This dataset contains population estimates of all European cities 
    with at least 10,000 inhabitants during the period 1500-1800. These data are
    adapted from Jan De Vries, "European Urbanization, 1500-1800" (1984).

Tools to download data from the Eurostat database
    <https://ec.europa.eu/eurostat> together with search and manipulation
    utilities.

Goodness-of-fit tests for selection of r in the r-largest order
    statistics (GEVr) model. Goodness-of-fit tests for threshold selection in the
    Generalized Pareto distribution (GPD). Random number generation and density functions
    for the GEVr distribution. Profile likelihood for return level estimation
    using the GEVr and Generalized Pareto distributions. P-value adjustments for
    sequential, multiple testing error control. Non-stationary fitting of GEVr and
    GPD.
    Bader, B., Yan, J. & Zhang, X. (2016) <doi:10.1007/s11222-016-9697-3>.
    Bader, B., Yan, J. & Zhang, X. (2018) <doi:10.1214/17-AOAS1092>.

Provides tools for post-process, evaluate and visualize results from 3d Meteorological and Air Quality models against point observations (i.e. surface stations) and grid (i.e. satellite) observations.

Evaluates the performance of binary classifiers.  Computes
    confusion measures (TP, TN, FP, FN), derived measures (TPR, FDR,
    accuracy, F1, DOR, ..), and area under the curve.  Outputs are well
    suited for nested dataframes.

Contains a set of clustering methods and evaluation metrics to select the best number of the clusters based on clustering stability. Two references describe the methodology: Fahimeh Nezhadmoghadam, and Jose Tamez-Pena (2021)<doi:10.1016/j.compbiomed.2021.104753>, and Fahimeh Nezhadmoghadam, et al.(2021)<doi:10.2174/1567205018666210831145825>.

Provides various statistical methods for evaluating
    Individualized Treatment Rules under randomized data. The provided
    metrics include Population Average Value (PAV), Population Average
    Prescription Effect (PAPE), Area Under Prescription Effect Curve
    (AUPEC). It also provides the tools to analyze Individualized
    Treatment Rules under budget constraints. Detailed reference in Imai
    and Li (2019) <arXiv:1905.05389>.