Geographic, use, and property related data on airports.
Bayesian Latent Class Analysis using several different methods.
Turn numeric,data.frame,matrix into fraction form.
Generate mock data in R using YAML configuration.
Magic functions to obtain results from for loops.
Create random passwords of letters, numbers and punctuation.
Produce quantile-based box-and-whisker plot(s).
Turn complex JSON data into tidy data frames.
Duplication rate quality control for RNA-Seq datasets.
data from a yeast ChIP-chip experiment.
This package implements methods for testing multiple mediators.
Experimental organization of combined expression and CGH data.
Stepwise normalization functions for cDNA microarray data.
This package provides utility functions for manipulating BAM files.
This package provides functions for drawing and calibrating samples.
This package provides useful tools for structural equation modeling.
RUTILS is a syntactic utilities package for Common Lisp.
This Common Lisp package provides a regular expression engine.
RESTAS is a Common Lisp web application framework.
Routines for developing models that describe reaction and advective-diffusive transport in one, two or three dimensions. Includes transport routines in porous media, in estuaries, and in bodies with variable shape.
Robust estimators for generalized ratio model (Wada, Sakashita and Tsubaki, 2021)<doi:10.17713/ajs.v50i1.994> and linear regression model by the IRLS(iterative reweighted least squares) algorithm are contained.
Stan implementation of the Theory of Visual Attention (TVA; Bundesen, 1990; <doi:10.1037/0033-295X.97.4.523>) and numerous convenience functions for generating, compiling, fitting, and analyzing TVA models.
Rouge is a code highlighter written in Ruby. It supports more than 100 languages and outputs HTML or ANSI 256-color text. Its HTML output is compatible with stylesheets designed for pygments.
Statistical tools for the Mallows-Binomial model, the first joint statistical model for preference learning for rankings and ratings. This project was supported by the National Science Foundation under Grant No. 2019901.