Repository that contains a set of functions for bnlearn package discrete models: multi-variable prediction and evaluation metrics
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Updated
Jun 25, 2020 - R
Repository that contains a set of functions for bnlearn package discrete models: multi-variable prediction and evaluation metrics
R package for displaying multivariate data through a quasi-Chernoff visualization
A generator for synthetic, multivariate & heterogeneous datasteams with probabilistically repeating patterns.
R package implementing the multivariate (multi-univariate) extension of the benchmarks used for the M
This repository includes custom scripts for data analysis for the paper: The latent structure of emerging cognitive abilities: an infant twin study. Bussu G., Taylor M., Tammimies K., Ronald A., Falck-Ytter T. Focusing on the investigation of the etiological structure underlying emerging cognitive and motor abilities early in infancy.
This is an Excel file that generates a multivariate plot with Numeric data. R code for the implementation is also provided. VBA script is available in Excel file
Data and code to reproduce analyses from "Bayesian multivariate meta-regression : a tutorial"
R-based project to analyze lyrics entropy by genre and decade. A hand-engineered feature "words-per-unique-word" is introduced and deeply studied. Spotify and Genius APIs are used
This link shows the codes in the paper: Robust Two-Layer Partition Clustering of Sparse Multivariate Functional Data. Please read readme.file first.
Functions for Wishart distributions, including sampling from the inverse Wishart and sampling from the Cholesky factorization of a Wishart.
An R package for Subset Multivariate Optimal Partitioning (SMOP), a multivariate changepoint detection algorithm.
This repository contains R code that explains graphically how a few different multivariate statistical techniques work. Topics covered are distance measures, principal component analysis, permutational analysis of variance, and partial least squares regression.
Create Multivariate Autoregressive State-Space Models with the MARSS R package
Multivariate quantile function from discrete approximation of continuous probability distribution function
Supervised Component Generalised Linear Regression for mixed models
Bayesian network analysis in R
Analyses from Orians et al. 2019 https://doi.org/10.1093/aob/mcz004
Multivariate density estimation and clustering. (R package)
Usage examples for the micompr R package
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