interface
AquaEnvAquaEnv - an integrated development toolbox for aquatic chemical model generation
ArDecTime series autoregressive-based decomposition
B2ZBayesian Two-Zone Model
BACCOBayesian Analysis of Computer Code Output (BACCO)
BAMDBayesian Association Model for Genomic Data with Missing Covariates
BARDBetter Automated ReDistricting
BASBayesian Model Averaging using Bayesian Adaptive Sampling
BAYSTAROn Bayesian analysis of Threshold autoregressive model (BAYSTAR)
BBSolving and Optimizing Large-Scale Nonlinear Systems
BBMMBrownian bridge movement model for estimating the movement path of an animal using discrete location data.
BCEBayesian composition estimator: estimating sample (taxonomic) composition from biomarker data
BGSIMDBlock Gibbs Sampler with Incomplete Multinomial Distribution
BHH2Useful Functions for Box, Hunter and Hunter II
BLCOPBlack-Litterman and copula-opinion pooling frameworks
BLRBayesian Linear Regression
BMABayesian Model Averaging
BMNThe pseudo-likelihood method for pairwise binary markov networks
BMSBayesian Model Averaging Library
BPHOBayesian Prediction with High-order Interactions
BSDABasic Statistics and Data Analysis
BSagriStatistical methods for safety assessment in agricultural field trials
BSgenomeInfrastructure for Biostrings-based genome data packages
BaBooNThe Bayesian Bootstrap Predictive Mean Matching Package - Multiple and single imputation for discrete data
BaMFunctions and datasets for books by Jeff Gill.
BayHapBayesian analysis of haplotype association using Markov Chain Monte Carlo
BayHazR Functions for Bayesian Hazard Rate Estimation
BayesDAFunctions and Datasets for the book "Bayesian Data Analysis"
BayesPeakBayesian Analysis of ChIP-seq Data
BayesQTLBICBayesian multi-locus QTL analysis based on the BIC criterion
BayesTreeBayesian Methods for Tree Based Models
BayesValidateBayesValidate Package
BayesXR Utilities Accompanying the Software Package BayesX
BergmBayesian inference for exponential random graph models
BhatGeneral likelihood exploration
BiasedUrnBiased Urn model distributions
BioIDMapperMapping between BioIDs
BioStatRInitiation la Statistique avec R
BiobaseBiobase: Base functions for Bioconductor
BiodemBiodemography functions
BiodiversityRGUI for biodiversity and community ecology analysis
BiographExplore life histories
BiostringsString objects representing biological sequences, and matching algorithms
BlakerCIBlaker's binomial confidence limits
BmixBayesian Sampling for Stick-breaking Mixtures
BoSSAa Bunch of Structure and Sequence Analysis
BolstadBolstad functions
Bolstad2Bolstad functions
BoolNetGeneration, reconstruction, simulation and analysis of synchronous, asynchronous, and probabilistic Boolean networks
BootPRBootstrap Prediction Intervals and Bias-Corrected Forecasting
BorutaBoruta -- a tool for finding significant attributes in information systems
BradleyTerryBradley-Terry Models -- this package is now deprecated in favour of 'BradleyTerry2'
BradleyTerry2Bradley-Terry models
BrobdingnagVery large numbers in R
BsMDBayes Screening and Model Discrimination
CADFtestHansen's Covariate-Augmented Dickey-Fuller (CADF) Test
CAVIARCambial Activity and wood formation data processing, visualisation and analysis using R
CCACanonical correlation analysis
CCMtoolsClustering through "Correlation Clustering Model" (CCM) and cluster analysis tools.
CCPSignificance Tests for Canonical Correlation Analysis (CCA)
CDFtStatistical downscaling through CDF-transform
CDNmoneyComponents of Canadian Monetary and Credit Aggregates
CFLCompensatory Fuzzy Logic
CGIwithRCGI Programming in R
CGeneCausal Genetic Analysis
CHNOSZChemical Thermodynamics and Activity Diagrams
CHsharpChoi and Hall Clustering in 3d
CMCCronbach-Mesbah Curve
CNVassocAssociation analysis of CNV data
COMPoissonRegConway-Maxwell Poisson (COM-Poisson) Regression
COPVariables selection for index models via correlation pursuit
CORElearnCORElearn - classification, regression, feature evaluation and ordinal evaluation
CORREPMultivariate Correlation Estimator and Statistical Inference Procedures.
