This package provides core functions and utilities for packages and other code developed by Jordan Mark Barbone.

Multivariate smoothing using iterative bias reduction with kernel, thin plate splines, Duchon splines or low rank splines.

Iterated Function Systems Estimator as in Iacus and La Torre (2005) <doi:10.1155/JAMDS.2005.33>.

Estimate and test inter-generational social mobility effect on an outcome with cross-sectional or longitudinal data.

This package provides functions to extract and handle commonly occurring principal phrases obtained from collections of texts.

This package provides functions and datasets for maximum likelihood fitting of some classes of graphical Markov models.

This package provides functions that read and solve linear inverse problems (food web problems, linear programming problems).

Rhino implements ECMAScript, also known as JavaScript, in Java as specified in the fifth edition of ECMA-262.

Automate downstream visualization & pathway analysis in RNAseq analysis. RVA is a collection of functions that efficiently visualize RNAseq differential expression analysis result from summary statistics tables. It also utilize the Fisher's exact test to evaluate gene set or pathway enrichment in a convenient and efficient manner.

This package performs robust and sparse correlation matrix estimation. Robustness is achieved based on a simple robust pairwise correlation estimator, while sparsity is obtained based on thresholding. The optimal thresholding is tuned via cross-validation. See Serra, Coretto, Fratello and Tagliaferri (2018) <doi:10.1093/bioinformatics/btx642>.

Algorithms developed for binned data analysis, gene expression data analysis and measurement error models for ordinal data analysis.

Implementation of the Control Polygon Reduction and Control Net Reduction methods for finding parsimonious B-spline regression models.

An implementation of distributional random forests as introduced in Cevid & Michel & Meinshausen & Buhlmann (2020) <arXiv:2005.14458>.

This package provides functions to generate and analyze data for psychology experiments based on the General Recognition Theory.

Robust Estimation of Multivariate Location and Scatter in the Presence of Cellwise and Casewise Contamination and Missing Data.

This package provides methods for estimation and statistical inference on directional and fluctuating selection in age-structured populations.

Fractional polynomials are used to represent curvature in regression models. A key reference is Royston and Altman, 1994.

Naive discriminative learning implements learning and classification models based on the Rescorla-Wagner equations and their equilibrium equations.

The Semi Parametric Piecewise Distribution blends the Generalized Pareto Distribution for the tails with a kernel based interior.

In order to facilitate R instruction for actuaries, we have organized several sets of publicly available data of interest to non-life actuaries. In addition, we suggest a set of packages, which most practicing actuaries will use routinely. Finally, there is an R markdown skeleton for basic reserve analysis.

This package provides the tools to undertake estimation in Regression Discontinuity Designs. Both sharp and fuzzy designs are supported. Estimation is accomplished using local linear regression. A provided function will utilize Imbens-Kalyanaraman optimal bandwidth calculation. A function is also included to test the assumption of no-sorting effects.

The purpose of this package is to factor out logic and math common to Item Factor Analysis fitting, diagnostics, and analysis. It is envisioned as core support code suitable for more specialized IRT packages to build upon. Complete access to optimized C functions is made available with R_RegisterCCallable().

Fits novel models for the conditional relative risk, risk difference and odds ratio <doi:10.1080/01621459.2016.1192546>.

This package provides a collection of functions which aim to assist common computational workflow for analysis of matabolomic data..