person("Kostas", "Anagnostopoulos", role = c("aut"),
Description: A wide variety of ways to calculate (through equations) or predict (using 9 Machine learning methods as well as a stack algorithm combination of them all) the Low Density Lipoprotein values of patients based on the values of three other metrics as Total Cholesterol , Triglyceride and High Density Lipoprotein.

Description: A wide variety of ways to calculate (through equations) or predict (using 9 Machine learning methods as well as a stack algorithm combination of them all) the Low Density Lipoprotein values of patients based on the values of three other metrics, namely Total Cholesterol , Triglycerides and High Density Lipoprotein. It can also calculate the variance of LDL and the Atherogenic Index of Plasma (AIP) using error propagation and bootstrapping.
RColorBrewer, lattice, resample, moments, ggplot2, janitor,
Suggests: rmarkdown, knitr, Cubist, earth, gbm, glmnet, gridExtra,
kernlab, randomForest, tidyr, testthat (>= 3.0.0)

Description: This is a Neural Network regression model implementation using 'Keras', consisting of 10 Long Short-Term Memory layers that are fully connected along with the rest of the inputs.

Title: Finding Locally D-optimal optimal designs for some nonlinear and
Author: Ehsan Masoudi, Majid Sarmad and Hooshang Talebi
Description: this package provides functions for Finding Locally
D-optimal designs for Logistic, Negative Binomial, Poisson,
Michaelis-Menten, Exponential, Log-Linear, Emax, Richards,
Weibull and Inverse Quadratic regression models and also
functions for auto-constructing Fisher information matrix and
Frechet derivative based on some input variables and without

Title: Probability of Default Calibration
Description: Implementation of most popular approaches to PD (probability of default) calibration: Quasi Moment Matching algorithm (D.Tasche), algorithm proposed by M.van der Burgt, K.Pluto and D.Tasche's most prudent estimation methodology.

Description: Implementation of most popular approaches to PD (probability of default) calibration: Quasi Moment Matching algorithm (D. Tasche), algorithm proposed by M. van der Burgt, K. Pluto and D. Tasche's most prudent estimation methodology.