The code computes the structural intervention distance (SID) between a true directed acyclic graph (DAG) and an estimated DAG. Definition and details about the implementation can be found in J. Peters and P. Bühlmann: "Structural intervention distance (SID) for evaluating causal graphs", Neural Computation 27, pages 771-799, 2015  <doi:10.1162/NECO_a_00708>.

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>.

Allows the user to connect with IBGE's (Instituto Brasileiro de 
    Geografia e Estatistica, see <https://www.ibge.gov.br/> for more information)
    SIDRA API in a flexible way. SIDRA is the acronym to "Sistema IBGE de 
    Recuperacao Automatica" and is the system where IBGE turns available 
    aggregate data from their researches.

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' package, ARS metadata is ingested (JSON or Excel format),
    producing programmes to generate Analysis Results Datasets (ARDs).