# Collection of portable choice dialog widgets in R

The following package and source code is collection of portable choice dialog widgets.

The following package and source code is collection of portable choice dialog widgets.

The following package and source code is about Multi-path General-to-Specific (GETS) model selection of the mean and log-volatility specification.

The following package and source code uses model selection tools to fit parametric curves.

The following package and source code is about ordinary least square test and Multivariate Analysis.

This package implements a method for normalization, testing, and false discovery rate estimation for RNA-sequencing data

This package implements a dynamic programming algorithm to cluster one-dimensional data optimally, by minimizing the sum of squares of within-cluster distances.

This package provides utilities to estimate and make inference on two summary measures for diagnostic tests.

extreme value analysis (EVA) is a branch of statistics dealing with the extreme deviations from the median of probability distributions.This package is used for doing extreme value analysis.

Graphical Markov models (GMM) use graphs, either undirected, directed, or mixed, to represent multivariate dependences in a visual and computationally efficient manner. The following are Functions for analyzing and fitting Graphical Markov models.

3D printing is a process of making a three-dimensional solid object of virtually any shape from a digital model. This package is used for visualizing data using a 3D printer Package r2stl converts R data to STL (stereolithography) files that can be used to feed a 3-dimensional printer

a generalized additive model (GAM) is a generalized linear model in which the linear predictor depends linearly on unknown smooth functions of some predictor variables, and interest focuses on inference about these smooth functions. The following package is about Robust Generalized Additive Model.

This package is working for inequal and incompatible timepoints between impulse and response curves. A numerical convolution method is also available.

This package is used to compute spillover measures, especially spillover tables and spillover indices.

Canonical correlation analysis is a popular statistical method for the study of the correlations between two sets of variables. This package implements the functions associated with Fast Regularized Canonical Correlation Analysis.

This package is used to fit free-knot splines for data with one independent variable and one dependent variable.

This package is used for re-parametrization of mixed model formulation to allow for a fixed residual variance.

This package is used to compute several IRT and non-IRT based statistical indices that is proposed in the literature for detecting answer copying on multiple-choice examinations..

This package is used to specify and fit generalized nonlinear models.

This package is ued to verify discrete,continuous, probabilistic forecasts as parametric distributions.

The following package is about bias correction of second order of the maximum likelihood estimators of the parameters of the beta regression model.

The following package can perform loop analysis and plot network structure,minimum spanning tree, loop decomposition of weighted directed graphs is included.

The following are about R Package for Epidemiologic Data and Graphics.

The following are about Miscellaneous astronomy functions, utilities, and data.

Functions to fit log-multiplicative models using gnm, with support for convenient printing, plots, and jackknife/bootstrap standard errors.

The following source code and r examples are used for risk model and a population description and it will generate a random case-control-study from that risk model and population for you.

The following source code and r examples are used for Linear and logistic ridge regression for small data sets and genome-wide SNP data.

The following source code and r examples are used for Bayesian estimation and variable selection for quantile regression models.

The following source code and r examples are used for Multi-layer perceptron neural network with partial monotonicity constraints.

The following source code and r examples are used for Barnard's unconditional test for 2x2 contingency tables.

This package used to develop a core collection for biological resources like genbanks. A core collection is defined as a sample of accessions that represent, with the lowest possible level of redundancy, the genetic diversity (the richness of gene or genotype categories) of the entire collection.