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

Found 141 packages in 0.02 seconds

CalcThemAll.PRM — by Alexander Bezzina, a year 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.

hyperSpec — by Claudia Beleites, a year ago

Work with Hyperspectral Data, i.e. Spectra + Meta Information (Spatial, Time, Concentration, ...)

Comfortable ways to work with hyperspectral data sets. I.e. spatially or time-resolved spectra, or spectra with any other kind of information associated with each of the spectra. The spectra can be data as obtained in XRF, UV/VIS, Fluorescence, AES, NIR, IR, Raman, NMR, MS, etc. More generally, any data that is recorded over a discretized variable, e.g. absorbance = f(wavelength), stored as a vector of absorbance values for discrete wavelengths is suitable.

BaseSet — by LluĂ­s Revilla Sancho, 7 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.

minty — by Chung-hong Chan, 8 months ago

Minimal Type Guesser

Port the type guesser from 'readr' (so-called 'readr' first edition parsing engine, now superseded by 'vroom').

multilevLCA — by Roberto Di Mari, 7 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) .

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.

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.

RcppRedis — by Dirk Eddelbuettel, 3 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, 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).