COSINECOndition SpecIfic sub-NEtwork
COUNTFunctions, data and code for count data.
COZIGAMConstrained and Unconstrained Zero-Inflated Generalized Additive Models with Model Selection Criterion
CPEConcordance Probability Estimates in Survival Analysis
CRTSizeSample Size Estimation Functions for Cluster Randomized Trials
CTTClassical Test Theory Functions
CVThreshLevel-Dependent Cross-Validation Thresholding
CairoR graphics device using cairo graphics library for creating high-quality bitmap (PNG, JPEG, TIFF), vector (PDF, SVG, PostScript) and display (X11 and Win32) output.
CalciOMaticAutomatic Calcium Imaging Analysis
CarbonELCarbon Event Loop
CausalGAMEstimation of Causal Effects with Generalized Additive Models
CellularAutomatonOne-Dimensional Cellular Automata
ChainLadderMack, Bootstrap, Munich, Multivariate-chain-ladder and Clark methods for insurance claims reserving
CircNNTSRCircNNTSR: An R package for the statistical analysis of circular data using nonnegative trigonometric sums (NNTS) models
CircSpatialFunctions For Circular Spatial Data
CircStatsCircular Statistics, from "Topics in circular Statistics" (2001)
Ckmeans.1d.dpOptimal distance-based clustering for one-dimensional data
ClinicalRobustPriorsRobust Bayesian Priors in Clinical Trials: An R Package for Practitioners
ClustOfVarClustering of variables
CoCoGraphical modelling by log-linear models (an interface from R to CoCo)
CoCoCgGraphical modelling by CG regressions
CoCoGraphInteractive and dynamic graphs for the CoCo objects
CollocInferCollocation Inference for Dynamic Systems
CombMSCCombined Model Selection Criteria
CompQuadFormDistribution function of quadratic forms in normal variables
CompRandFldComposite-likelihood based Analysis of Random Fields
CompetingRiskFrailtyCompeting Risk Model with Frailties for Right Censored Survival Data
ConvCalendarConverts dates between calendars
ConvergenceConceptsSeeing convergence concepts in action
CorrBinNonparametrics with clustered binary data
CoxBoostCox models by likelihood based boosting for a single survival endpoint or competing risks
CprobConditional probability function of a competing event
CreditMetricsFunctions for calculating the CreditMetrics risk model
CvM2SL1TestL1-version of Cramer-von Mises Two Sample Tests
CvM2SL2TestCramer-von Mises Two Sample Tests
DAAGData Analysis And Graphics data and functions
DAAGbioData Sets and Functions, for demonstrations with expression arrays and gene sequences
DAAGxtrasData Sets and Functions, supplementary to DAAG
DAKSData Analysis and Knowledge Spaces
DAMiscDave Armstrong's Miscellaneous Functions
DBIR Database Interface
DCGLDifferential Coexpression Analysis of Gene Expression Microarray Data
DClusterFunctions for the detection of spatial clusters of diseases
DDHFmVariance Stabilization by Data-Driven Haar-Fisz (for Microarrays)
DECIDEDEComposition of Indirect and Direct Effects
DEMEticsEvaluating the genetic differentiation between populations based on Gst and D values.
DESeqDigital gene expresion analysis based on the negative binomial distribution
DEoptimGlobal optimization by differential evolution
DMwRFunctions and data for "Data Mining with R"
DNAtoolsTools for analysing forensic genetic DNA data
DOBADAnalysis of Discretely Observed linear Birth-And-Death(-and-immigration) Markov Chains
DPpackageBayesian Nonparametric and Semiparametric Analysis
DSpatSpatial modelling for distance sampling data
DTDADoubly truncated data analysis
DTKDunnett-Tukey-Kramer Pairwise Multiple Comparison Test Adjusted for Unequal Variances and Unequal Sample Sizes
DaimDiagnostic accuracy of classification models.
DatABELfile-based access to large matrices stored on HDD in binary format
DaviesThe Davies quantile function
DefaultsCreate Global Function Defaults
DescribeDisplayR interface to DescribeDisplay (GGobi plugin)
DesignDesign Package
DesignPatternsDesign Patterns in R to build reusable object-oriented software
Devore5Data sets from Devore's "Prob and Stat for Eng (5th ed)"
Devore6Data sets from Devore's "Prob and Stat for Eng (6th ed)"
Devore7Data sets from Devore's "Prob and Stat for Eng (7th ed)"
DiagnosisMedDiagnostic test accuracy evaluation for medical professionals.
