Computes shrinkage estimators for regression problems. Selects penalty parameter by minimizing bias and variance in the effect estimate, where bias and variance are estimated from the posterior predictive distribution. See Keller and Rice (2017) <doi:10.1093/aje/kwx225> for more details.

An implementation of extended state-space SIR models developed by
    Song Lab at UM school of Public Health. There are several functions available
    by 1) including a time-varying transmission modifier, 2) adding a time-dependent
    quarantine compartment, 3) adding a time-dependent antibody-immunization compartment.
    Wang L. (2020) <doi:10.6339/JDS.202007_18(3).0003>.

Misc functions programmed by Eduard Szöcs. 
    Provides read_regnie() to read gridded precipitation data from German Weather 
    Service  (DWD, see <http://www.dwd.de/> for more information).

Support in preparing a raw ESM dataset for statistical analysis. Preparation includes the handling of errors (mostly due to technological reasons) and the generating of new variables that are necessary and/or helpful in meeting the conditions when statistically analyzing ESM data. The functions in 'esmprep' are meant to hierarchically lead from bottom, i.e. the raw (separated) ESM dataset(s), to top, i.e. a single ESM dataset ready for statistical analysis. This hierarchy evolved out of my personal experience in working with ESM data.

Tailored explicitly for Experience Sampling Method (ESM)
    data, it contains a suite of functions designed to simplify
    preprocessing steps and create subsequent reporting. It empowers
    users with capabilities to extract critical insights during
    preprocessing, conducts thorough data quality assessments (e.g., design
    and sampling scheme checks, compliance rate, careless responses), and
    generates visualizations and concise summary tables tailored
    specifically for ESM data. Additionally, it streamlines the creation
    of informative and interactive preprocessing reports, enabling
    researchers to transparently share their dataset preprocessing
    methodologies. Finally, it is part of a larger ecosystem which
    includes a framework and a web gallery
    (<https://preprocess.esmtools.com/>).