Calculation of the parametric, nonparametric confidence intervals
 for the difference or ratio of location parameters, nonparametric confidence interval
 for the Behrens-Fisher problem and for the difference, ratio and odds-ratio of binomial
 proportions for comparison of independent samples. Common wrapper functions to split 
 data sets and apply confidence intervals or tests to these subsets.
 A by-statement allows calculation of CI separately for the levels of further factors. 
 CI are not adjusted for multiplicity.

Provides functions for landscape analysis and data retrieval. 
    The package allows users to download environmental variables from global 
    datasets (e.g., WorldClim, ESA WorldCover, Nighttime Lights), and to 
    compute spatial and landscape metrics using a hexagonal grid system 
    based on the H3 spatial index. It is useful for ecological modeling, 
    biodiversity studies, and spatial data processing in landscape ecology. 
    Fick and Hijmans (2017) <doi:10.1002/joc.5086>. 
    Zanaga et al. (2022) <doi:10.5281/zenodo.7254221>. 
    Uber Technologies Inc. (2022) "H3: Hexagonal hierarchical spatial index".

The goal of 'pak' is to make package installation faster and
    more reliable. In particular, it performs all HTTP operations in
    parallel, so metadata resolution and package downloads are fast.
    Metadata and package files are cached on the local disk as well. 'pak'
    has a dependency solver, so it finds version conflicts before
    performing the installation. This version of 'pak' supports CRAN,
    'Bioconductor' and 'GitHub' packages as well.

Provides a comprehensive suite of tools for analyzing Pakistan's Quarterly National Accounts data. Users can gain detailed insights into Pakistan's economic performance, visualize quarterly trends, and detect patterns and anomalies in key economic indicators. Compare sector contributions—including agriculture, industry, and services—to understand their influence on economic growth or decline. Customize analyses by filtering and manipulating data to focus on specific areas of interest. Ideal for policymakers, researchers, and analysts aiming to make informed, data-driven decisions based on timely and detailed economic insights.