Test for independence of two random vectors, learn and report the dependency structure. For more information, see Gorsky, Shai and Li Ma, Multiscale Fisher's Independence Test for Multivariate Dependence, Biometrika, accepted, January 2022.
Fits Semiparametric Promotion Time Cure Models, taking into account (using a corrected score approach or the SIMEX algorithm) or not the measurement error in the covariates, using a backfitting approach to maximize the likelihood.
This package provides a Shiny application to estimate the sample size required for a metabolomic experiment to achieve a desired statistical power. Estimation is possible with or without available data from a pilot study.
This package provides functions for simulating, estimating and forecasting stationary Vector Autoregressive (VAR) models for multiple subject data using the penalized multi-VAR framework in Fisher, Kim and Pipiras (2020) <arXiv:2007.05052>
.
Construct and evaluate directed tree structures that model the process of occurrence of genetic alterations during carcinogenesis as described in Szabo, A. and Boucher, K (2002) <doi:10.1016/S0025-5564(02)00086-X>.
This extension of the poems pattern-oriented modeling (POM) framework provides a collection of modules and functions customized for paleontological time-scales, and optimized for single-generation transitions and large populations, across multiple generations.
Given a bulk transcriptomic (RNA-seq) sample of an Myeloid Leukemia patient calculates immune composition and drug resistance for different small-molecule inhibitors. Published in <https://www.nature.com/articles/s41698-024-00596-9>.
Performing Item Response Theory analysis such as parameter estimation, ability estimation, item and model fit analyse, local independence assumption, dimensionality assumption, characteristic and information curves under various models with a user friendly shiny interface.
Interface to the API for TreeBASE
<http://treebase.org> from R. TreeBASE
is a repository of user-submitted phylogenetic trees (of species, population, or genes) and the data used to create them.
This package provides a toolkit for working with TOML files in R while preserving formatting, comments, and structure. tomledit enables serialization of R objects such as lists, data.frames, numeric, logical, and date vectors.
An upgraded causal reasoning tool from Melas et al in R with updated assignments of TFs weights from PROGENy scores. Optimization parameters can be freely adjusted and multiple solutions can be obtained and aggregated.
This package provides functions for plotting heatmaps of genome-wide data across genomic intervals, such as ChIP-seq
signals at peaks or across promoters. Many functions are also provided for investigating sequence features.
Statistical tools for building random mutagenesis libraries for prokaryotes. The package has functions for handling the occupancy distribution for a multinomial and for estimating the number of essential genes in random transposon mutagenesis libraries.
This crate implements borsh
, the binary object representation serializer for hashing. It is meant to be used in security-critical projects as it prioritizes consistency, safety, speed, and comes with a strict specification.
This crate implements borsh
, the binary object representation serializer for hashing. It is meant to be used in security-critical projects as it prioritizes consistency, safety, speed, and comes with a strict specification.
This package performs robust estimation and inference when using covariate adjustment and/or covariate-adaptive randomization in randomized clinical trials. Ting Ye, Jun Shao, Yanyao Yi, Qinyuan Zhao (2023) <doi:10.1080/01621459.2022.2049278>. Ting Ye, Marlena Bannick, Yanyao Yi, Jun Shao (2023) <doi:10.1080/24754269.2023.2205802>. Ting Ye, Jun Shao, Yanyao Yi (2023) <doi:10.1093/biomet/asad045>. Marlena Bannick, Jun Shao, Jingyi Liu, Yu Du, Yanyao Yi, Ting Ye (2024) <doi:10.48550/arXiv.2306.10213>
.
Robust mixture discriminant analysis (RMDA), proposed in Bouveyron & Girard, 2009 <doi:10.1016/j.patcog.2009.03.027>, allows to build a robust supervised classifier from learning data with label noise. The idea of the proposed method is to confront an unsupervised modeling of the data with the supervised information carried by the labels of the learning data in order to detect inconsistencies. The method is able afterward to build a robust classifier taking into account the detected inconsistencies into the labels.
This package provides Parse and inspect Rust literals (i.e. tokens in the Rust programming language representing fixed values). Particularly useful for proc macros, but can also be used outside of a proc-macro context.
This package provides tools for downloading and extracting data from the Copernicus "Agrometeorological indicators from 1979 to present derived from reanalysis" <https://cds.climate.copernicus.eu/cdsapp#!/dataset/sis-agrometeorological-indicators?tab=overview> (AgERA5
).
API to the database of CRAN package downloads from the RStudio CRAN mirror'. The database itself is at <http://cranlogs.r-pkg.org>, see <https://github.com/r-hub/cranlogs.app> for the raw API'.
This package provides tools for the fitting and cross validation of exact conditional logistic regression models with lasso and elastic net penalties. Uses cyclic coordinate descent and warm starts to compute the entire path efficiently.
Resampling is a standard step in particle filtering and in sequential Monte Carlo. This package implements the chopthin resampler, which keeps a bound on the ratio between the largest and the smallest weights after resampling.
Evaluates the empirical characteristic function of univariate and multivariate samples. This package uses RcppArmadillo
for fast evaluation. It is also possible to export the code to be used in other packages at C++ level.
Allows get address and port of the free proxy server, from one of two services <http://gimmeproxy.com/> or <https://getproxylist.com/>. And it's easy to redirect your Internet connection through a proxy server.