Semi-Parametric Shape-Restricted Fixed/Mixed Effect(s) Regression Spline

Select the most suitable shape to describe the relationship between the exposure and the outcome among increasing, decreasing, convex, and concave shapes (Yin et al. (2021) ); estimate the direct and indirect effects with prior knowledge on the relationship between the mediator and the outcome with binary exposure (Yin et al. (2024) ); estimate the direct and indirect effects using linear regression-based approach (VanderWeele (2015, ISBN:9780199325870)).

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.

R to Symbolic Data Analysis

Symbolic Data Analysis (SDA) was proposed by professor Edwin Diday in 1987, the main purpose of SDA is to substitute the set of rows (cases) in the data table for a concept (second order statistical unit). This package implements, to the symbolic case, certain techniques of automatic classification, as well as some linear models.

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.

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).

'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.

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) .

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) .

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.

Allocate Samples Among Strata

Functions for the design process of survey sampling, with specific tools for multi-wave and multi-phase designs. Perform optimum allocation using Neyman (1934) or Wright (2012) allocation, split strata based on quantiles or values of known variables, randomly select samples from strata, allocate sampling waves iteratively, and organize a complex survey design. Also includes a Shiny application for observing the effects of different strata splits. A paper on this package was published in the Journal of Statistical Software .