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

Found 114 packages in 0.02 seconds

VIM — by Matthias Templ, 3 months ago

Visualization and Imputation of Missing Values

New tools for the visualization of missing and/or imputed values are introduced, which can be used for exploring the data and the structure of the missing and/or imputed values. Depending on this structure of the missing values, the corresponding methods may help to identify the mechanism generating the missing values and allows to explore the data including missing values. In addition, the quality of imputation can be visually explored using various univariate, bivariate, multiple and multivariate plot methods. A graphical user interface available in the separate package VIMGUI allows an easy handling of the implemented plot methods.

laeken — by Andreas Alfons, a year ago

Estimation of Indicators on Social Exclusion and Poverty

Estimation of indicators on social exclusion and poverty, as well as Pareto tail modeling for empirical income distributions.

distrEx — by Matthias Kohl, 2 years ago

Extensions of Package 'distr'

Extends package 'distr' by functionals, distances, and conditional distributions.

robCompositions — by Matthias Templ, 5 months ago

Compositional Data Analysis

Methods for analysis of compositional data including robust methods (), imputation of missing values (), methods to replace rounded zeros (, , ), count zeros (), methods to deal with essential zeros (), (robust) outlier detection for compositional data, (robust) principal component analysis for compositional data, (robust) factor analysis for compositional data, (robust) discriminant analysis for compositional data (Fisher rule), robust regression with compositional predictors, functional data analysis () and p-splines (), contingency () and compositional tables (, , ) and (robust) Anderson-Darling normality tests for compositional data as well as popular log-ratio transformations (addLR, cenLR, isomLR, and their inverse transformations). In addition, visualisation and diagnostic tools are implemented as well as high and low-level plot functions for the ternary diagram.

RandVar — by Matthias Kohl, a year ago

Implementation of Random Variables

Implements random variables by means of S4 classes and methods.

cluster — by Martin Maechler, 3 days ago

"Finding Groups in Data": Cluster Analysis Extended Rousseeuw et al.

Methods for Cluster analysis. Much extended the original from Peter Rousseeuw, Anja Struyf and Mia Hubert, based on Kaufman and Rousseeuw (1990) "Finding Groups in Data".

RUnit — by Roman Zenka, 3 years ago

R Unit Test Framework

R functions implementing a standard Unit Testing framework, with additional code inspection and report generation tools.

pROC — by Xavier Robin, 3 months ago

Display and Analyze ROC Curves

Tools for visualizing, smoothing and comparing receiver operating characteristic (ROC curves). (Partial) area under the curve (AUC) can be compared with statistical tests based on U-statistics or bootstrap. Confidence intervals can be computed for (p)AUC or ROC curves.

sdcMicro — by Matthias Templ, 3 months ago

Statistical Disclosure Control Methods for Anonymization of Data and Risk Estimation

Data from statistical agencies and other institutions are mostly confidential. This package (see also Templ, Kowarik and Meindl (2017) ) can be used for the generation of anonymized (micro)data, i.e. for the creation of public- and scientific-use files. The theoretical basis for the methods implemented can be found in Templ (2017) . Various risk estimation and anonymisation methods are included. Note that the package includes a graphical user interface (Meindl and Templ, 2019 ) that allows to use various methods of this package.

simPop — by Matthias Templ, 5 months ago

Simulation of Complex Synthetic Data Information

Tools and methods to simulate populations for surveys based on auxiliary data. The tools include model-based methods, calibration and combinatorial optimization algorithms, see Templ, Kowarik and Meindl (2017) ) and Templ (2017) . The package was developed with support of the International Household Survey Network, DFID Trust Fund TF011722 and funds from the World bank.