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

Found 116 packages in 0.02 seconds

parameters — by Daniel Lüdecke, a month ago

Processing of Model Parameters

Utilities for processing the parameters of various statistical models. Beyond computing p values, CIs, and other indices for a wide variety of models (see list of supported models using the function 'insight::supported_models()'), this package implements features like bootstrapping or simulating of parameters and models, feature reduction (feature extraction and variable selection) as well as functions to describe data and variable characteristics (e.g. skewness, kurtosis, smoothness or distribution).

snapr — by Douglas Ezra Morrison, 2 months ago

Convenient Snapshot Testing Functions for Packages

Provides convenient snapshot testing functions for packages, including expect_snapshot_data() for data.frames and expect_snapshot_object() for any R object.

safuzzy — by Maciel Douglas, O., 18 days ago

Stability Analysis with Fuzzy Logic

It integrates 'fuzzy logic' into the analysis of genotype adaptability and stability. By classifying genotypes based on degrees of belonging, the package provides a detailed assessment of their behavior in different environmental groups.

causaldrf — by Douglas Galagate, 4 years ago

Estimating Causal Dose Response Functions

Functions and data to estimate causal dose response functions given continuous, ordinal, or binary treatments. A description of the methods is given in Galagate (2016) < https://drum.lib.umd.edu/handle/1903/18170>.

Rlab — by Dennis Boos, 6 months ago

Functions and Datasets Required for ST370 Class

Provides functions and datasets required for the ST 370 course at North Carolina State University.

micEcon — by Arne Henningsen, 10 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.

RDP — by Robert Dahl Jacobsen, 3 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" .

RPEIF — by Anthony Christidis, 7 months ago

Computation and Plots of Influence Functions for Risk and Performance Measures

Computes the influence functions time series of the returns for the risk and performance measures as mentioned in Chen and Martin (2018) < https://www.ssrn.com/abstract=3085672>, as well as in Zhang et al. (2019) < https://www.ssrn.com/abstract=3415903>. Also evaluates estimators influence functions at a set of parameter values and plots them to display the shapes of the influence functions.

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.

sirt — by Alexander Robitzsch, 10 months ago

Supplementary Item Response Theory Models

Supplementary functions for item response models aiming to complement existing R packages. The functionality includes among others multidimensional compensatory and noncompensatory IRT models (Reckase, 2009, ), MCMC for hierarchical IRT models and testlet models (Fox, 2010, ), NOHARM (McDonald, 1982, ), Rasch copula model (Braeken, 2011, ; Schroeders, Robitzsch & Schipolowski, 2014, ), faceted and hierarchical rater models (DeCarlo, Kim & Johnson, 2011, ), ordinal IRT model (ISOP; Scheiblechner, 1995, ), DETECT statistic (Stout, Habing, Douglas & Kim, 1996, ), local structural equation modeling (LSEM; Hildebrandt, Luedtke, Robitzsch, Sommer & Wilhelm, 2016, ).