lsasim - Functions to Facilitate the Simulation of Large Scale Assessment Data
Provides functions to simulate data from large-scale educational assessments, including background questionnaire data and cognitive item responses that adhere to a multiple-matrix sampled design. The theoretical foundation can be found on Matta, T.H., Rutkowski, L., Rutkowski, D. et al. (2018) <doi:10.1186/s40536-018-0068-8>.
Last updated 7 months ago
6.11 score 6 stars 18 scripts 671 downloadsTruncExpFam - Truncated Exponential Family
Handles truncated members from the exponential family of probability distributions. Contains functions such as rtruncnorm() and dtruncpois(), which are truncated versions of rnorm() and dpois() from the stats package that also offer richer output containing, for example, the distribution parameters. It also provides functions to retrieve the original distribution parameters from a truncated sample by maximum-likelihood estimation.
Last updated 2 months ago
truncated-distribution
4.95 score 5 scripts 381 downloadscellmigRation - Track Cells, Analyze Cell Trajectories and Compute Migration Statistics
Import TIFF images of fluorescently labeled cells, and track cell movements over time. Parallelization is supported for image processing and for fast computation of cell trajectories. In-depth analysis of cell trajectories is enabled by 15 trajectory analysis functions.
Last updated 24 days ago
cellbiologydatarepresentationdataimportbioconductor-packagecell-trackingshinytrajectory-analysis
4.60 score 4 scripts 130 downloadscontingencytables - Statistical Analysis of Contingency Tables
Provides functions to perform statistical inference of data organized in contingency tables. This package is a companion to the "Statistical Analysis of Contingency Tables" book by Fagerland et al. <ISBN 9781466588172>.
Last updated 3 months ago
contingency-table
4.50 score 3 stars 1 packages 7 scripts 435 downloadspermChacko - Chacko Test for Order-Restriction with Permutation
Implements an extension of the Chacko chi-square test for ordered vectors (Chacko, 1966, <https://www.jstor.org/stable/25051572>). Our extension brings the Chacko test to the computer age by implementing a permutation test to offer a numeric estimate of the p-value, which is particularly useful when the analytic solution is not available.
Last updated 2 months ago
4.48 score 3 scripts 178 downloadsDIscBIO - A User-Friendly Pipeline for Biomarker Discovery in Single-Cell Transcriptomics
An open, multi-algorithmic pipeline for easy, fast and efficient analysis of cellular sub-populations and the molecular signatures that characterize them. The pipeline consists of four successive steps: data pre-processing, cellular clustering with pseudo-temporal ordering, defining differential expressed genes and biomarker identification. More details on Ghannoum et. al. (2021) <doi:10.3390/ijms22031399>. This package implements extensions of the work published by Ghannoum et. al. (2019) <doi:10.1101/700989>.
Last updated 1 years ago
biomarker-discoveryjupyter-notebookscrna-seqsingle-cell-analysistranscriptomics
4.38 score 12 stars 5 scripts 236 downloadsmatlab2r - Translation Layer from MATLAB to R
Allows users familiar with MATLAB to use MATLAB-named functions in R. Several basic MATLAB functions are written in this package to mimic the behavior of their original counterparts, with more to come as this package grows.
Last updated 1 years ago
matlab
3.48 score 2 stars 1 packages 224 downloadsnutrition - Useful Functions for People on a Diet
Contains a collection of functions for performing different kinds of calculation that are of interest to someone following a diet plan. Calculators for the Basal Metabolic Rate are based on Mifflin et al. (1990) <doi:10.1093/ajcn/51.2.241> and McArdle, W. D., Katch, F. I., & Katch, V. L. (2010, ISBN:9780812109917).
Last updated 1 years ago
2.70 score 240 downloadsSparseFunClust - Sparse Functional Clustering
Provides a general framework for performing sparse functional clustering as originally described in Floriello and Vitelli (2017) <doi:10.1016/j.jmva.2016.10.008>, with the possibility of jointly handling data misalignment (see Vitelli, 2019, <doi:10.48550/arXiv.1912.00687>).
Last updated 2 years ago
2.00 score 2 scripts 128 downloads