Quantiles, Conditional Quantiles, Confidence Quantiles for p, Logodds(p)
Emanuel Parzen · Communication in Statistics- Theory and Methods · 2009
This article discusses (1) our research to provide a framework for almost all of statistical methods for simple data, (2) need to plan the future of the “Science of Statistics” in order to compete for leadership in the practice of the “Statistics of Science”, (3) grand unifying ideas of the Science of Statistics, (4) an elegant rigorous proof when quantile function minimizes check loss function which is the basis of quantile regression, and (5) exact and approximate confidence quantiles (confidence interval endpoint functions) for parameters p and logodds(p) given a sample of a 0-1 variable.