Examples: visualization, C++, networks, data cleaning, html widgets, ropensci.

Found 137 packages in 0.11 seconds

gumbel — by Christophe Dutang, a month ago

The Gumbel-Hougaard Copula

Provides probability functions (cumulative distribution and density functions), simulation function (Gumbel copula multivariate simulation) and estimation functions (Maximum Likelihood Estimation, Inference For Margins, Moment Based Estimation and Canonical Maximum Likelihood).

nexus — by Nicolas Frerebeau, 8 months ago

Sourcing Archaeological Materials by Chemical Composition

Exploration and analysis of compositional data in the framework of Aitchison (1986, ISBN: 978-94-010-8324-9). This package provides tools for chemical fingerprinting and source tracking of ancient materials.

pathviewr — by Vikram B. Baliga, 8 months ago

Wrangle, Analyze, and Visualize Animal Movement Data

Tools to import, clean, and visualize movement data, particularly from motion capture systems such as Optitrack's 'Motive', the Straw Lab's 'Flydra', or from other sources. We provide functions to remove artifacts, standardize tunnel position and tunnel axes, select a region of interest, isolate specific trajectories, fill gaps in trajectory data, and calculate 3D and per-axis velocity. For experiments of visual guidance, we also provide functions that use subject position to estimate perception of visual stimuli.

validann — by Greer B. Humphrey, 9 years ago

Validation Tools for Artificial Neural Networks

Methods and tools for analysing and validating the outputs and modelled functions of artificial neural networks (ANNs) in terms of predictive, replicative and structural validity. Also provides a method for fitting feed-forward ANNs with a single hidden layer.

SBICgraph — by Quang Nguyen, 5 years ago

Structural Bayesian Information Criterion for Graphical Models

This is the implementation of the novel structural Bayesian information criterion by Zhou, 2020 (under review). In this method, the prior structure is modeled and incorporated into the Bayesian information criterion framework. Additionally, we also provide the implementation of a two-step algorithm to generate the candidate model pool.

REPPlab — by Daniel Fischer, 2 years ago

R Interface to 'EPP-Lab', a Java Program for Exploratory Projection Pursuit

An R Interface to 'EPP-lab' v1.0. 'EPP-lab' is a Java program for projection pursuit using genetic algorithms written by Alain Berro and S. Larabi Marie-Sainte and is included in the package.

epitrix — by Thibaut Jombart, 6 months ago

Small Helpers and Tricks for Epidemics Analysis

A collection of small functions useful for epidemics analysis and infectious disease modelling. This includes computation of basic reproduction numbers from growth rates, generation of hashed labels to anonymize data, and fitting discretized Gamma distributions.

mixAK — by Arnošt Komárek, a year ago

Multivariate Normal Mixture Models and Mixtures of Generalized Linear Mixed Models Including Model Based Clustering

Contains a mixture of statistical methods including the MCMC methods to analyze normal mixtures. Additionally, model based clustering methods are implemented to perform classification based on (multivariate) longitudinal (or otherwise correlated) data. The basis for such clustering is a mixture of multivariate generalized linear mixed models. The package is primarily related to the publications Komárek (2009, Comp. Stat. and Data Anal.) and Komárek and Komárková (2014, J. of Stat. Soft.) . It also implements methods published in Komárek and Komárková (2013, Ann. of Appl. Stat.) , Hughes, Komárek, Bonnett, Czanner, García-Fiñana (2017, Stat. in Med.) , Jaspers, Komárek, Aerts (2018, Biom. J.) and Hughes, Komárek, Czanner, García-Fiñana (2018, Stat. Meth. in Med. Res) .

NiLeDAM — by Nathalie Vialaneix, 8 months ago

Monazite Dating for the NiLeDAM Team

Th-U-Pb electron microprobe age dating of monazite, as originally described in .

nlpred — by David Benkeser, 6 years ago

Estimators of Non-Linear Cross-Validated Risks Optimized for Small Samples

Methods for obtaining improved estimates of non-linear cross-validated risks are obtained using targeted minimum loss-based estimation, estimating equations, and one-step estimation (Benkeser, Petersen, van der Laan (2019), ). Cross-validated area under the receiver operating characteristics curve (LeDell, Petersen, van der Laan (2015), ) and other metrics are included.