Found 173 packages in 0.02 seconds
Open Welfare Data Brazil
Tools for collecting municipal-level data < http://www.transparencia.gov.br/swagger-ui.html> from several Brazilian governmental social programs.
Biodiversity Assessment Tools
Includes algorithms to assess alpha and beta diversity
in all their dimensions (taxonomic, phylogenetic and functional).
It allows performing a number of analyses based on species
identities/abundances, phylogenetic/functional distances, trees,
convex-hulls or kernel density n-dimensional hypervolumes
depicting species relationships.
Cardoso et al. (2015)
Core Inflation
Provides access to core inflation functions. Four different core inflation functions are provided. The well known trimmed means, exclusion and double weighing methods, alongside the new Triple Filter method introduced in Ferreira et al. (2016) < https://goo.gl/UYLhcj>.
Download, Compile and Link 'OpenBLAS' Library with R
The 'ropenblas' package (< https://prdm0.github.io/ropenblas/>) is useful for users of any 'GNU/Linux' distribution. It will be possible to download, compile and link the 'OpenBLAS' library (< https://www.openblas.net/>) with the R language, always by the same procedure, regardless of the 'GNU/Linux' distribution used. With the 'ropenblas' package it is possible to download, compile and link the latest version of the 'OpenBLAS' library even the repositories of the 'GNU/Linux' distribution used do not include the latest versions of 'OpenBLAS'. If of interest, older versions of the 'OpenBLAS' library may be considered. Linking R with an optimized version of 'BLAS' (< https://netlib.org/blas/>) may improve the computational performance of R code. The 'OpenBLAS' library is an optimized implementation of 'BLAS' that can be easily linked to R with the 'ropenblas' package.
Decision Models with Multi Attribute Utility Theory
Provides functions for the creation, evaluation and test of decision models based in Multi Attribute Utility Theory (MAUT). Can process and evaluate local risk aversion utilities for a set of indexes, compute utilities and weights for the whole decision tree defining the decision model and simulate weights employing Dirichlet distributions under addition constraints in weights. Also includes other rating analysis methods as for example the Colley, Offensive - Defensive ratings and the ranking aggregation with Borda count.
Semantic UI Support for Shiny
Creating a great user interface for your Shiny apps can be a hassle, especially if you want to work purely in R and don't want to use, for instance HTML templates. This package adds support for a powerful UI library Fomantic UI - < https://fomantic-ui.com/> (before Semantic). It also supports universal UI input binding that works with various DOM elements.
Spatial Regression Analysis
A collection of all the estimation functions for spatial cross-sectional models (on lattice/areal data using spatial weights matrices) contained up to now in 'spdep'. These model fitting functions include maximum likelihood methods for cross-sectional models proposed by 'Cliff' and 'Ord' (1973, ISBN:0850860369) and (1981, ISBN:0850860814), fitting methods initially described by 'Ord' (1975)
National Road Safety Observatory (ONSV) Style for 'ggplot2' Graphics
Helps to create 'ggplot2' charts in the style used by the National Road Safety Observatory (ONSV). The package includes functions to customize 'ggplot2' objects with new theme and colors.
Modeling Complex Longitudinal Data in a Quick and Easy Way
Matching longitudinal methodology models with complex sampling design. It fits fixed and random effects models and covariance structured models so far. It also provides tools to perform statistical tests considering these specifications as described in : Pacheco, P. H. (2021). "Modeling complex longitudinal data in R: development of a statistical package." < https://repositorio.ufjf.br/jspui/bitstream/ufjf/13437/1/pedrohenriquedemesquitapacheco.pdf>.
Microbiota STability ASsessment via Iterative cluStering
The toolkit 'µSTASIS' has been developed for the stability analysis of microbiota in a temporal framework by leveraging on iterative clustering. Concretely, the core function uses Hartigan-Wong k-means algorithm as many times as possible for stressing out paired samples from the same individuals to test if they remain together for multiple numbers of clusters over a whole data set of individuals. Moreover, the package includes multiple functions to subset samples from paired times, validate the results or visualize the output.