Datasets with yearly (2000 to 2021) Brazilian population estimates from DataSUS/Brazilian Health Ministry, aggregated by state, municipality, sex, and age groups. The data in this package is manually downloaded from the DataSUS website and converted to tibbles.

Bayesian estimation and variable selection for quantile regression models.

Provides the facility to calculate the Brainerd-Robinson similarity coefficient for the rows of an input table, and to calculate the significance of each coefficient based on a permutation approach; a heatmap is produced to visually represent the similarity matrix. Optionally, hierarchical agglomerative clustering can be performed and the silhouette method is used to identify an optimal number of clusters; the results of the clustering can be optionally used to sort the heatmap.

Broadly useful convenient and efficient R functions
    that bring users concise and elegant R data analyses.
    This package includes easy-to-use functions for
    (1) basic R programming
    (e.g., set working directory to the path of currently opened file;
    import/export data from/to files in any format;
    print tables to Microsoft Word);
    (2) multivariate computation
    (e.g., compute scale sums/means/... with reverse scoring);
    (3) reliability analyses and factor analyses;
    (4) descriptive statistics and correlation analyses;
    (5) t-test, multi-factor analysis of variance (ANOVA),
    simple-effect analysis, and post-hoc multiple comparison;
    (6) tidy report of statistical models
    (to R Console and Microsoft Word);
    (7) mediation and moderation analyses (PROCESS);
    and (8) additional toolbox for statistics and graphics.

Fully-interactive R interface to the 'OpenBUGS' software for Bayesian analysis using MCMC sampling.  Runs natively and stably in 32-bit R under Windows.  Versions running on x86Linux and on 64-bit R under Windows are in "beta" status and less efficient.

Provides high-level modeling functions to define and train
    models using the 'torch' R package. Models include linear, logistic,
    and multinomial regression as well as multilayer perceptrons.