Provides tools for splitting large Excel worksheets into multiple smaller sheets based on a specified number of rows per chunk. The package reads Excel files, partitions the data efficiently using the 'data.table' package, and writes the resulting subsets into a single workbook with multiple sheets using the 'openxlsx' package. This is useful for handling large datasets, preparing data for reporting, and exporting manageable Excel files for downstream analysis.

Functions for computing split regularized estimators defined in Christidis, Lakshmanan, 
             Smucler and Zamar (2019) <doi:10.48550/arXiv.1712.03561>. The approach fits linear regression models that
             split the set of covariates into groups. The optimal split of the variables into groups and the 
             regularized estimation of the regression coefficients are performed by minimizing  an objective 
             function that encourages sparsity within each group and diversity among them. 
             The estimated coefficients are then pooled together to form the final fit.

Functions to generate or sample from all possible splits of features or variables
             into a number of specified groups. Also computes the best split selection estimator 
             (for low-dimensional data) as defined in Christidis, Van Aelst and Zamar (2019) 
             <arXiv:1812.05678>.

Performs analysis of split-split plot experiments in both completely randomized and randomized complete block designs. With the results, you can obtain ANOVA, mean tests, and regression analysis (Este pacote faz a analise de experimentos em parcela subsubdivididas no delineamento inteiramente casualizado e delineamento em blocos casualizados. Com resultados e possível obter a ANOVA, testes de medias e análise de regressao) <https://www.expstat.com/pacotes-do-r>.

Online data collection tools like Google Forms often export
    multiple-response questions with data concatenated in cells. The
    concat.split (cSplit) family of functions splits such data into separate 
    cells. The package also includes functions to stack groups of columns and 
    to reshape wide data, even when the data are "unbalanced"---something 
    which reshape (from base R) does not handle, and which melt and dcast from 
    reshape2 do not easily handle.