The percentile of r and r-squared (prr) generated by pivotal Monte Carlo analysis has been promoted as a goodness of fit measure by Robert B. Abernethy.
AbPval(F,R2,model="weibull")The quantity of complete failure data points under consideration.
The square of the correlation coefficient derived from residuals of the linear model.
A string defining the distribution under consideration. Only entry of "lnorm", or "lognormal" will alter the default of "weibull".
Returns a vector containing the P-value and the square of CCC (for comparison with R squared).
The value returned is derived from a correlation developed from previously run pivotal analysis with 10^8 random samples. Only the prr derived from 2 parameter models is judged to have usefullness in comparitive analysis. For validity of a 3rd parameter optimization on a given model over its 2 parameter fit, only the Likelihood Ratio Test should be considered.
Robert B. Abernethy, (2008) "The New Weibull Handbook, Fifth Edition"
Wes Fulton, (2005) "Improved Goodness of Fit: P-value of the Correlation Coefficient"
Chi-Chao Lui, (1997) "A Comparison Between The Weibull And Lognormal Models Used To Analyse Reliability Data" (dissertation from University of Nottingham)
# NOT RUN {
AbernethyPvalue<-AbPval(50, 0.996, "lnorm")
# }
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