Provides access to datasets published by 'Hlídač státu' <https://www.hlidacstatu.cz/>, 
    a Czech watchdog, via their API.

A suite of diagnostic tools for hierarchical
    (multilevel) linear models. The tools include
    not only leverage and traditional deletion diagnostics (Cook's
    distance, covratio, covtrace, and MDFFITS) but also 
    convenience functions and graphics for residual analysis. Models
    can be fit using either lmer in the 'lme4' package or lme in the 'nlme' package.

Provides functions for visualization and decomposition in
    hierarchical linear models (HLM) for applications in education, psychology,
    and the social sciences. Includes variance decomposition for two-level and
    three-level data structures following Snijders and Bosker (2012,
    ISBN:9781849202015), intraclass correlation (ICC) estimation and design
    effect computation as described in Shrout and Fleiss (1979)
    <doi:10.1037/0033-2909.86.2.420>, and contextual effect decomposition via
    the Mundlak (1978) <doi:10.2307/1913646> specification distinguishing
    within- and between-cluster components. Supports visualization of random
    slopes and cross-level interactions following Hofmann and Gavin (1998)
    <doi:10.1177/014920639802400504> and Hamaker and Muthen (2020)
    <doi:10.1037/met0000239>. Multilevel models are estimated using 'lme4'
    (Bates et al., 2015 <doi:10.18637/jss.v067.i01>). An optional 'Shiny'
    application enables interactive exploration of model components and
    parameter variation. The implementation follows the multilevel modeling
    framework of Raudenbush and Bryk (2002, ISBN:9780761919049).

Provides constructors for hl-rhotrices of dimension 2, 4 and 6,
    together with computation of the determinant, adjoint, inverse and
    eigenvalues under the Robust Multiplication Method (RMM).
    A 'ggplot2'-based function visualises the rhomboidal layout and the
    decomposition into principal minors.

Fits latent space models for single networks and hierarchical latent space models for ensembles of networks as described in Sweet, Thomas & Junker (2013).