Designed to add datasets which are used in the Nonparametric Statistical Methods textbook, 3rd edition.

To account for non-stationary multivariate data, this package implements the framework including copula and marginal distributions. In addition to modeling and parameter estimations, it allows the computation and visualization of multivariate quantile curves for given events.
  This package is useful for a variety of disciplines such as finance, climatology and particularly for hydrological applications, where dependence structures and marginal parameters may vary over time.
  This framework, based on Chebana & Ouarda (2021) <doi:10.1016/j.jhydrol.2020.125907>, integrates both multivariate and non-stationary aspects to be more accurate (e.g. for risk assessment) and more realistic (e.g. considering climate changes).

National Statistical Office of Mongolia (NSO) is the national statistical service and an organization of Mongolian government. NSO provides open access to official data via its API <http://opendata.1212.mn/en/doc>. The package NSO1212 has functions for accessing the API service. The functions are compatible with the API v2.0 and get data sets and its detailed informations from the API.

Implementation of Narrowest Significance Pursuit, a general and
    flexible methodology for automatically detecting localised regions in data sequences
    which each must contain a change-point (understood as an abrupt change in the
    parameters of an underlying linear model), at a prescribed global significance level.
    Narrowest Significance Pursuit works with a wide range of distributional assumptions
    on the errors, and yields exact desired finite-sample coverage probabilities,
    regardless of the form or number of the covariates. For details, see P. Fryzlewicz
    (2021) <https://stats.lse.ac.uk/fryzlewicz/nsp/nsp.pdf>.

Mainly for maximum likelihood estimation of nonparametric
             and semiparametric mixture models, but can also be used
             for fitting finite mixtures. The algorithms are
             developed in Wang (2007)
             <doi:10.1111/j.1467-9868.2007.00583.x> and Wang (2010)
             <doi:10.1007/s11222-009-9117-z>.