Conducts Bayesian Hypothesis tests of a point null hypothesis against a two-sided alternative
using Non-local Alternative Prior (NAP) for one- and two-sample z- and t-tests
(Pramanik and Johnson, 2022). Under the alternative, the NAP is assumed on the standardized
effects size in one-sample tests and on their differences in two-sample tests. The package
considers two types of NAP densities: (1) the normal moment prior, and (2) the composite alternative.
In fixed design tests, the functions calculate the Bayes factors and the expected weight of evidence
for varied effect size and sample size. The package also provides a sequential testing framework using the
Sequential Bayes Factor (SBF) design. The functions calculate the operating characteristics (OC)
and the average sample number (ASN), and also conducts sequential tests for a sequentially observed data.

Performs the processing and normalisation of Nanostring miRNA
and mRNA data
Enables the processing and normalisation of the standard mRNA data output from the Nanostring nCounter software

Performs the Processing and Normalisation of Nanostring miRNA
and mRNA Data
Enables the processing and normalisation of the standard mRNA data output from the Nanostring nCounter software.

Maximum Likelihood method in estimating effective population
size from genetic data
Estimate the effective population size of a closed population using genetic data collected from two or more data points.

Model-based clustering of high-dimensional nonnegative
data that follow Generalized Negative Binomial distribution. All functions
in this package applies to either continuous or integer data. Correlation
between variables is allowed, while samples are assumed to be independent.

Model-based clustering of high-dimensional non-negative
data that follow Generalized Negative Binomial distribution. All functions
in this package applies to either continuous or integer data. Correlation
between variables are allowed, while samples are assumed to be independent.