Physical Sciences and Mathematics Commons^™

Computational Network Analysis Of The Anatomical And Genetic Organizations In The Mouse Brain, Shuiwang Ji

Computer Science Faculty Publications

Motivation: The mammalian central nervous system (CNS) generates high-level behavior and cognitive functions. Elucidating the anatomical and genetic organizations in the CNS is a key step toward understanding the functional brain circuitry. The CNS contains an enormous number of cell types, each with unique gene expression patterns. Therefore, it is of central importance to capture the spatial expression patterns in the brain. Currently, genome-wide atlas of spatial expression patterns in the mouse brain has been made available, and the data are in the form of aligned 3D data arrays. The sheer volume and complexity of these data pose significant challenges …

Mark-Recapture Creel Survey And Survival Models, Shampa Saha

Mathematics & Statistics Theses & Dissertations

In this dissertation, we consider a model based approach to the estimation of exploitation rate of a fish population by combining mark-recapture procedures with a creel survey. We also consider the analysis of a proportional hazards survival model for randomly censored observations, known as the Koziol-Green model. The model assumes that the lifetime survivor function is a power of the censored time survivor function.

In Chapter 2, we introduce the model based approach to the estimation of the exploitation rate of a fish population by combining mark-recapture procedures with a creel survey. We assume that in the beginning of a …

Software Reliability Models, Syed Afzal Hossain

Mathematics & Statistics Theses & Dissertations

The problem considered here is the building of Non-homogeneous Poisson Process (NHPP) model. Currently existing popular NHPP process models like Goel-Okumoto (G-O) and Yamada et al models suffer from the drawback that the probability density function of the inter-failure times is an improper density function. This is because the event no failure in (0, oo] is allowed in these models. In real life situations we cannot draw sample(s) from such a population and also none of the moments of inter-failure times exist. Therefore, these models are unsuitable for modelling real software error data. On the other hand if the density …