This package allows the user to access functionality in the CDK, a Java framework for cheminformatics. This allows the user to load molecules, evaluate fingerprints, calculate molecular descriptors and so on. In addition the CDK API allows the user to view structures in 2D.
Statistical evaluation of calibration curves by different regression techniques: ordinary, weighted, robust (up to 4th order polynomial). Log-log and Box-Cox transform, estimation of optimal power and weighting scheme. Tests for heteroscedascity and normality of residuals. Different kinds of plots commonly used in illustrating calibrations. Easy "inverse prediction" of concentration by given responses and statistical evaluation of results (comparison of precision and accuracy by common tests).
Kappa, ICC, Cronbach alpha, screeplot, mtmm
This package contains linear and nonlinear regression methods based on Partial Least Squares and Penalization Techniques. Model parameters are selected via cross-validation, and confidence intervals ans tests for the regression coefficients can be conducted via jackknifing.
Multivariate regression methods Partial Least Squares Regression (PLSR), Principal Component Regression (PCR) and Canonical Powered Partial Least Squares (CPPLS)
Robust PCA by Projection Pursuit
An R interface to the Lawson-Hanson implementation of an algorithm for non-negative least squares (NNLS). Also allows the combination of non-negative and non-positive constraints.
Fit and compare Gaussian linear and nonlinear mixed-effects models.
The nls.lm function provides an R interface to lmder and lmdif from the MINPACK library, for solving nonlinear least-squares problems by a modification of the Levenberg-Marquardt algorithm, with support for lower and upper parameter bounds. The implementation can be used via nls-like calls using the nlsLM function.
Implements the LS-PLS (least squares - partial least squares) method described in for instance J