DiceDesignDesigns of Computer Experiments
DiceEvalConstruction and evaluation of metamodels
DiceKrigingKriging methods for computer experiments
DiceOptimKriging-based optimization for computer experiments
DierckxSplineR companion to "Curve and Surface Fitting with Splines"
DistributionUtilsDistribution Utilities
DiversitySamplerFunctions for re-sampling a community matrix to compute diversity indices at different sampling levels.
DoE.baseFull factorials, orthogonal arrays and base utilities for DoE packages
DoE.wrapperWrapper package for design of experiments functionality
DoseFindingPlanning and Analyzing Dose Finding experiments
DynDocDynamic document tools
EDREstimation of the effective dimension reduction (EDR) space
EMCEvolutionary Monte Carlo (EMC) algorithm
EMCCEvolutionary Monte Carlo (EMC) methods for clustering
EMDEmpirical Mode Decomposition and Hilbert Spectral Analysis
EMJumpDiffusionEM-Algorithm for Jump Diffusion processes
EMTExact Multinomial Test: Goodness-of-Fit Test for Discrete Multivariate data
ENmiscNeuwirth miscellaenous
EQLExtended-Quasi-Likelihood-Function (EQL)
ETCEquivalence to control
EVEREstimation of Variance by Efficient Replication
EbayesThreshEmpirical Bayes Thresholding and Related Methods
EcdatData sets for econometrics
EffectiveDoseEstimation of the Effective Dose including Bootstrap confidence intervals
ElectroGraphEnhanced routines for plotting and analyzing valued relational data.
ElemStatLearnData 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.
EmpLikeGOFGoodness of Fit Test for Empirical Likelihood
EnQuireRA package dedicated to questionnaires
EngrExptData sets from "Introductory Statistics for Engineering Experimentation"
EpiA package for statistical analysis in epidemiology.
EquiNormNormalize expression data using equivalently expressed genes
EvalEstDynamic Systems Estimation - extensions
ExPD2DExact Computation of Bivariate Projection Depth Based on Fortran Code
FAMTFactor Analysis for Multiple Testing (FAMT) : simultaneous tests under dependence in high-dimensional data
FAwRFunctions and Datasets for "Forest Analytics with R".
FBNFISH Based Normalization and Copy Number inference of SNP microarray data
FDMeasuring functional diversity (FD) from multiple traits, and other tools for functional ecology
FGNFractional Gaussian Noise, estimation and simulaton
FITSioFITS (Flexible Image Transport System) utilities
FKFFast Kalman Filter
FMEA Flexible Modelling Environment for Inverse Modelling, Sensitivity, Identifiability, Monte Carlo Analysis.
FNNFast Nearest Neighbor Search Algorithms and Applications
FRBFast and Robust Bootstrap
FTICRMSPrograms for Analyzing Fourier Transform-Ion Cyclotron Resonance Mass Spectrometry Data
FactoClassCombination of Factorial Methods and Cluster Analysis
FactoMineRMultivariate Exploratory Data Analysis and Data Mining with R
FahrmeirData from the book "Multivariate Statistical Modelling Based on Generalized Linear Models", first edition, by Ludwig Fahrmeir and Gerhard Tutz
FeaLectScores features for Feature seLection
FinTSCompanion to Tsay (2005) Analysis of Financial Time Series
FitARSubset AR Model Fitting
FitARMAFitARMA: Fit ARMA or ARIMA using fast MLE algorithm
FluryData Sets from Flury, 1997
FormulaExtended Model Formulas
FourierDescriptorsGenerate images using Fourier descriptors.
FrF2Fractional Factorial designs with 2-level factors
FrF2.catlg128Complete catalogues of resolution IV 128 run 2-level fractional factorials up to 24 factors
FracSimSimulation of Lvy motions
FunClusterFunctional Profiling of Microarray Expression Data
FunNetIntegrative Functional Analysis of Transcriptional Networks
FuncMapHive Plots of R Package Function Calls
FunctSNPFunctSNP - SNP annotation data methods and species specific database builder
G1DBNA package performing Dynamic Bayesian Network inference.
GADGeneral ANOVA Design (GAD): Analysis of variance from general principles
GAMBoostGeneralized linear and additive models by likelihood based boosting
GAMensApplies GAMbag, GAMrsm and GAMens ensemble classifiers for binary classification
GB2Generalized Beta Distribution of the Second Kind: properties, likelihood, estimation.
