This article deals with approximation of empirical distribution to standard normal distribution using Johnson transformation. This transformation enables us to approximate wide spectrum of continuous distributions with a normal distribution. The estimation of parameters of transformation...

In the dissertation, we study the statistical evaluation of treatment comparisons by evaluating the relative comparison of survival experiences between two treatment groups. We construct confidence interval and simultaneous confidence bands for the ratio and odds ratio of two survival functions...

Asymptotic expansions for the null distribution of thelogrank statistic and its distribution under local proportionalhazards alternatives are developed in the case of iid observations.The results, which are derived from the work of Gu (1992) andTaniguchi (1992), are easy to interpret, and...

We propose a new method to find spatially adaptive smoothing splines. This new method breaks down the interval [0, 1] into p disjoint sub-intervals. Then we define p functional components in [0, 1], which have two importantfeatures. First, the purpose of each of these p components is to estimate...

Determnation of the structure of a medium from normal-incidenceacoustic reflection data is a basic problem in fieldsas diverse as medical technology and the earth sciences; thisresearch examines the accuracy with which quantitative structureestimates can be made from noise-corrupted...

Previous research implementing stratification on the propensity score has generally relied on using five strata, based on prior theoretical groundwork and minimal empirical evidence as to the suitability of quintiles to adequately reduce bias in all cases and across all sample sizes. This study...

In terms of risk measurement, probability and quantile risk estimation have developed enormously in the past decade, from value-at-risk measures to coherent measures such as expected shortfall. These measures allow an investor to determine their risk profile accounting for losses (quantiles) at...

To overcome the curse of dimensionality, dimension reduction is important andnecessary for understanding the underlying phenomena in a variety of fields.Dimension reduction is the transformation of high-dimensional data into ameaningful representation in the low-dimensional space. It can be...