https://github.com/bonstats/gcreg

General Constraint Regression Models

https://github.com/bonstats/gcreg

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Keywords

constrained-regression mixed-effects monotonicity polynomial-regression r shape-constraints
Last synced: 6 months ago · JSON representation

Repository

General Constraint Regression Models

Basic Info
  • Host: GitHub
  • Owner: bonStats
  • License: gpl-3.0
  • Language: R
  • Default Branch: master
  • Homepage:
  • Size: 654 KB
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  • Open Issues: 3
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Topics
constrained-regression mixed-effects monotonicity polynomial-regression r shape-constraints
Created over 9 years ago · Last pushed about 8 years ago
Metadata Files
Readme License

README.md

gcreg: General Constraint Regression models in R

This package is currently being developed. It's aim is to provide methods for fitting regression models with: * Functional and shape constraints, e.g. monotonicity * Parameter inequality constraints * Joint constraints, e.g. combinations of the above * Other constraints that create closed and convex parameter spaces

The paper accompanying this package is available here.

The current focus of development is on monotonicity in polynomial fixed and mixed effects models but will be extended over time to more general models and constraints.

To get started, install this package from GitHub using the devtools package:

r devtools::install_github("bonStats/gcreg") library(gcreg)

To install with vignettes you will need to install some required packages and set build_vignettes = T: r install.packages(c("rmarkdown","ggplot2","fda")) devtools::install_github("bonStats/gcreg", build_vignettes = T) library(gcreg)

You can start fitting constrained polynomial models with the gcreg::cpm() function. For example

r library(fda) data(onechild) cpm(height~day, data = onechild, degree = 5, constraint = "monotone", c_region = c(1,312)) See the package vignettes for more examples: * Fixed effects constrained polynomial models (Updated: 2017-12-01) * Mixed effects monotone-constrained polynomial models (Updated: 2017-12-01)

Owner

  • Name: Joshua Bon
  • Login: bonStats
  • Kind: user
  • Location: Meanjin / Brisbane
  • Company: Queensland University of Technology

Research statistician. Computation and a lot of dabbling. Centre for Data Science, Queensland University of Technology

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