Reads annual and quarterly financial reports from companies traded at B3, the Brazilian exchange 
            <https://www.b3.com.br/>. 
            All data is downloaded and imported from CVM's public ftp site <https://dados.cvm.gov.br/dados/CIA_ABERTA/>.

The getDTeval() function facilitates the translation of the original coding statement to an optimized form for improved runtime efficiency without compromising on the programmatic coding design.
    The function can either provide a translation of the coding statement, directly evaluate the translation to return a coding result, or provide both of these outputs.

Reads corporate data such as board composition and compensation for companies traded at B3, 
             the Brazilian exchange <https://www.b3.com.br/>. All data is downloaded and imported from the ftp site <http://dados.cvm.gov.br/dados/CIA_ABERTA/DOC/FRE/>.

A micro-package for getting your 'IP' address, either the 
    local/internal or the public/external one. Currently only 'IPv4' addresses
    are supported.

Tool for import and process data from 'Lattes' curriculum platform (<http://lattes.cnpq.br/>). The Brazilian government keeps an extensive base of curricula for academics from all over the country, with over 5 million registrations. The academic life of the Brazilian researcher, or related to Brazilian universities, is documented in 'Lattes'. Some information that can be obtained: professional formation, research area, publications, academics advisories, projects, etc. 'getLattes' package allows work with 'Lattes' data exported to XML format.

A simple API for downloading and reading xml data directly from Lattes <http://lattes.cnpq.br/>.

Quantifying systematic heterogeneity in meta-analysis using R.
    The M statistic aggregates heterogeneity information across multiple
    variants to, identify systematic heterogeneity patterns and their direction
    of effect in meta-analysis. It's primary use is to identify outlier studies,
    which either show "null" effects or consistently show stronger or weaker
    genetic effects than average across, the panel of variants examined in a
    GWAS meta-analysis. In contrast to conventional heterogeneity metrics
    (Q-statistic, I-squared and tau-squared) which measure random heterogeneity
    at individual variants, M measures systematic (non-random)
    heterogeneity across multiple independently associated variants. Systematic
    heterogeneity can arise in a meta-analysis due to differences in the study
    characteristics of participating studies. Some of the differences may
    include: ancestry, allele frequencies, phenotype definition, age-of-disease
    onset, family-history, gender, linkage disequilibrium and quality control
    thresholds. See <https://magosil86.github.io/getmstatistic/> for statistical
    statistical theory, documentation and examples.