GEOmapTopographic and Geologic Mapping
GEVcdnGEV conditonal density estimation network
GExMapA visual, intuitive, easy to use software giving access to a new type of information buried into your microarray data.
GGMselectGaussian Graphs Models selection
GGallyExtension to ggplot2.
GLDEXFitting Single and Mixture of Generalised Lambda Distributions (RS and FMKL) using Various Methods
GLMMarpGeneralized Linear Multilevel Model with AR(p) Errors Package
GO.dbA set of annotation maps describing the entire Gene Ontology
GOFSNGoodness-of-fit tests for the family of skew-normal models
GPArotationGPA Factor Rotation
GPseqgpseq: Using the generalized Poisson distribution to model sequence read counts from high throughput sequencing experiments
GRRGIGauge R and R Confidence Intervals
GSAGene set analysis
GSMGamma Shape Mixture
GWAFGenome-Wide Association analyses with Family data
GWASExactHWExact Hardy-Weinburg testing for Genome Wide Association Studies
GenABELgenome-wide SNP association analysis
GenKernFunctions for generating and manipulating binned kernel density estimates
GeneCycleIdentification of Periodically Expressed Genes
GeneFPackage for Generalized F-statistics
GeneNetModeling and Inferring Gene Networks
GeneRegConstruct time delay gene regulatory network
GeneclustSimulation and analysis of spatial structure of population genetics data
GenelandDetection of structure from multilocus genetic data.
GeneralizedHyperbolicThe generalized hyperbolic distribution
GenomicRangesRepresentation and manipulation of genomic intervals
GillespieSSAGillespie's Stochastic Simulation Algorithm (SSA)
GrapheRA multiplatform GUI for drawing highly customizable common graphs in R
GrassmannOptimGrassmann Manifold Optimization
GridRExecutes functions on remote hosts, clusters or grids.
GroupSeqPerforming computations related to group sequential designs.
GuerryGuerry: maps, data and methods related to Guerry (1833) "Moral Statistics of France"
HDMDStatistical Analysis Tools for High Dimension Molecular Data (HDMD)
HDclassifHigh Dimensionnal Classification.
HFWutilscsv import, csv export, garbage collection,string matching and passing by reference
HGLMMMHierarchical Generalized Linear Models
HHStatistical Analysis and Data Display: Heiberger and Holland
HISimulation from distributions supported by nested hyperplanes
HMMHMM - Hidden Markov Models
HMRFlux estimation with static chamber data
HPbayesHeligman Pollard mortality model parameter estimation using Bayesian Melding with Incremental Mixture Importance Sampling
HSAURA Handbook of Statistical Analyses Using R
HSAUR2A Handbook of Statistical Analyses Using R (2nd Edition)
HTMLUtilsFacilitates automated HTML report creation
HWEBayesBayesian investigation of Hardy-Weinberg Equilibrium via estimation and testing.
HWEintrinsicObjective Bayesian Testing for the Hardy-Weinberg Equilibrium Problem
HadoopStreamingUtilities for using R scripts in Hadoop streaming
HaplinAnalyzing case-parent triad and/or case-control data with SNP haplotypes
HardyWeinbergGraphical tests for Hardy-Weinberg equilibrium
HiddenMarkovHidden Markov Models
HistDataData sets from the history of statistics and data visualization
HmiscHarrell Miscellaneous
HybridMCImplementation of the Hybrid Monte Carlo and Multipoint Hybrid Monte Carlo sampling techniques
HydroMeEstimation of Soil Hydraulic Parameters from Experimental Data
HyperbolicDistThe hyperbolic distribution
IBrokersR API to Interactive Brokers Trader Workstation
ICEIterated Conditional Expectation
ICEinferIncremental Cost-Effectiveness (ICE) Statistical Inference from Two Unbiased Samples
ICSTools for Exploring Multivariate Data via ICS/ICA
ICSNPTools for Multivariate Nonparametrics
IDPmiscUtilities of Institute of Data Analyses and Process Design (www.idp.zhaw.ch)
IFPIdentifying functional polymorphisms in genetic association studies
IMISIncreamental Mixture Importance Sampling
IPSURIntroduction to Probability and Statistics Using R
IQCCImproved Quality Control Charts
IRangesInfrastructure for manipulating intervals on sequences
ISOcodesSelected ISO codes
ISwRIntroductory Statistics with R
IcensNPMLE for Censored and Truncated Data
ImapInteractive Mapping
ImpactIVIdentifying Causal Effect for Multi-Component Intervention Using Instrumental Variable Method
IniStatRInitiation la Statistique avec R
InterpolInterpolation of amino acid sequences
IsoFunctions to perform isotonic regression.
