s_TLS: Total Least Squares Regression [R]

View source: R/s_TLS.R

s_TLSR Documentation

Total Least Squares Regression [R]

Description

A minimal function to perform total least squares regression

Usage

s_TLS(
  x,
  y = NULL,
  x.test = NULL,
  y.test = NULL,
  x.name = "x",
  y.name = "y",
  print.plot = FALSE,
  plot.fitted = NULL,
  plot.predicted = NULL,
  plot.theme = rtTheme,
  question = NULL,
  verbose = TRUE,
  outdir = NULL,
  save.mod = ifelse(!is.null(outdir), TRUE, FALSE),
  ...
)

Arguments

x

Numeric vector or matrix / data frame of features i.e. independent variables

y

Numeric vector of outcome, i.e. dependent variable

x.test

Numeric vector or matrix / data frame of testing set features Columns must correspond to columns in x

y.test

Numeric vector of testing set outcome

x.name

Character: Name for feature set

y.name

Character: Name for outcome

print.plot

Logical: if TRUE, produce plot using mplot3 Takes precedence over plot.fitted and plot.predicted.

plot.fitted

Logical: if TRUE, plot True (y) vs Fitted

plot.predicted

Logical: if TRUE, plot True (y.test) vs Predicted. Requires x.test and y.test

plot.theme

Character: "zero", "dark", "box", "darkbox"

question

Character: the question you are attempting to answer with this model, in plain language.

verbose

Logical: If TRUE, print summary to screen.

outdir

Path to output directory. If defined, will save Predicted vs. True plot, if available, as well as full model output, if save.mod is TRUE

save.mod

Logical: If TRUE, save all output to an RDS file in outdir save.mod is TRUE by default if an outdir is defined. If set to TRUE, and no outdir is defined, outdir defaults to paste0("./s.", mod.name)

...

Additional arguments

Details

The main differences between a linear model and TLS is that the latter assumes error in the features as well as the outcome. The solution is essentially the projection on the first principal axis.

Author(s)

E.D. Gennatas


egenn/rtemis documentation built on May 4, 2024, 7:40 p.m.