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

Found 133 packages in 0.06 seconds

CalcThemAll.PRM — by Alexander Bezzina, 8 months ago

Calculate Pesticide Risk Metric (PRM) Values from Multiple Pesticides...Calc Them All

Contains functions which can be used to calculate Pesticide Risk Metric values in aquatic environments from concentrations of multiple pesticides with known species sensitive distributions (SSDs). Pesticides provided by this package have all be validated however if the user has their own pesticides with SSD values they can append them to the pesticide_info table to include them in estimates.

rankICC — by Shengxin Tu, a year ago

Rank Intraclass Correlation for Clustered Data

Estimates the rank intraclass correlation coefficient (ICC) for clustered continuous and ordinal data. See Tu et al. (2023) for details.

minty — by Chung-hong Chan, a day ago

Minimal Type Guesser

Port the type guesser from 'readr' (so-called 'readr' first edition parsing engine, now superseded by 'vroom').

broom — by Simon Couch, 3 months ago

Convert Statistical Objects into Tidy Tibbles

Summarizes key information about statistical objects in tidy tibbles. This makes it easy to report results, create plots and consistently work with large numbers of models at once. Broom provides three verbs that each provide different types of information about a model. tidy() summarizes information about model components such as coefficients of a regression. glance() reports information about an entire model, such as goodness of fit measures like AIC and BIC. augment() adds information about individual observations to a dataset, such as fitted values or influence measures.

mra — by Trent McDonald, 7 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.

multilevLCA — by Roberto Di Mari, 3 months 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 (2023) .

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.

EpiLPS — by Oswaldo Gressani, 10 months 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, 4 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).

bartCause — by Vincent Dorie, 4 months ago

Causal Inference using Bayesian Additive Regression Trees

Contains a variety of methods to generate typical causal inference estimates using Bayesian Additive Regression Trees (BART) as the underlying regression model (Hill (2012) ).