IsoGeneTesting for monotonic relationship between gene expression and doses in a microarray experiment.
JADEJADE and ICA performance criteria
JJcorrCalculates polychorical correlations for several copula families.
JMJoint Modelling of Longitudinal and Survival Data
JOPJoint Optimization Plot
JointModelingJoint Modelling of Mean and Dispersion
KEGG.dbA set of annotation maps for KEGG
KFASKalman filter and smoothers for exponential family state space models.
KMsurvData sets from Klein and Moeschberger (1997), Survival Analysis
KendallKendall rank correlation and Mann-Kendall trend test
KernSmoothFunctions for kernel smoothing for Wand & Jones (1995)
KrigInvKriging-based Inversion for Deterministic and Noisy Computer Experiments
LCAextendLatent Class Analysis (LCA) with familial dependence in extended pedigrees
LDdiagLink Function and Distribution Diagnostic Test for Social Science Researchers
LDheatmapGraphical display of pairwise linkage disequilibria between SNPs
LDtestsExact tests for Linkage Disequilibrium and Hardy-Weinberg Equilibrium
LIMLinear Inverse Model examples and solution methods.
LIStestLongest Increasing Subsequence Independence Test
LLAhclustHierarchical clustering of variables or objects based on the likelihood linkage analysis method
LLdecompDecomposes a set of variables into cliques and separators.
LMERConvenienceFunctionsAn assortment of functions to facilitate modeling with linear mixed-effects regression (LMER).
LMGeneLMGene Software for Data Transformation and Identification of Differentially Expressed Genes in Gene Expression Arrays
LPCMLocal principal curve methods
LS2WLocally stationary two-dimensional wavelet process estimation scheme
LSDLots of Superior Depictions
LVQToolsLearning Vector Quantization Tools
LambertWGaussianize and analyze skewed, heavy-tailed data
LaplacesDemonLaplace's Demon: Software for Bayesian Inference
LearnBayesFunctions for Learning Bayesian Inference
LearnEDAFunctions for Learning Exploratory Data Analysis
LiblineaRLinear Predictive Models Based On The Liblinear C/C++ Library.
LmomentsL-moments and quantile mixtures
LogConcDEADLog-concave Density Estimation in Arbitrary Dimensions
LogicForestLogic Forest
LogicRegLogic Regression
LogitNetInfer network based on binary arrays using regularized logistic regression
LoopAnalystA collection of tools to conduct Levins' Loop Analysis
LowRankQPLow Rank Quadratic Programming
MAMSECalculation of Minimum Averaged Mean Squared Error (MAMSE) weights.
MARSSMultivariate Autoregressive State-Space Modeling
MASSSupport Functions and Datasets for Venables and Ripley's MASS
MATMultidimensional Adaptive Testing (MAT)
MAcMeta-Analysis with Correlations
MAclinicalClass prediction based on microarray data and clinical parameters
MAdMeta-Analysis with Mean Differences
MCAPSMCAPS data and results
MCETools for evaluating Monte Carlo Error
MCLIMESimultaneous Estimation of the Regression Coefficients and Precision Matrix
MCMCglmmMCMC Generalised Linear Mixed Models
MCMChybridGPHybrid Markov chain Monte Carlo using Gaussian Processes
MCMCpackMarkov chain Monte Carlo (MCMC) Package
MCPANMultiple comparisons using normal approximation
MCPModDesign and Analysis of Dose-Finding Studies (see also DoseFinding package)
MChtestMonte Carlo hypothesis tests with Sequential Stopping
MDRDetect gene-gene interactions using multifactor dimensionality reduction
MEMSSData sets from Mixed-effects Models in S
MFDAModel Based Functional Data Analysis
MFDFModeling Functional Data in Finance
MIfunsPharmacometric tools for data preparation, modeling, simulation, and reporting
MImixMixture summary method for multiple imputation
MKLEMaximum kernel likelihood estimation.
