R implementation of Maximum Likelihood Principal Component Analysis The main idea of this package is to have an alternative way of PCA for subspace modeling that considers measurement errors. More details can be found in Peter D. Wentzell (2009) <doi:10.1016/B978-0-444-64165-6.03029-9>.
This package provides the robust gamma rank correlation coefficient as introduced by Bodenhofer, Krone, and Klawonn (2013) <DOI:10.1016/j.ins.2012.11.026> along with a permutation-based rank correlation test. The rank correlation coefficient and the test are explicitly designed for dealing with noisy numerical data.
The handling of an API key (misnomer for password) for protected data can be difficult. This package provides secure convenience functions for entering / handling API keys and pulling data directly into memory. By default it will load from REDCap instances, but other sources are injectable via inversion of control.
This package provides a safe Rust wrapper for ONNX Runtime 1.18 - Optimize and accelerate machine learning inference & training.
Record your test suite's HTTP interactions and replay them during future test runs for fast, deterministic, accurate tests.
Dynamic regression for time series using Extreme Gradient Boosting with hyper-parameter tuning via Bayesian Optimization or Random Search.
Collection of functions, data sets and code examples for evaluations of field trials with the objective of equivalence assessment.
The main functions carry out Gibbs sampler routines for nonparametric and semiparametric Bayesian models for random effects meta-analysis.
Visualizes results of item analysis such as item difficulty, item discrimination, and coefficient alpha for ease of result communication.
Variance estimation on indicators of income concentration and poverty using complex sample survey designs. Wrapper around the survey package.
Encrypts and decrypts strings using either the Caesar cipher or a pseudorandom number generation (using set.seed()) method.
This package provides a system for the management, assessment, and psychometric analysis of data from educational and psychological tests.
Basic routines used in scientific coding, such as timing routines, vector/array handing functions and I/O support routines.
Example datasets from the book "An Introduction to Generalised Linear Models" (Year: 2018, ISBN:9781138741515) by Dobson and Barnett.
This package provides a dibble that implements data cubes (derived from dimensional tibble'), and allows broadcasting by dimensional names.
Utilities for building certain kinds of common matrices and models in the extended structural equation modeling package, OpenMx'.
Data sets and scripts used in the book Generalized Additive Models: An Introduction with R', Wood (2006,2017) CRC.
Streamlines downloading and cleaning biodiversity data from Integrated Digitized Biocollections (iDigBio) and the Global Biodiversity Information Facility (GBIF).
An implementation of Gini-based weighting approaches in constructing composite indicators, providing functionalities for normalization, aggregation, and ranking comparison.
Fits a linear excess relative risk model by maximum likelihood, possibly including several variables and allowing for lagged exposures.
Fits sex-specific life-history models for fish and other taxa where some of the individuals have unknown sex.
Define, manipulate and plot meshes on simplices, spheres, balls, rectangles and tubes. Directional and other multivariate histograms are provided.
This package provides functions for creating designs for mixture experiments, making ternary contour plots, and making mixture effect plots.
We fit inverse probability weighting estimator and the augmented inverse probability weighting for non-monotone missing at random data.