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

Found 133 packages in 0.01 seconds

MAMSE — by Jean-Francois Plante, 2 years ago

Calculation of Minimum Averaged Mean Squared Error (MAMSE) Weights

Calculates the nonparametric adaptive MAMSE weights for univariate, right-censored or multivariate data. The MAMSE weights can be used in a weighted likelihood or to define a mixture of empirical distribution functions. The package includes functions for the MAMSE weighted Kaplan-Meier estimate and for MAMSE weighted ROC curves.

abc.data — by Blum Michael, 4 years ago

Data Only: Tools for Approximate Bayesian Computation (ABC)

Contains data which are used by functions of the 'abc' package.

ClinReport — by Jean-Francois Collin, 3 months ago

Statistical Reporting in Clinical Trials

It enables to create easily formatted statistical tables in 'Microsoft Word' documents in pretty formats according to 'clinical standards'. It can be used also outside the scope of clinical trials, for any statistical reporting in 'Word'. Descriptive tables for quantitative statistics (mean, median, max etc..) and/or qualitative statistics (frequencies and percentages) are available and formatted tables of Least Square Means of Linear Models, Linear Mixed Models and Generalized Linear Mixed Models coming from emmeans() function are also available. The package works with 'officer' and 'flextable' packages to export the outputs into 'Microsoft Word' documents.

RCSF — by Jean-Romain Roussel, 7 months ago

Airborne LiDAR Filtering Method Based on Cloth Simulation

Cloth Simulation Filter (CSF) is an airborne LiDAR (Light Detection and Ranging) ground points filtering algorithm which is based on cloth simulation. It tries to simulate the interactions between the cloth nodes and the corresponding LiDAR points, the locations of the cloth nodes can be determined to generate an approximation of the ground surface.

leaflet.minicharts — by Jalal-Edine ZAWAM, a year ago

Mini Charts for Interactive Maps

Add and modify small charts on an interactive map created with package 'leaflet'. These charts can be used to represent at same time multiple variables on a single map.

Factoshiny — by Francois Husson, 7 months ago

Perform Factorial Analysis from 'FactoMineR' with a Shiny Application

Perform factorial analysis with a menu and draw graphs interactively thanks to 'FactoMineR' and a Shiny application.

inpdfr — by Rebaudo Francois, 8 months ago

Analyse Text Documents Using Ecological Tools

A set of functions to analyse and compare texts, using classical text mining functions, as well as those from theoretical ecology.

gwfa — by Francois Semecurbe, 3 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.

devRate — by Francois Rebaudo, 23 days 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) .

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.