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

Found 124 packages in 0.01 seconds

gwfa — by Francois Semecurbe, 2 years ago

Geographically Weighted Fractal Analysis

Performs Geographically Weighted Fractal Analysis (GWFA) to calculate the local fractal dimension of a set of points. GWFA mixes the Sandbox multifractal algorithm and the Geographically Weighted Regression. Unlike fractal box-counting algorithm, the sandbox algorithm avoids border effects because the boxes are adjusted on the set of points. The Geographically Weighted approach consists in applying a kernel that describes the way the neighbourhood of each estimated point is taken into account to estimate its fractal dimension. GWFA can be used to discriminate built patterns of a city, a region, or a whole country.

knitrProgressBar — by Robert M Flight, a year ago

Provides Progress Bars in 'knitr'

Provides a progress bar similar to 'dplyr' that can write progress out to a variety of locations, including stdout(), stderr(), or from file(). Useful when using 'knitr' or 'rmarkdown', and you still want to see progress of calculations in the terminal.

devRate — by Francois Rebaudo, 4 months ago

Quantify the Relationship Between Development Rate and Temperature in Ectotherms

A set of functions to quantify the relationship between development rate and temperature and to build phenological models. The package comprises a set of models and estimated parameters borrowed from a literature review in ectotherms. The methods and literature review are described in Rebaudo et al. (2018) and Rebaudo and Rabhi (2018) . An example can be found in Rebaudo et al. (2017) .

SensoMineR — by Francois Husson, a year ago

Sensory Data Analysis

Statistical Methods to Analyse Sensory Data. SensoMineR: A package for sensory data analysis. S. Le and F. Husson (2008) .

RcmdrPlugin.FactoMineR — by Francois Husson, 3 years ago

Graphical User Interface for FactoMineR

Rcmdr Plugin for the 'FactoMineR' package.

manipulateWidget — by Jalal-Edine ZAWAM, 7 months ago

Add Even More Interactivity to Interactive Charts

Like package 'manipulate' does for static graphics, this package helps to easily add controls like sliders, pickers, checkboxes, etc. that can be used to modify the input data or the parameters of an interactive chart created with package 'htmlwidgets'.

simcausal — by Oleg Sofrygin, 17 days ago

Simulating Longitudinal Data with Causal Inference Applications

A flexible tool for simulating complex longitudinal data using structural equations, with emphasis on problems in causal inference. Specify interventions and simulate from intervened data generating distributions. Define and evaluate treatment-specific means, the average treatment effects and coefficients from working marginal structural models. User interface designed to facilitate the conduct of transparent and reproducible simulation studies, and allows concise expression of complex functional dependencies for a large number of time-varying nodes. See the package vignette for more information, documentation and examples.

disparityfilter — by Alessandro Bessi, 3 years ago

Disparity Filter Algorithm for Weighted Networks

The disparity filter algorithm is a network reduction technique to identify the 'backbone' structure of a weighted network without destroying its multi-scale nature. The algorithm is documented in M. Angeles Serrano, Marian Boguna and Alessandro Vespignani in "Extracting the multiscale backbone of complex weighted networks", Proceedings of the National Academy of Sciences 106 (16), 2009. This implementation of the algorithm supports both directed and undirected networks.

sars — by Thomas J. Matthews, 5 months ago

Fit and Compare Species-Area Relationship Models Using Multimodel Inference

Implements the basic elements of the multi-model inference paradigm for up to twenty species-area relationship models (SAR), using simple R list-objects and functions, as in Triantis et al. 2012 . The package is scalable and users can easily create their own model and data objects. Additional SAR related functions are provided.

mvst — by Antonio Parisi, 6 months ago

Bayesian Inference for the Multivariate Skew-t Model

Estimates the multivariate skew-t and nested models, as described in the articles Liseo, B., Parisi, A. (2013). Bayesian inference for the multivariate skew-normal model: a population Monte Carlo approach. Comput. Statist. Data Anal. and in Parisi, A., Liseo, B. (2017). Objective Bayesian analysis for the multivariate skew-t model. Statistical Methods & Applications .