Found 121 packages in 0.03 seconds
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.
Approximate Conditional Inference for Logistic and Loglinear Models
Implements higher order likelihood-based inference for logistic and loglinear models.
Downloading, Reading and Analyzing PNADC Microdata
Provides tools for downloading, reading and analyzing the Continuous National Household Sample Survey - PNADC, a household survey from Brazilian Institute of Geography and Statistics - IBGE. The data must be downloaded from the official website < https://www.ibge.gov.br/>. Further analysis must be made using package 'survey'.
Varying Coefficient Meta-Analysis
Implements functions for varying coefficient meta-analysis methods. These methods do not assume effect size homogeneity. Subgroup effect size comparisons, general linear effect size contrasts, and linear models of effect sizes based on varying coefficient methods can be used to describe effect size heterogeneity. Varying coefficient meta-analysis methods do not require the unrealistic assumptions of the traditional fixed-effect and random-effects meta-analysis methods. For details see: Statistical Methods for Psychologists, Volume 5, < https://dgbonett.sites.ucsc.edu/>.
Consistent Anonymisation Across Datasets
A simple function that anonymises a list of variables in a consistent way: anonymised factors are not recycled and the same original levels receive the same anonymised factor even if located in different datasets.
Import Professional Baseball Data from 'Retrosheet'
A collection of tools to import and structure the (currently) single-season event, game-log, roster, and schedule data available from < https://www.retrosheet.org>. In particular, the event (a.k.a. play-by-play) files can be especially difficult to parse. This package does the parsing on those files, returning the requested data in the most practical R structure to use for sabermetric or other analyses.
Regression with Interval-Censored Covariates
Provides functions to simulate and analyze data for a regression model with an interval censored covariate, as described in Morrison et al. (2021)
Read and Process 'Pamguard' Binary Data
Functions for easily reading and processing binary data files created by 'Pamguard' (< https://www.pamguard.org/>). All functions for directly reading the binary data files are based on 'MATLAB' code written by Michael Oswald.
A Distributed Worker Launcher Framework
In computationally demanding analysis projects,
statisticians and data scientists asynchronously
deploy long-running tasks to distributed systems,
ranging from traditional clusters to cloud services.
The 'NNG'-powered 'mirai' R package by Gao (2023)
Multi-Resolution Kriging Based on Markov Random Fields
Methods for the interpolation of large spatial datasets. This package uses a basis function approach that provides a surface fitting method that can approximate standard spatial data models. Using a large number of basis functions allows for estimates that can come close to interpolating the observations (a spatial model with a small nugget variance.) Moreover, the covariance model for this method can approximate the Matern covariance family but also allows for a multi-resolution model and supports efficient computation of the profile likelihood for estimating covariance parameters. This is accomplished through compactly supported basis functions and a Markov random field model for the basis coefficients. These features lead to sparse matrices for the computations and this package makes of the R spam package for sparse linear algebra. An extension of this version over previous ones ( < 5.4 ) is the support for different geometries besides a rectangular domain. The Markov random field approach combined with a basis function representation makes the implementation of different geometries simple where only a few specific R functions need to be added with most of the computation and evaluation done by generic routines that have been tuned to be efficient. One benefit of this package's model/approach is the facility to do unconditional and conditional simulation of the field for large numbers of arbitrary points. There is also the flexibility for estimating non-stationary covariances and also the case when the observations are a linear combination (e.g. an integral) of the spatial process. Included are generic methods for prediction, standard errors for prediction, plotting of the estimated surface and conditional and unconditional simulation. See the 'LatticeKrigRPackage' GitHub repository for a vignette of this package. Development of this package was supported in part by the National Science Foundation Grant 1417857 and the National Center for Atmospheric Research.