Implements conjugate power priors for efficient Bayesian analysis 
    of normal data. Power priors allow principled incorporation of historical 
    information while controlling the degree of borrowing through a discounting 
    parameter (Ibrahim and Chen (2000) <doi:10.1214/ss/1009212519>). This 
    package provides closed-form conjugate representations for both univariate 
    and multivariate normal data using Normal-Inverse-Chi-squared and 
    Normal-Inverse-Wishart distributions, eliminating the need for MCMC sampling. 
    The conjugate framework builds upon standard Bayesian methods described in 
    Gelman et al. (2013, ISBN:978-1439840955).

A set of functions designed to calculate the standardised
    precipitation and standardised precipitation evapotranspiration indices
    using NASA POWER data as described in Blain et al. (2023)
    <doi:10.2139/ssrn.4442843>.  These indices are calculated using a reference
    data source.  The functions verify if the indices' estimates meet the
    assumption of normality and how well NASA POWER estimates represent
    real-world data.  Indices are calculated in a routine mode.  Potential
    evapotranspiration amounts and the difference between rainfall and potential
    evapotranspiration are also calculated.  The functions adopt a basic time
    scale that splits each month into four periods.  Days 1 to 7, days 8 to 14,
    days 15 to 21, and days 22 to 28, 29, 30, or 31, where 'TS=4' corresponds to
    a 1-month length moving window (calculated 4 times per month) and 'TS=48'
    corresponds to a 12-month length moving window (calculated 4 times per
    month).

Functions to calculate power and
                sample size for testing main effect or interaction effect in
                the survival analysis of epidemiological studies
                (non-randomized studies), taking into account the 
                correlation between the covariate of the
                interest and other covariates. Some calculations also take 
                into account the competing risks and stratified analysis. 
                This package also includes
                a set of functions to calculate power and sample size
                for testing main effect in the survival analysis of 
                randomized clinical trials and conditional logistic regression for nested case-control study.