It performs regression analysis for zero-inflated and zero-altered data, enabling modeling of sparse response variable distributions and assessing their association with covariates. It computes Maximum Likelihood Estimates (MLE) and conducts model selection using AIC and BIC criteria. Additionally, it calculates Fisher Information, confidence intervals, standard errors, and z-scores for all model parameters.

Download and parse public files released by B3 and convert them
    into useful formats and data structures common to data analysis
    practitioners.

An approach to age-depth modelling that uses Bayesian statistics to reconstruct accumulation histories for deposits, through combining radiocarbon and other dates with prior information on accumulation rates and their variability. See Blaauw & Christen (2011).

Simulation of phenotype / genotype data under assortative mating. 
    Includes functions for generating Bahadur order-2 multivariate Bernoulli 
    variables with general and diagonal-plus-low-rank correlation structures. 
    Further details are provided in: Border and Malik (2022) 
    <doi:10.1101/2022.10.13.512132>.

'BaseX' <https://basex.org> is a XML database engine and a compliant 'XQuery 3.1' processor with full support of 'W3C Update Facility'. This package is a full client-implementation of the client/server protocol for 'BaseX' and provides functionalities to create, manipulate and query on XML-data.

A Pure R implementation of Bayesian Global Optimization with Gaussian Processes.

A novel bias-bound approach for non-parametric inference is introduced, 
    focusing on both density and conditional expectation estimation. 
    It constructs valid confidence intervals that account for the presence of 
    a non-negligible bias and thus make it possible to perform inference with 
    optimal mean squared error minimizing bandwidths. 
    This package is based on Schennach (2020) <doi:10.1093/restud/rdz065>.

The Brazilian Central Bank API delivers many datasets which regard economic
  activity, regional economy, international economy, public finances, credit
  indicators and many more. For more information please see <http://dadosabertos.bcb.gov.br/>.
  These datasets can be accessed through 'rbcb' functions and can be obtained in
  different data structures common to R ('tibble', 'data.frame', 'xts', ...).