Provides function to apply "Subgroup Identification based on Differential Effect Search" (SIDES) method proposed by Lipkovich et al. (2011) <doi:10.1002/sim.4289>.

Evolutionary reconstruction based on substitutions and insertion-deletion (indels) analyses in a distance-based framework as described in Muñoz-Pajares (2013) <doi:10.1111/2041-210X.12118>.

Interface to the SIDRA (Sistema IBGE de Recuperação Automática)
    web service provided by the Brazilian Institute of Geography and
    Statistics (IBGE). Data are retrieved through the official API
    <https://apisidra.ibge.gov.br/>.

Provides a flexible interface to the aggregate data available
    from the Brazilian Institute of Geography and Statistics (IBGE) through
    its SIDRA application programming interfaces. SIDRA is IBGE's system for
    retrieving aggregate statistical data.

We provide functions for estimation and inference of locally-stationary time series using the sieve methods and bootstrapping procedure. In addition, it also contains functions to generate Daubechies and Coiflet wavelet by Cascade algorithm and to process data visualization.

Allows to retrieve time series of all indicators available in the Bank of Mexico's Economic Information System (<http://www.banxico.org.mx/SieInternet/>).

Methods for regression with high-dimensional predictors and  univariate or maltivariate response variables. It considers the decomposition of the coefficient matrix that leads to the best approximation to the signal part in the response given any rank, and estimates the decomposition by solving a penalized generalized eigenvalue problem followed by a least squares procedure. Ruiyan Luo and Xin Qi (2017) <doi:10.1016/j.jmva.2016.09.005>.

Analysis Results Standard (ARS), a foundational standard by CDISC
    (Clinical Data Interchange Standards Consortium), provides a logical
    data model for metadata describing all components to calculate Analysis
    Results. <https://www.cdisc.org/standards/foundational/analysis-results-standard>
    Using 'siera', ARS metadata is ingested (JSON or Excel format), producing
    R programmes to generate Analysis Results Datasets (ARDs). Supports
    arbitrary-depth table structures, multi-value conditions, data-driven
    groupings, and CDISC-compliant ARD column stamping.