This package contains data files to accompany Smithson & Merkle (2013), Generalized Linear Models for Categorical and Continuous Limited Dependent Variables.

This package provides Apache Spark style window aggregation for R dataframes and remote dbplyr tables via mutate in dplyr flavour.

Helps systematize and ease the process of building unit tests with the testthat package by providing tools for generating expectations.

This package implements methods described by the paper Robins and Tsiatis (1991) <DOI:10.1080/03610929108830654>. These use g-estimation to estimate the causal effect of a treatment in a two-armed randomised control trial where non-compliance exists and is measured, under an assumption of an accelerated failure time model and no unmeasured confounders.

This package implements Bayesian inference for the conditional genetic stock identification model. It allows inference of mixed fisheries and also simulation of mixtures to predict accuracy. A full description of the underlying methods is available in a recently published article in the Canadian Journal of Fisheries and Aquatic Sciences: <doi:10.1139/cjfas-2018-0016>.

Toolbox for chemometrics analysis of bidimensional gas chromatography data. This package import data for common scientific data format (NetCDF) and fold it to 2D chromatogram. Then, it can perform preprocessing and multivariate analysis. In the preprocessing algorithms, baseline correction, smoothing, and peak alignment are available. While in multivariate analysis, multiway principal component analysis is incorporated.

We generate random variables following general Marchenko-Pastur distribution and Tracy-Widom distribution. We compute limits and distributions of eigenvalues and generalized components of spiked covariance matrices. We give estimation of all population eigenvalues of spiked covariance matrix model. We give tests of population covariance matrix. We also perform matrix denoising for signal-plus-noise model.

This package provides functionality to group lines that form naturally continuous lines in a spatial network. The algorithm implemented is based on the Continuity in Street Networks (COINS) method from Tripathy et al. (2021) <doi:10.1177/2399808320967680>, which identifies continuous "strokes" in the network as the line strings that maximize the angles between consecutive segments.

This package provides empirical likelihood ratio tests for means/quantiles/hazards from possibly censored and/or truncated data. It also does regression.

This package provides an R wrapper to the Python natural language processing (NLP) library spaCy, from http://spacy.io.

This package provides an R interface to the jExcel library to create web-based interactive tables and spreadsheets compatible with spreadsheet software.

This package provides an R tool for estimating and partitioning R2 in generalized linear mixed models (GLMMs) based on predictor variance.

Contains functions for data preparation, descriptives, hazard estimation and prediction with Aalen-Johansen or simulation in competing risks and multi-state models.

This package provides a series of additional Tcl commands and Tk widgets with style and various functions to supplement the tcltk package

Models and methods for fitting linear models to gene expression data, together with tools for computing and using various regression diagnostics.

This package provides a collection of models for bivariate alternating recurrent event data analysis. Includes non-parametric and semi-parametric methods.

Bindings to the blowfish password hashing algorithm <https://www.openbsd.org/papers/bcrypt-paper.pdf> derived from the OpenBSD implementation.

This package provides a set of functions for doing analysis of A/B split test data and web metrics in general.

Calculate the operating characteristics of the Bayesian Optimal Interval with Back Filling Design for dose escalation in early-phase oncology trials.

Bayesian Nonparametric sensitivity analysis of multiple testing procedures for p values with arbitrary dependencies, based on the Dirichlet process prior distribution.

This package provides methods for the import/export and automated analysis of concept maps and concept landscapes (sets of concept maps).

This package provides a collection of functions to preprocess data and organize them in a format amenable to use by chevron.

This package creates simple to highly customized tables for a wide selection of descriptive statistics, with or without weighting the data.

Efficient estimation of maximum likelihood models with multiple fixed-effects. Standard-errors can easily and flexibly be clustered and estimations exported.