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

Found 110 packages in 0.17 seconds

speechbr — by Douglas Cardoso, 4 years ago

Access the Speechs and Speaker's Informations of House of Representatives of Brazil

Scrap speech text and speaker informations of speeches of House of Representatives of Brazil, and transform in a cleaned tibble.

micEcon — by Arne Henningsen, 2 months ago

Microeconomic Analysis and Modelling

Various tools for microeconomic analysis and microeconomic modelling, e.g. estimating quadratic, Cobb-Douglas and Translog functions, calculating partial derivatives and elasticities of these functions, and calculating Hessian matrices, checking curvature and preparing restrictions for imposing monotonicity of Translog functions.

retrosheet — by Colin Douglas, 2 years ago

Import Professional Baseball Data from 'Retrosheet'

A collection of tools to import and structure the (currently) single-season event, game-log, roster, and schedule data available from < https://www.retrosheet.org>. In particular, the event (a.k.a. play-by-play) files can be especially difficult to parse. This package does the parsing on those files, returning the requested data in the most practical R structure to use for sabermetric or other analyses.

RDP — by Robert Dahl Jacobsen, 2 years ago

The Ramer-Douglas-Peucker Algorithm

Pretty fast implementation of the Ramer-Douglas-Peucker algorithm for reducing the number of points on a 2D curve. Urs Ramer (1972), "An iterative procedure for the polygonal approximation of plane curves" . David H. Douglas and Thomas K. Peucker (1973), "Algorithms for the Reduction of the Number of Points Required to Represent a Digitized Line or its Caricature" .

cond — by Alessandra R. Brazzale, 6 months ago

Approximate Conditional Inference for Logistic and Loglinear Models

Implements higher order likelihood-based inference for logistic and loglinear models.

statpsych — by Douglas G. Bonett, 6 months ago

Statistical Methods for Psychologists

Implements confidence interval and sample size methods that are especially useful in psychological research. The methods can be applied in 1-group, 2-group, paired-samples, and multiple-group designs and to a variety of parameters including means, medians, proportions, slopes, standardized mean differences, standardized linear contrasts of means, plus several measures of correlation and association. Confidence interval and sample size functions are given for single parameters as well as differences, ratios, and linear contrasts of parameters. The sample size functions can be used to approximate the sample size needed to estimate a parameter or function of parameters with desired confidence interval precision or to perform a variety of hypothesis tests (directional two-sided, equivalence, superiority, noninferiority) with desired power. For details see: Statistical Methods for Psychologists, Volumes 1 – 4, < https://dgbonett.sites.ucsc.edu/>.

vcmeta — by Douglas G. Bonett, 3 months ago

Varying Coefficient Meta-Analysis

Implements functions for varying coefficient meta-analysis methods. These methods do not assume effect size homogeneity. Subgroup effect size comparisons, general linear effect size contrasts, and linear models of effect sizes based on varying coefficient methods can be used to describe effect size heterogeneity. Varying coefficient meta-analysis methods do not require the unrealistic assumptions of the traditional fixed-effect and random-effects meta-analysis methods. For details see: Statistical Methods for Psychologists, Volume 5, < https://dgbonett.sites.ucsc.edu/>.

rwicc — by Douglas Morrison, 4 years ago

Regression with Interval-Censored Covariates

Provides functions to simulate and analyze data for a regression model with an interval censored covariate, as described in Morrison et al. (2021) .

mlmRev — by Steve Walker, 6 years ago

Examples from Multilevel Modelling Software Review

Data and examples from a multilevel modelling software review as well as other well-known data sets from the multilevel modelling literature.

blme — by Vincent Dorie, a year ago

Bayesian Linear Mixed-Effects Models

Maximum a posteriori estimation for linear and generalized linear mixed-effects models in a Bayesian setting, implementing the methods of Chung, et al. (2013) . Extends package 'lme4' (Bates, Maechler, Bolker, and Walker (2015) ).