hyper.fit: Generic N-Dimensional Hyperplane Fitting with Heteroscedastic Covariant Errors and Intrinsic Scatter

Includes two main high level codes for hyperplane fitting (hyper.fit) and visualising (hyper.plot2d / hyper.plot3d). In simple terms this allows the user to produce robust 1D linear fits for 2D x vs y type data, and robust 2D plane fits to 3D x vs y vs z type data. This hyperplane fitting works generically for any N-1 hyperplane model being fit to a N dimension dataset. All fits include intrinsic scatter in the generative model orthogonal to the hyperplane.

Install the latest version of this package by entering the following in R:
install.packages("hyper.fit")
AuthorAaron Robotham and Danail Obreschkow
Date of publication2016-08-01 17:29:45
MaintainerAaron Robotham <aaron.robotham@uwa.edu.au>
LicenseGPL-3
Version1.0.3

View on CRAN

Files

inst
inst/CITATION
NAMESPACE
NEWS
data
data/convtest1dNorm.tab
data/intrin.tab
data/convtest2dOpt.tab
data/convtest2dLD.tab
data/TFR.tab
data/trumpet.tab
data/datalist
data/MJB.tab
data/GAMAsmVsize.tab
data/hogg.tab
data/FP6dFGS.tab
R
R/hyper.like.R R/hyper.fit.R R/hyper.sigcor.R R/hyper.plot.R R/hyper.basics.R R/hyper.convert.R
MD5
build
build/partial.rdb
DESCRIPTION
man
man/hyper.like.Rd man/hyper.fit-package.Rd man/hyper.summary.Rd man/hyper.fit.Rd man/hyper.convert.Rd man/hyper.data.Rd man/hyper.basic.Rd man/hyper.plot.Rd man/hyper.sigcor.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.