MKmiscMiscellaneous Functions from M. Kohl
MLCMMaximum Likelihood Conjoint Measurement
MLDAMethylation Linear Discriminant Analysis (MLDA)
MLDSMaximum Likelihood Difference Scaling
MLEcensComputation of the MLE for bivariate (interval) censored data
MLPAstatsMLPA analysis to detect gains and loses in genes
MMGMixture Model on Graphs
MMIXModel selection uncertainty and model mixing
MNMMultivariate Nonparametric Methods. An Approach Based on Spatial Signs and Ranks
MNPR Package for Fitting the Multinomial Probit Model
MOCCAMulti-objective optimization for collecting cluster alternatives
MPVData Sets from Montgomery, Peck and Vining's Book
MSBVARMarkov-Switching, Bayesian, Vector Autoregression Models
MSToolkitThe MSToolkit library for clinical trial design
MTSKNNMultivariate two-sample tests based on K-nearest-neighbors
MVpowerGive power for a given effect size using multivariate classification methods
MaXactExact max-type Cochran-Armitage trend test(CATT)
MarkedPointProcessAnalysis of Marks of Marked Point Processes
MasterBayesML and MCMC Methods for Pedigree Reconstruction and Analysis
MatchingMultivariate and Propensity Score Matching with Balance Optimization
MatrixSparse and Dense Matrix Classes and Methods
MatrixModelsModelling with Sparse And Dense Matrices
McompData from the M-competitions
MeDiChIMeDiChI ChIP-chip deconvolution library
MetabolAnalyzeProbabilistic latent variable models for metabolomic data.
MineyImplementation of the Well-Known Game to Clear Bombs from a Given Field (Matrix)
MiscPsychoMiscellaneous Psychometric Analyses
MixSimSimulating Data to Study Performance of Clustering Algorithms.
ModalclustHierarchical Modal Clustering
ModelGoodValidation of prediction models
MortalitySmoothSmoothing Poisson counts with P-splines
MplusAutomationAutomating Mplus Model Estimation and Interpretation
MsatAlleleVisualizes the scoring and binning of microsatellite fragment sizes
MuMInMulti-model inference
MultEqMultiple equivalence tests and simultaneous confidence intervals
MulticlasstestingPerformance of N-ary classification testing
NADANondetects And Data Analysis for environmental data
NCBI2RNCBI2R-An R package to navigate and annotate genes and SNPs
NISTnlsNonlinear least squares examples from NIST
NMFAlgorithms and framework for Nonnegative Matrix Factorization (NMF).
NMFNNon-negative Matrix Factorization
NMRSNMR Spectroscopy
NORMT3Evaluates complex erf, erfc, Faddeeva, and density of sum of Gaussian and Student's t
NRAIAData sets from "Nonlinear Regression Analysis and Its Applications"
NestedCohortSurvival Analysis for Cohorts with Missing Covariate Information
NetClusterClustering for networks
NetDataNetwork Data for McFarland's SNA R labs
NetIndicesEstimating network indices, including trophic structure of foodwebs in R
NetworkAnalysisStatistical inference on populations of weighted or unweighted networks.
OAIHarvesterHarvest Metadata Using OAI-PMH v2.0
OPEOuter-product emulator
ORDER2PARENTEstimate parent distributions with data of several order statistics
ORIClustOrder-restricted Information Criterion-based Clustering Algorithm
OSACCOrdered Subset Analysis for Case-Control Studies
OarrayArrays with arbitrary offsets
OjaNPMultivariate Methods Based on the Oja Median and Related Concepts
OligoSpecificitySystemOligo Specificity System
OncotreeEstimating oncogenetic trees
OrdFacRegLeast squares, logistic, and Cox-regression with ordered predictors
OrdMonRegCompute least squares estimates of one bounded or two ordered isotonic regression curves
OrgMassSpecROrganic Mass Spectrometry
PBSddesolveSolver for Delay Differential Equations
PBSmappingMapping Fisheries Data and Spatial Analysis Tools
PBSmodellingGUI Tools Made Easy: Interact with Models, Explore Data, Give Dynamic Presentations
PCITPCIT algorithm - Partial Correlation Coefficient with Information Theory
PCSCalculate the probability of correct selection (PCS)
PERregressRegression Functions and Datasets
PETSimulation and Reconstruction of PET Images
PHYLOGRFunctions for phylogenetically based statistical analyses
PKBasic Non-Compartmental Pharmacokinetics
PKfitA Data Analysis Tool for Pharmacokinetics
PKreportA reporting pipeline for checking population pharmacokinetic model assumption
PKtoolsunified computational interfaces for pop PK
PLISMultiplicity control using Pooled LIS statisitcs
PMAPenalized Multivariate Analysis
POTGeneralized Pareto Distribution and Peaks Over Threshold
PSAgraphicsPropensity Score Analysis Graphics
PSMNon-Linear Mixed-Effects modelling using Stochastic Differential Equations.
