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"name": "R-nlstools",
"description": "Tools for non-linear regression analysis"
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{
"name": "R-nltm",
"description": "Non-Linear Transformation Models"
},
{
"name": "R-nlts",
"description": "Non-linear time series analysis"
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{
"name": "R-NMA",
"description": "Network meta-analysis based on multivariate meta-analysis models"
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{
"name": "R-NMF",
"description": "Algorithms and framework for nonnegative matrix factorization (NMF)"
},
{
"name": "R-nmfbin",
"description": "Non-negative matrix factorization for binary data"
},
{
"name": "R-NMI",
"description": "Normalized Mutual Information of community structure in network"
},
{
"name": "R-Nmix",
"description": "Bayesian inference on univariate normal mixtures"
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{
"name": "R-NMOF",
"description": "Numerical Methods and Optimization in Finance"
},
{
"name": "R-nna",
"description": "Nearest-Neighbor Analysis"
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{
"name": "R-nnet",
"description": "Feed-forward neural networks and multinomial log-linear models"
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{
"name": "R-nnfor",
"description": "Time series forecasting with neural networks"
},
{
"name": "R-nnlasso",
"description": "Non-negative lasso and elastic net penalized generalized linear models"
},
{
"name": "R-nnlib2Rcpp",
"description": "Tool for creating custom neural networks in C++ and using them in R"
},
{
"name": "R-nnls",
"description": "The Lawson–Hanson algorithm for non-negative least squares"
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{
"name": "R-NNS",
"description": "Non-linear Non-parametric Statistics"
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{
"name": "R-nnTensor",
"description": "Non-negative tensor decomposition"
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{
"name": "R-noisemodel",
"description": "Noise models for classification datasets"
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{
"name": "R-nonnest2",
"description": "Tests of non-nested models"
},
{
"name": "R-NonProbEst",
"description": "Estimation in non-probability sampling"
},
{
"name": "R-nor1mix",
"description": "Gaussian mixture models (S3 classes and methods)"
},
{
"name": "R-norm",
"description": "Analysis of multivariate normal datasets with missing values"
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{
"name": "R-norm2",
"description": "Analysis of incomplete multivariate data under a normal model"
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{
"name": "R-normalize",
"description": "Centering and scaling of numeric data"
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{
"name": "R-NormalLaplace",
"description": "Normal Laplace Distribution"
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{
"name": "R-normalp",
"description": "Routines for exponential power distribution"
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{
"name": "R-norMmix",
"description": "Direct MLE for multivariate normal mixture distributions"
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{
"name": "R-NormPsy",
"description": "Normalisation of psychometric tests"
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{
"name": "R-nortest",
"description": "Tests for normality"
},
{
"name": "R-not",
"description": "Narrowest-over-threshold change-point detection"
},
{
"name": "R-NovelDistns",
"description": "Computes PDF, CDF, quantile, random numbers and measures of inference for 3 general families of distributions."
},
{
"name": "R-np",
"description": "Nonparametric kernel smoothing methods for mixed data types"
},
{
"name": "R-nparcomp",
"description": "Multiple comparisons and simultaneous confidence intervals"
},
{
"name": "R-npcs",
"description": "Neyman–Pearson classification via cost-sensitive learning"
},
{
"name": "R-npde",
"description": "Normalised prediction distribution errors for nonlinear mixed-effect models"
},
{
"name": "R-NPflow",
"description": "Bayesian Non-parametrics for automatic gating of flow-cytometry data"
},
{
"name": "R-npmlreg",
"description": "Non-parametric maximum likelihood estimation for random effect models"
},
{
"name": "R-NPP",
"description": "Normalized Power Prior Bayesian analysis"
},
{
"name": "R-NPRED",
"description": "Predictor identifier – nonparametric prediction"
},
{
"name": "R-npsf",
"description": "Non-parametric and stochastic efficiency and productivity analysis"
},
{
"name": "R-npsr",
"description": "Validate instrumental variables using NPS"
},
{
"name": "R-npsurvSS",
"description": "Sample size and power calculation for common non-parametric tests in survival analysis"
},
{
"name": "R-nseval",
"description": "Tools for lazy and non-standard evaluation"
},
{
"name": "R-nsyllable",
"description": "Count syllables in character vectors"
},
{
"name": "R-nullabor",
"description": "Tools for graphical inference"
},
{
"name": "R-numbers",
"description": "Number-theoretic functions"
},
{
"name": "R-numDeriv",
"description": "Accurate numerical derivatives"
},
{
"name": "R-Numero",
"description": "Statistical framework to define subgroups in complex datasets"
},
{
"name": "R-numGen",
"description": "A number series generator that creates number series items based on cognitive models"
},
{
"name": "R-nycflights13",
"description": "Flights departed from NYC in 2013"
}
]
}