Description Usage Arguments Details Value Examples
The WREG.OLS
function executes the multiple linear
regression analysis using ordinary leastsquares regression.
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 
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 follows the basic implementation of ordinary leastsquares regression.
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  # 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)
# Run a simple regression
Y < importedData$Y$AEP_0.5
X < importedData$X[c("Sand", "OutletElev", "Slope")]
transY < "none"
result < WREG.OLS(Y, X, transY)

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