Description Usage Arguments Details Value Examples
The WREG.UW
function executes the multiple linear
regression analysis using a userprovided weighting matrix.
1 
Y 
The dependent variable of interest, with any transformations already applied. 
X 
The independent variables in the regression, with any transformations
already applied. Each row represents a site and each column represents a
particular independe variable. (If a leading constant is used, it should be
included here as a leading column of ones.) The rows must be in the same
order as the dependent variables in 
customWeight 
This allows the user to enter a custom weighting matrix.
It is included also to provide legacy code for WREG v. 1.05.

transY 
A required character string indicating if the the dependentvariable was transformed by the common logarithm ('log10'), transformed by the natural logarithm ('ln') or untransformed ('none'). 
x0 
A vector containing the independent variables (as above) for a particular target site. This variable is only used for ROI analysis. 
This function allows users to develop weights outside of the WREG program and observe the resultant regressions. Note that the weighting matrix must be invertible.
All outputs are returned as part of a list. The elements of the list depend on the type of regression performed. The elements of the list may include:
Coefs 
A data frame composed of four variables: (1)

ResLevInf 
A data frame composed of three variables for each site in
the regression. 
LevLim 
The critical value of
leverage. See 
InflLim 
The critical value of
influence. See 
LevInf.Sig 
A logical matrix indicating if the leverage (column 1) is significant and the influence (column 2) is significant for each site in the regression. 
PerformanceMetrics 
A list of not more than ten elements. All
regression types return the mean squared error of residuals ( 
X 
The input predictors. 
Y 
The input observations. 
fitted.values 
A vector of model estimates from the regression model. 
residuals 
A vector of model residuals. 
Weighting 
The weighting matrix used to develop regression estimates. 
Input 
A list of input parameters for error searching. Currently empty. 
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17  # Import some example data
peakFQdir < paste0(
file.path(system.file("exampleDirectory", package = "WREG"),
"pfqImport"))
gisFilePath < file.path(peakFQdir, "pfqSiteInfo.txt")
importedData < importPeakFQ(pfqPath = peakFQdir, gisFile = gisFilePath)
# Organizing input data
Y < importedData$Y$AEP_0.5
X < importedData$X[c("Sand", "OutletElev", "Slope")]
transY < "none"
# Make simple weighting using inverse record lengths
inverseRecLen < diag(1 / diag(importedData$recLen))
# Run userweights regression
result < WREG.UW(Y, X, customWeight = inverseRecLen, transY)

Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.