PTAkPrincipal Tensor Analysis on k modes
PairVizVisualization using Eulerian tours and Hamiltonian decompositions
PearsonDSPearson Distribution System
PearsonICAIndependent component analysis using score functions from the Pearson system
PerformanceAnalyticsEconometric tools for performance and risk analysis.
PermAlgoPermutational algorithm to simulate survival data
PhysicalActivityProcess Physical Activity Accelerometer Data
PolynomFPolynomials in R
PomicPattern Oriented Modelling Information Criterion
PowerTOSTPower and Sample size based on two one-sided t-tests (TOST) for bioequivalence studies
PredictiveRegressionPrediction Intervals for Three Basic Statistical Models
PresenceAbsencePresence-Absence Model Evaluation.
ProDenICAProduct Density Estimation for ICA using tilted Gaussian density estimates
ProbForecastGOPProbabilistic weather forecast using the GOP method
ProfessRGrades Setting and Exam Maker
ProfileLikelihoodProfile Likelihood for a Parameter in Commonly Used Statistical Models
ProjectTemplateAutomates the creation of new statistical analysis projects.
PropCIsComputes confidence intervals for single proportions, for differences in proportions, for an odds-ratio and for the relative risk in a 2x2 table
PtProcessTime Dependent Point Process Modelling
PwrGSDPower in a Group Sequential Design
QCAQualitative Comparative Analysis
QCA3Yet another package for Qualitative Comparative Analysis
QCAGUIQCA Graphical User Interface
QRMlibProvides R-language code to examine Quantitative Risk Management concepts
QSARdataQuantitative Structure Activity Relationship (QSAR) Data Sets
QTQT Knowledge Management System
QTLRelTools for mapping of quantitative traits of genetically related individuals
QuantPsycQuantitative Psychology Tools
R.cacheFast and light-weight caching of objects
R.filesetsEasy handling of and access to files organized in structured directories
R.hugeMethods for accessing huge amounts of data [DEPRECATED]
R.matlabRead and write of MAT files together with R-to-Matlab connectivity
R.methodsS3Utility function for defining S3 methods
R.ooR object-oriented programming with or without references
R.rspR Server Pages
R.utilsVarious programming utilities
R2CubaMultidimensional Numerical Integration
R2HTMLHTML exportation for R objects
R2WinBUGSRunning WinBUGS and OpenBUGS from R / S-PLUS
R4dfp4dfp MRI Image Read and Write Routines
RANNFast Nearest Neighbour Search
RArcInfoFunctions to import data from Arc/Info V7.x binary coverages
RBGLAn interface to the BOOST graph library
RBerkeleyR API to Oracle Berkeley DB
RBrownieContinuous and discrete ancestral character reconstruction and evolutionary rate tests.
RCReproducible Computing
RColorBrewerColorBrewer palettes
RCurlGeneral network (HTTP/FTP/...) client interface for R
RDSR Functions for Respondent-Driven Sampling
REEMtreeRegression Trees with Random Effects for Longitudinal (Panel) Data
REQSR/EQS Interface
RFARegional Frequency Analysis
RFLPtoolsTools to analyse RFLP data
RFOCGraphics for Spherical Distributions and Earthquake Focal Mechanisms
RGCCARegularized Generalized Canonical Correlation Analysis
RGraphicsData and Functions from the book R Graphics
RHRVHeart rate variability analysis of ECG data
RHmmHidden Markov Models simulations and estimations
RInsideC++ classes to embed R in C++ applications
RItoolsRandomization inference tools
RJSONIOSerialize R objects to JSON, JavaScript Object Notation
RJaCGHReversible Jump MCMC for the analysis of CGH arrays.
RLMMA Genotype Calling Algorithm for Affymetrix SNP Arrays
RLRsimExact (Restricted) Likelihood Ratio tests for mixed and additive models.
