Functions to calculate some point estimators and estimate their variance under unequal probability sampling without replacement. Single and two-stage sampling designs are considered. Some approximations for the second-order inclusion probabilities (joint inclusion probabilities) are available (sample and population based). A variety of Jackknife variance estimators are implemented. Almost every function is written in C (compiled) code for faster results. The functions incorporate some performance improvements for faster results with large datasets.

Contains human behaviour datasets collected by the SAMPLING project (<https://sampling.warwick.ac.uk>).

Implementation of the SAM prior and generation of its
     operating characteristics for dynamically borrowing information
     from historical data. For details, please refer to Yang et al. (2023)
     <doi:10.1111/biom.13927>.

Estimation of the required sample size to validate a risk model for binary outcomes, based on the sample size equations proposed by Pavlou et al. (2021) <doi:10.1177/09622802211007522>. For precision-based sample size calculations, the user is required to enter the anticipated values of the C-statistic and outcome prevalence, which can be obtained from a previous study. The user also needs to specify the required precision (standard error) for the C-statistic, the calibration slope and the calibration in the large. The calculations are valid under the assumption of marginal normality for the distribution of the linear predictor.

Significance Analysis of Microarrays for differential expression analysis, RNAseq data and related problems.

Markov chain Monte Carlo samplers for posterior simulations of conjugate Bayesian nonparametric
    mixture models. Functionality is provided for Gibbs sampling as in Algorithm 3 of Neal (2000)
    <DOI:10.1080/10618600.2000.10474879>, restricted Gibbs merge-split sampling as described in Jain & Neal
    (2004) <DOI:10.1198/1061860043001>, and sequentially-allocated merge-split sampling <DOI:10.1080/00949655.2021.1998502>, as well as
    summary and utility functions.