Shiny Web Application for the Multichannel Attribution Problem. It is a user-friendly graphical interface for package 'ChannelAttribution'.

Adjusts the loglikelihood of common econometric models for
    clustered data based on the estimation process suggested in 
    Chandler and Bate (2007) <doi:10.1093/biomet/asm015>, using the 'chandwich' 
    package <https://cran.r-project.org/package=chandwich>, and provides 
    convenience functions for inference on the adjusted models.

Computes and visualize the results of the 0-1 test for chaos proposed
    by Gottwald and Melbourne (2004) <DOI:10.1137/080718851>. The algorithm is
    available in parallel for the independent values of parameter c. Additionally,
    fast RQA is added to distinguish chaos from noise.

The main objective of the package is to enter a word of at least two letters based on which an Iterated Function System with Probabilities is constructed, and a two-dimensional fractal containing the chosen word infinitely often is generated via the Chaos Game. Additionally, the package allows to project the two-dimensional fractal on several three-dimensional surfaces and to transform the fractal into another fractal with uniform marginals.

Estimation of gas transport properties (viscosity, diffusion, thermal conductivity) using Chapman-Enskok theory (Chapman and Larmor 1918, <doi:10.1098/rsta.1918.0005>) and of the second virial coefficient (Vargas et al. 2001, <doi:10.1016/s0378-4371(00)00362-9>) using the Lennard-Jones (12-6) potential. Up to the third order correction is taken into account for viscosity and thermal conductivity. It is also possible to calculate the binary diffusion coefficients of polar and non-polar gases in non-polar bath gases (Brown et al. 2011, <doi:10.1016/j.pecs.2010.12.001>). 16 collision integrals are calculated with four digit accuracy over the reduced temperature range [0.3, 400] using an interpolation function of Kim and Monroe (2014, <doi:10.1016/j.jcp.2014.05.018>).

CHAP-GWAS (Chromosomal Haplotype-Integrated Genome-Wide Association
    Study) provides a dynamically adaptive framework for genome-wide association
    studies (GWAS) that integrates chromosome-scale haplotypes with single
    nucleotide polymorphism (SNP) analysis. The method identifies and extends
    haplotype variants based on their phenotypic associations rather than
    predefined linkage blocks, enabling high-resolution detection of quantitative
    trait loci (QTL). By leveraging long-range phased haplotype information,
    CHAP-GWAS improves statistical power and offers a more comprehensive view of
    the genetic architecture underlying complex traits.