A set of functions for two-dimensional sociometric status
    determination with rating scales. For each person assessed, SSrat computes
    probability distributions of the total scores for `Sympathy' (S),
    `Antipathy' (A), social `Preference' (P) and social `Impact' (I), and
    applies a set of criteria for sociometric status categorization.

Provides the necessary sample size for a longitudinal study with binary outcome in order to attain a pre-specified power while strictly maintaining the Type I error rate. 
 Kapur K, Bhaumik R, Tang XC, Hur K, Reda DJ, Bhaumik D (2014) <doi:10.1002/sim.6203>.

Calculates the power and sample size based on the difference in Restricted Mean Survival Time.

Implement the algorithm provided in scan for estimating the 
  transmission route on railway network using passenger volume. It is a 
  generalization of the scan statistic approach for railway network to identify
  the hot railway route for transmitting infectious diseases.

This is a collection of functions to calculate stop-signal reaction time (SSRT). Includes functions for both "integration" and "mean" methods; both fixed and adaptive stop-signal delays are supported (see appropriate functions). Calculation is based on Verbruggen et al. (2019) <doi:10.7554/eLife.46323.001> and Verbruggen et al. (2013) <doi:10.1177/0956797612457390>.

Tools to import survey files in the '.sss' (triple-s) format. 
    The package provides the function 'read.sss()' that reads the '.asc' 
    (or '.csv') and '.sss' files of a triple-s survey data file. 
    See also <https://triple-s.org/>.

Imports Variant Calling Format file into R. It can detect
             whether a sample contains contaminant from the same species.
             In the first stage of the approach, a change-point detection
             method is used to identify copy number variations for filtering.
             Next, features are extracted from the data for a support vector
             machine model. For log-likelihood calculation, the deviation
             parameter is estimated by maximum likelihood method. Using
             a radial basis function kernel support vector machine, the
             contamination of a sample can be detected.