Provides tools for estimating uncertainty in individual 
    polygenic risk scores (PRSs) using both sampling-based and analytical 
    methods, as well as the Best Linear Unbiased Estimator (BLUE). 
    These methods quantify variability in PRS estimates for both binary 
    and quantitative traits. 
    See Henderson (1975) <doi:10.2307/2529430> for more details.

Estimates the density of a spatially distributed animal population 
  sampled with an array of passive detectors, such as traps. Models incorporating 
  distance-dependent detection are fitted by simulation and inverse prediction 
  as proposed by Efford (2004) <doi:10.1111/j.0030-1299.2004.13043.x>.

Advanced fuzzy logic based techniques are implemented to compute the similarity among different objects or items. Typically, application areas consist of transforming raw data into the corresponding advanced fuzzy logic representation and determining the similarity between two objects using advanced fuzzy similarity techniques in various fields of research, such as text classification, pattern recognition, software projects, decision-making, medical diagnosis, and market prediction. Functions are designed to compute the membership, non-membership, hesitant-membership, indeterminacy-membership, and refusal-membership for the input matrices. Furthermore, it also includes a large number of advanced fuzzy logic based similarity measure functions to compute the Intuitionistic fuzzy similarity (IFS), Pythagorean fuzzy similarity (PFS), and Spherical fuzzy similarity (SFS) between two objects or items based on their fuzzy relationships. It also includes working examples for each function with sample data sets.

Contains data sets, programmes and illustrations 
    discussed in the book, "Introduction to Probability, Statistics and R:
    Foundations for Data-Based Sciences."  Sahu (2024, isbn:9783031378645)
    describes the methods in detail.

An easy way to work with census, survey, and geographic data
    provided by IPUMS in R. Generate and download data through the IPUMS
    API and load IPUMS files into R with their associated metadata to
    make analysis easier. IPUMS data describing 1.4 billion individuals
    drawn from over 750 censuses and surveys is available free of charge
    from the IPUMS website <https://www.ipums.org>.