Provides data on countries and their main city or agglomeration and
    the different distance measures and dummy variables indicating whether two
    countries are contiguous, share a common language or a colonial
    relationship. The reference article for these datasets is Mayer and Zignago
    (2011) <http://www.cepii.fr/CEPII/en/publications/wp/abstract.asp?NoDoc=3877>.

Functions and Data to support Context Driven Exploratory Projection Pursuit.

Retorna detalhes de dados de CEPs brasileiros, bairros, logradouros 
    e tal. (Returns info of Brazilian postal codes, city names, addresses 
    and so on.)

Read Condensed Cornell Ecology Program ('CEP') and legacy
    'CANOCO' files into R data frames.

Modeling associations between covariates and power spectra of replicated time series using a cepstral-based semiparametric framework. Implements a fast two-stage estimation procedure via Whittle likelihood and multivariate regression.The methodology is based on Li and Dong (2025) <doi:10.1080/10618600.2025.2473936>.

Provides functions and data files to help CE Public-Use
    Microdata (PUMD) users calculate annual estimated expenditure means,
    standard errors, and quantiles according to the methods used by the CE with
    PUMD. For more information on the CE please visit <https://www.bls.gov/cex>.
    For further reading on CE estimate calculations please see the CE
    Calculation section of the U.S. Bureau of Labor Statistics (BLS) Handbook of
    Methods at <https://www.bls.gov/opub/hom/cex/calculation.htm>. For
    further information about CE PUMD please visit
    <https://www.bls.gov/cex/pumd.htm>.

Perform censored quantile regression of Huang (2010) <doi:10.1214/09-AOS771>, and restore monotonicity respecting via adaptive interpolation for dynamic regression of Huang (2017) <doi:10.1080/01621459.2016.1149070>. The monotonicity-respecting restoration applies to general dynamic regression models including (uncensored or censored) quantile regression model, additive hazards model, and dynamic survival models of Peng and Huang (2007) <doi:10.1093/biomet/asm058>, among others.