README.md

SUR Kmeans

If you run into problems you can contact allen.chen@noaa.gov. Latent class inference with k-means and homogeneity testing implemented for a Seemingly Unrelated Regressions framework: uses Lin and Ng's (2012 Journal of Econometric Methods) k-means algorithm in conjunction with Pesaran and Yamagata's (2008 Journal of Econometrics) parameter homoegeneity test to uncover latent classes, implemented here for a Seemingly Unrelated Regressions framework.

Installation

To install with vignette:

> install.packages("devtools")
> library(devtools)

Set the directory you've downloaded the package into:

> setwd("J:/Fishperson/Directory_containing_sur.kmeans")

No vignettes to install with yet:

> install("sur.kmeans", build_vignettes = FALSE)

Check out documentation:

> help(package="sur.kmeans")

Need to add simulated data for test usage, then run wrapper function with variable names and data:

> kmeans_wrapper(FullTable, YYlist, XXlist, Vessel, testvars, nontestvars,
    nseeds, startseeds, runparallel=TRUE)

DISCLAIMER

“This repository is a scientific product and is not official communication of the National Oceanic and Atmospheric Administration, or the United States Department of Commerce. All NOAA GitHub project code is provided on an ‘as is’ basis and the user assumes responsibility for its use. Any claims against the Department of Commerce or Department of Commerce bureaus stemming from the use of this GitHub project will be governed by all applicable Federal law. Any reference to specific commercial products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply their endorsement, recommendation or favoring by the Department of Commerce. The Department of Commerce seal and logo, or the seal and logo of a DOC bureau, shall not be used in any manner to imply endorsement of any commercial product or activity by DOC or the United States Government.”



allen-chen-noaa-gov/sur.kmeans documentation built on March 5, 2024, 2:20 p.m.