RLastFMR interface to last.fm API
RM2Revenue Management and Pricing Package
RMCFunctions for fitting Markov models
RMTstatDistributions, Statistics and Tests derived from Random Matrix Theory
RNCEPObtain, organize, and visualize NCEP weather data
RNiftyRegMedical image registration using the NiftyReg library
ROCRVisualizing the performance of scoring classifiers.
ROptEstOptimally robust estimation
ROptEstOldOptimally robust estimation - old version
ROptRegTSOptimally robust estimation for regression-type models
RPMGGraphical User Interface (GUI) for interactive R analysis sessions
RPMMRecursively Partitioned Mixture Model
RPPanalyzerReads, annotates, and normalizes reverse phase protein array data
RSAGASAGA Geoprocessing and Terrain Analysis in R
RSEISSeismic Time Series Analysis Tools
RSNNSNeural Networks in R using the Stuttgart Neural Network Simulator (SNNS)
RSQLiteSQLite interface for R
RSQLite.extfunsMath and String Extension Functions for RSQLite
RSVGTipsDeviceAn R SVG graphics device with dynamic tips and hyperlinks
RSeqMethPackage for analysis of Sequenom EpiTYPER Data
RSienaSiena - Simulation Investigation for Empirical Network Analysis
RSvgDeviceAn R SVG graphics device.
RTOMOVisualization for seismic tomography
RTiseanR interface to Tisean algorithms
RUnitR Unit test framework
RXshrinkMaximum Likelihood Shrinkage via Generalized Ridge or Least Angle Regression
RadioSondeTools for plotting skew-T diagrams and wind profiles
RandVarImplementation of random variables
RandomFieldsSimulation and Analysis of Random Fields
RankAggregWeighted rank aggregation
RaschSamplerRasch Sampler
RassocRobust tests for case-control genetic association studies
RatingsModel-based Ratings Figures
RcaptureLoglinear Models for Capture-Recapture Experiments
RcgminConjugate gradient minimization of nonlinear functions with box constraints
RcmdrR Commander
RcmdrPlugin.DoER Commander Plugin for (industrial) Design of Experiments
RcmdrPlugin.EHESsamplingTools for sampling in European Health Examination Surveys (EHES)
RcmdrPlugin.ExportGraphically export output to LaTeX or HTML
RcmdrPlugin.FactoMineRGraphical User Interface for FactoMineR
RcmdrPlugin.HHRcmdr support for the HH package
RcmdrPlugin.IPSURAn IPSUR Plugin for the R Commander
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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

Fred Jewell started at the U of I in 1983 as a freshman studying Computer Engineering. Julie Furmanek began at Illinois the same time, studying Bioengineering. Both of them ended up transferring into General Engineering (now renamed Systems Engineering and Design) by their sophomore year, and they met each other in class.

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

At Accenture, Julie says she did “client work, technology coding and implementing systems” and worked “on the technology support side of things, supporting the manufacturing, the inventory control and ultimately some of the finance side of the application.” Today, Julie works at Anthem, Inc. as an IT change management lead.

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.

Lynda Wort and Tim McGrath didn’t meet each other until their junior year at Illinois, after Lynda transferred to Illinois from Lincoln Land Community College. They both graduated with their bachelors' degrees in Industrial Engineering in 1983 and they got married a year later. 


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

At Illinois, Lynda worked in the engineering library, was involved in the American Institute of Industrial Engineers (AIIE), and she tutored students. 


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

Tim’s career has been more unpredictable. He says, “it’s a little bit non-traditional for an industrial engineer.” After earning his MBA, Tim worked as a market research analyst at Leo Burnett Advertising. He says, “While I was working at Leo Burnett, I started to rethink my own career path… I went back to school to get my teaching certification so I could teach math. I taught math in middle school and high school for several years and then at some point I decided to go back to school again and get my masters in school counseling.” For the past 11 years, Tim has worked as a high school counselor. 


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

Tim says his conversation with DeVor taught him “how understanding people can be within giant organizations and… how to always look towards how to help students first and to teach them the content at the same time.” He also says it helps him to “remember that you’re working with students who have thoughts, who have goals, who also have limitations and to always try to be understanding and compassionate as an educator.” This lesson, Tim says is “something that I was always grateful to Professor DeVor for and likewise the University.” 


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

In college, they say the best place to find the perfect spouse isn’t in the bars, but in the library. That is exactly what happened to Richard “Dick” Henneman and Janet Fath in the fall of 1979.  

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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