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

Found 143 packages in 0.01 seconds

minty — by Chung-hong Chan, a year ago

Minimal Type Guesser

Port the type guesser from 'readr' (so-called 'readr' first edition parsing engine, now superseded by 'vroom').

BaseSet — by LluĂ­s Revilla Sancho, 10 months ago

Working with Sets the Tidy Way

Implements a class and methods to work with sets, doing intersection, union, complementary sets, power sets, cartesian product and other set operations in a "tidy" way. These set operations are available for both classical sets and fuzzy sets. Import sets from several formats or from other several data structures.

multilevLCA — by Roberto Di Mari, a month ago

Estimates and Plots Single-Level and Multilevel Latent Class Models

Efficiently estimates single- and multilevel latent class models with covariates, allowing for output visualization in all specifications. For more technical details, see Lyrvall et al. (2025) .

ropercenter — by Frederick Solt, 2 years ago

Reproducible Data Retrieval from the Roper Center Data Archive

Reproducible, programmatic retrieval of datasets from the Roper Center data archive. The Roper Center for Public Opinion Research < https://ropercenter.cornell.edu> maintains the largest archive of public opinion data in existence, but researchers using these datasets are caught in a bind. The Center's terms and conditions bar redistribution of downloaded datasets, but to ensure that one's work can be reproduced, assessed, and built upon by others, one must provide access to the raw data one employed. The `ropercenter` package cuts this knot by providing registered users with programmatic, reproducible access to Roper Center datasets from within R.

mra — by Trent McDonald, 8 years ago

Mark-Recapture Analysis

Accomplishes mark-recapture analysis with covariates. Models available include the Cormack-Jolly-Seber open population (Cormack (1972) ; Jolly (1965) ; Seber (1965) ) and Huggin's (1989) closed population. Link functions include logit, sine, and hazard. Model selection, model averaging, plot, and simulation routines included. Open population size by the Horvitz-Thompson (1959) estimator.

RcppRedis — by Dirk Eddelbuettel, 6 months ago

'Rcpp' Bindings for 'Redis' using the 'hiredis' Library

Connection to the 'Redis' (or 'Valkey') key/value store using the C-language client library 'hiredis' (included as a fallback) with 'MsgPack' encoding provided via 'RcppMsgPack' headers. It now also includes the pub/sub functions from the 'rredis' package.

EpiLPS — by Oswaldo Gressani, 2 years ago

A Fast and Flexible Bayesian Tool for Estimating Epidemiological Parameters

Estimation of epidemiological parameters with Laplacian-P-splines following the methodology of Gressani et al. (2022) .

rDppDiversity — by Sining Ng, 5 years ago

Subset Searching Algorithm Using DPP Greedy MAP

Given item set, item representation vector, and item ratings, find a subset with better relevance-diversity trade-off. Also provide machine learning algorithm to learn item representations maximizing log likelihood under DPP assumption. References: [1]Laming Chen, Guoxin Zhang, and Hanning Zhou(2017)< https://lsrs2017.files.wordpress.com/2017/08/lsrs_2017_lamingchen.pdf> [2]Laming Chen, Guoxin Zhang, and Hanning Zhou(2018)< https://papers.nips.cc/paper/2018/file/dbbf603ff0e99629dda5d75b6f75f966-Paper.pdf> [3]Wilhelm, Mark & Ramanathan, Ajith & Bonomo, Alexander & Jain, Sagar & Chi, Ed & Gillenwater, Jennifer(2018).

EGRET — by Laura DeCicco, 7 months ago

Exploration and Graphics for RivEr Trends

Statistics and graphics for streamflow history, water quality trends, and the statistical modeling algorithm: Weighted Regressions on Time, Discharge, and Season (WRTDS).

prcr — by Joshua M Rosenberg, 6 years ago

Person-Centered Analysis

Provides an easy-to-use yet adaptable set of tools to conduct person-center analysis using a two-step clustering procedure. As described in Bergman and El-Khouri (1999) , hierarchical clustering is performed to determine the initial partition for the subsequent k-means clustering procedure.