Classical multiple correspondence analysis and multiple correspondence analysis via orthogonal polynomials

Provides two variants of multiple correspondence analysis (ca):
multiple ca and ordered multiple ca via orthogonal polynomials of Emerson.

R (> 3.0.1), methods, tools, ggplot2, ggrepel, gridExtra,
plotly

Monte Carlo Simulation for Surface Backscattering
Monte Carlo simulation is a stochastic method computing trajectories of photons in media. Surface backscattering is performing calculations in semi-infinite media and summarizing photon flux leaving the surface. This simulation is modeling the optical measurement of diffuse reflectance using an incident light beam. The semi-infinite media is considered to have flat surface. Media, typically biological tissue, is described by four optical parameters: absorption coefficient, scattering coefficient, anisotropy factor, refractive index. The media is assumed to be homogeneous.
Computational parameters of the simulation include: number of photons, radius of incident light beam, lowest photon energy threshold, intensity profile (halo) radius, spatial resolution of intensity profile.

Monte Carlo simulation is a stochastic method computing trajectories of photons in media. Surface backscattering is performing calculations in semi-infinite media and summarizing photon flux leaving the surface. This simulation is modeling the optical measurement of diffuse reflectance using an incident light beam. The semi-infinite media is considered to have flat surface. Media, typically biological tissue, is described by four optical parameters: absorption coefficient, scattering coefficient, anisotropy factor, refractive index. The media is assumed to be homogeneous.
Computational parameters of the simulation include: number of photons, radius of incident light beam, lowest photon energy threshold, intensity profile (halo) radius, spatial resolution of intensity profile.
You can find more information and validation in the Open Access paper.
Laszlo Baranyai (2020) <doi:10.1016/j.mex.2020.100958>.