Change PP plot and continous sample quantile function

Abstract

Functional inference recommends data analysis of a sample of n observations by functional and graphical representations of its probability models using various functions on 0 < u < 1, including the quantile function. This paper discusses: charge PP plots and a continuous version of the sample quantile function which use the mid-distinct value probability integral transform; comparison density functions; comparison interpretation of probability integral transform; maximum spacings method of one sample parameter estimation.

Keywords:

• Functional inference
• Goodness of fit
• Comparison density
• Renyi information
• Quantile data analysis
• Continuous sample quantiles
• Maximum spacing parameter estimation
• Distinct mid-value probability transform
• Change PP Plot

^∗Research supported by U.S. Army Research Office.

^∗Research supported by U.S. Army Research Office.

Notes

^∗Research supported by U.S. Army Research Office.