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Kendall-Theil Robust Line - A Visual Basic Program for Calculating and Graphing Robust Nonparametric Estimates of Linear-Regression Coefficients Between Two Continuous Variables (Paperback)
Loot Price: R414
Discovery Miles 4 140
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Kendall-Theil Robust Line - A Visual Basic Program for Calculating and Graphing Robust Nonparametric Estimates of Linear-Regression Coefficients Between Two Continuous Variables (Paperback)
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Loot Price R414
Discovery Miles 4 140
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Total price: R434
Discovery Miles: 4 340
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The Kendall-Theil Robust Line software (KTRLine-version 1.0) is a
Visual Basic program that may be used with the Microsoft Windows
operating system to calculate parameters for robust, nonparametric
estimates of linear-regression coefficients between two continuous
variables. The KTRLine software was developed by the U.S.
Geological Survey, in cooperation with the Federal Highway
Administration, for use in stochastic data modeling with local,
regional, and national hydrologic data sets to develop
planning-level estimates of potential effects of highway runoff on
the quality of receiving waters. The Kendall-Theil robust line was
selected because this robust nonparametric method is resistant to
the effects of outliers and nonnormality in residuals that commonly
characterize hydrologic data sets. The slope of the line is
calculated as the median of all possible pairwise slopes between
points. The intercept is calculated so that the line will run
through the median of input data. A single-line model or a
multisegment model may be specified. The program was developed to
provide regression equations with an error component for stochastic
data generation because nonparametric multisegment regression tools
are not available with the software that is commonly used to
develop regression models. The Kendall-Theil robust line is a
median line and, therefore, may underestimate total mass, volume,
or loads unless the error component or a bias correction factor is
incorporated into the estimate. Regression statistics such as the
median error, the median absolute deviation, the prediction error
sum of squares, the root mean square error, the confidence interval
for the slope, and the bias correction factor for median estimates
are calculated by use of nonparametric methods. These statistics,
however, may be used to formulate estimates of mass, volume, or
total loads. The program is used to read a two- or three-column
tab-delimited input file with variable names in the first row and
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