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tyee001

VGAM:Vector Generalized Linear and Additive Models

An implementation of about 6 major classes of statistical regression models. The central algorithm is Fisher scoring and iterative reweighted least squares. At the heart of this package are the vector generalized linear and additive model (VGLM/VGAM) classes. VGLMs can be loosely thought of as multivariate GLMs. VGAMs are data-driven VGLMs that use smoothing. The book "Vector Generalized Linear and Additive Models: With an Implementation in R" (Yee, 2015) <DOI:10.1007/978-1-4939-2818-7> gives details of the statistical framework and the package. Currently only fixed-effects models are implemented. Many (100+) models and distributions are estimated by maximum likelihood estimation (MLE) or penalized MLE. The other classes are RR-VGLMs (reduced-rank VGLMs), quadratic RR-VGLMs, doubly constrained RR-VGLMs, quadratic RR-VGLMs, reduced-rank VGAMs, RCIMs (row-column interaction models)---these classes perform constrained and unconstrained quadratic ordination (CQO/UQO) models in ecology, as well as constrained additive ordination (CAO). Hauck-Donner effect detection is implemented. Note that these functions are subject to change; see the NEWS and ChangeLog files for latest changes.

Maintained by Thomas Yee. Last updated 2 months ago.

fortran

10 stars 10.67 score 3.6k scripts 169 dependents

swihart

rmutil:Utilities for Nonlinear Regression and Repeated Measurements Models

A toolkit of functions for nonlinear regression and repeated measurements not to be used by itself but called by other Lindsey packages such as 'gnlm', 'stable', 'growth', 'repeated', and 'event' (available at <https://www.commanster.eu/rcode.html>).

Maintained by Bruce Swihart. Last updated 2 years ago.

fortran

1 stars 8.35 score 358 scripts 70 dependents

pengyan2000

simplexreg:Regression Analysis of Proportional Data Using Simplex Distribution

Simplex density, distribution, quantile functions as well as random variable generation of the simplex distribution are given. Regression analysis of proportional data using various kinds of simplex models is available. In addition, GEE method can be applied to longitudinal data to model the correlation. Residual analysis is also involved. Some subroutines are written in C with GNU Scientific Library (GSL) so as to facilitate the computation.

Maintained by Peng Zhang. Last updated 9 years ago.

gslcpp

1.89 score 26 scripts 1 dependents

f-rousset

blackbox:Black Box Optimization and Exploration of Parameter Space

Performs prediction of a response function from simulated response values, allowing black-box optimization of functions estimated with some error. Includes a simple user interface for such applications, as well as more specialized functions designed to be called by the Migraine software (Rousset and Leblois, 2012 <doi:10.1093/molbev/MSR262>; Leblois et al., 2014 <doi:10.1093/molbev/msu212>; and see URL). The latter functions are used for prediction of likelihood surfaces and implied likelihood ratio confidence intervals, and for exploration of predictor space of the surface. Prediction of the response is based on ordinary Kriging (with residual error) of the input. Estimation of smoothing parameters is performed by generalized cross-validation.

Maintained by François Rousset. Last updated 1 years ago.

cpp

1.79 score 8 scripts 1 dependents

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