Multiple Comparisons Procedures Based on Studentized Midrange and Range Distributions

Apply tests of multiple comparisons based on studentized 'midrange' and 'range' distributions. The tests are: Tukey Midrange ('TM' test), Student-Newman-Keuls Midrange ('SNKM' test), Means Grouping Midrange ('MGM' test) and Means Grouping Range ('MGR' test). The first two tests were published by Batista and Ferreira (2020) . The last two were published by Batista and Ferreira (2023) .

Attraction Indian Buffet Distribution

An implementation of probability mass function and sampling algorithms is provided for the attraction Indian buffet distribution (AIBD), originally from Dahl (2016) < https://ww2.amstat.org/meetings/jsm/2016/onlineprogram/ActivityDetails.cfm?SessionID=213038>.

Thresholded Partial Least Squares Model for Neuroimaging Data

Uses thresholded partial least squares algorithm to create a regression or classification model. For more information, see Lee, Bradlow, and Kable .

Simplify Access to Brazilian Social Data

Provides tools for downloading and processing microdata from the PNAD Contínua (PNADC, Continuous National Household Sample Survey), a rotating panel survey published quarterly by IBGE (Brazilian Institute of Geography and Statistics). Includes panel identification algorithms for linking individuals across survey waves.

Fuzzy and Non-Fuzzy Classifiers

It provides classifiers which can be used for discrete variables and for continuous variables based on the Naive Bayes and Fuzzy Naive Bayes hypothesis. Those methods were developed by researchers belong to the 'Laboratory of Technologies for Virtual Teaching and Statistics (LabTEVE)' and 'Laboratory of Applied Statistics to Image Processing and Geoprocessing (LEAPIG)' at 'Federal University of Paraiba, Brazil'. They considered some statistical distributions and their papers were published in the scientific literature, as for instance, the Gaussian classifier using fuzzy parameters, proposed by 'Moraes, Ferreira and Machado' (2021) .

Download Official Spatial Data Sets of Brazil

Easy access to official spatial data sets of Brazil. The package offers a wide range of spatial data sets available at various geographic scales and for various years with harmonized attributes, projection and fixed topology. All functions allow for seamless integration sf, DuckDB and Arrow.

Goodness of Fit Tests Based on Empirical Distribution Functions

Routines that allow the user to run goodness of fit tests based on empirical distribution functions for formal model evaluation in a general likelihood model. In addition, functions are provided to test if a sample follows Normal or Gamma distributions, validate the normality assumptions in a linear model, and examine the appropriateness of a Gamma distribution in generalized linear models with various link functions. Michael Arthur Stephens (1976) < http://www.jstor.org/stable/2958206>.

Datasets for 'spatstat' Family

Contains all the datasets for the 'spatstat' family of packages.

Importing and Analysing 'SNP' and 'Silicodart' Data Generated by Genome-Wide Restriction Fragment Analysis

Functions are provided that facilitate the import and analysis of 'SNP' (single nucleotide polymorphism) and 'silicodart' (presence/absence) data. The main focus is on data generated by 'DarT' (Diversity Arrays Technology), however, data from other sequencing platforms can be used once 'SNP' or related fragment presence/absence data from any source is imported. Genetic datasets are stored in a derived 'genlight' format (package 'adegenet'), that allows for a very compact storage of data and metadata. Functions are available for importing and exporting of 'SNP' and 'silicodart' data, for reporting on and filtering on various criteria (e.g. 'CallRate', heterozygosity, reproducibility, maximum allele frequency). Additional functions are available for visualization (e.g. Principle Coordinate Analysis) and creating a spatial representation using maps. 'dartR' supports also the analysis of 3rd party software package such as 'newhybrid', 'structure', 'NeEstimator' and 'blast'. Since version 2.0.3 we also implemented simulation functions, that allow to forward simulate 'SNP' dynamics under different population and evolutionary dynamics. Comprehensive tutorials and support can be found at our 'github' repository: github.com/green-striped-gecko/dartR/. If you want to cite 'dartR', you find the information by typing citation('dartR') in the console.

Efficient Implementation of K-Means++ Algorithm

Efficient implementation of K-Means++ algorithm. For more information see (1) "kmeans++ the advantages of the k-means++ algorithm" by David Arthur and Sergei Vassilvitskii (2007), Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms, Society for Industrial and Applied Mathematics, Philadelphia, PA, USA, pp. 1027-1035, and (2) "The Effectiveness of Lloyd-Type Methods for the k-Means Problem" by Rafail Ostrovsky, Yuval Rabani, Leonard J. Schulman and Chaitanya Swamy .