Get Data Frame Representations of ‘Elasticsearch’ Results (uptasticsearch)
Elasticsearch’ is an open-source, distributed, document-based datastore (<https://…/elasticsearch> ). It provides an ‘HTTP’ ‘API’ for querying the database and extracting datasets, but that ‘API’ was not designed for common data science workflows like pulling large batches of records and normalizing those documents into a data frame that can be used as a training dataset for statistical models. ‘uptasticsearch’ provides an interface for ‘Elasticsearch’ that is explicitly designed to make these data science workflows easy and fun.

Credible Subsets (credsubs)
Functions for constructing simultaneous credible bands and identifying subsets via the ‘credible subsets’ (also called ‘credible subgroups’) method.

Augmented and Penalized Minimization Method L0 (APML0)
Fit linear and Cox models regularized with L0, lasso (L1), elastic-net (L1 and L2), or net (L1 and Laplacian) penalty, and their adaptive forms, such as adaptive lasso / elastic-net and net adjusting for signs of linked coefficients. It solves L0 penalty problem by simultaneously selecting regularization parameters and the number of non-zero coefficients. This augmented and penalized minimization method provides an approximation solution to the L0 penalty problem, but runs as fast as L1 regularization problem. The package uses one-step coordinate descent algorithm and runs extremely fast by taking into account the sparsity structure of coefficients. It could deal with very high dimensional data and has superior selection performance.

Social Autocorrelation (social)
A set of functions to quantify and visualise social autocorrelation.

Systematic Screening of Study Data for Subgroup Effects (subscreen)
Systematically screens study data for subgroup effects and visualizes these.

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