Found 1090 packages in 0.03 seconds
Community Ecology Package
Ordination methods, diversity analysis and other functions for community and vegetation ecologists.
The R Package Ada for Stochastic Boosting
Performs discrete, real, and gentle boost under both exponential and logistic loss on a given data set. The package ada provides a straightforward, well-documented, and broad boosting routine for classification, ideally suited for small to moderate-sized data sets.
Efficient Plotting of Large-Sized Data
A tool to plot data with a large sample size using 'shiny' and 'plotly'. Relatively small samples are obtained from the original data using a specific algorithm. The samples are updated according to a user-defined x range. Jonas Van Der Donckt, Jeroen Van Der Donckt, Emiel Deprost (2022) < https://github.com/predict-idlab/plotly-resampler>.
Easily Work with 'Bootstrap' Icons
Easily use 'Bootstrap' icons inside 'Shiny' apps and 'R Markdown' documents. More generally, icons can be inserted in any 'htmltools' document through inline 'SVG'.
Functions for Optimal Matching
Distance based bipartite matching using minimum cost flow, oriented
to matching of treatment and control groups in observational studies ('Hansen'
and 'Klopfer' 2006
Network Meta-Analysis Using Bayesian Methods
Network meta-analyses (mixed treatment comparisons) in the Bayesian
framework using JAGS. Includes methods to assess heterogeneity and
inconsistency, and a number of standard visualizations.
van Valkenhoef et al. (2012)
Analyzing Dendrometer Data
Various functions to import, verify, process and plot
high-resolution dendrometer data using daily and stem-cycle approaches
as described in Deslauriers et al, 2007
Empirical Transition Matrix
The etm (empirical transition matrix) package permits to estimate the matrix of transition probabilities for any time-inhomogeneous multi-state model with finite state space using the Aalen-Johansen estimator. Functions for data preparation and for displaying are also included (Allignol et al., 2011
Data Table Back-End for 'dplyr'
Provides a data.table backend for 'dplyr'. The goal of 'dtplyr' is to allow you to write 'dplyr' code that is automatically translated to the equivalent, but usually much faster, data.table code.
Bayesian Latent Variable Analysis
Fit a variety of Bayesian latent variable models, including confirmatory
factor analysis, structural equation models, and latent growth curve models. References: Merkle & Rosseel (2018)