Scalable Statistical Methods for Ancestral Inference from Genomic Variation Data by Andrew Hans Chan Doctor of Philosophy in Computer Science University of California, Berkeley Professor Yun S. Song, Chair Developments in DNA sequencing technology over the last few years have yielded unprecedented volumes of genetic data. The resulting datasets are indispensable for a variety of purposes, from ...

This study applied statistical approaches to the discrimination of spatial variations between sites and between forest types in the upper area of the Liukuei Experimental Forest of Taiwan Forestry Research Institute, Taiwan. The main purpose was to compare the effectiveness of various statistical approaches and then present the best strategy for discriminating the spatial variations of species ...

In this paper, a data-driven approach to statistical modeling pronunciation variation is proposed. It consists of learning stochastic pronunciation rules. The proposed method jointly models different rules that define the same transformation. Hierarchic Grouping Rule Inference (HIEGRI) algorithm is proposed to generate this model based on graphs. HIEGRI algorithm detects the common patterns of ...

Bring home now the book enPDFd statistical engineering an algorithm for reducing variation in manufacturing processes to be your sources when going to read. It can be your new collection to not only display in your racks but also be the one that can help you fining the best sources. As in common, book is the window to get in the world and you can open the world easily. These wise words are real...

With the advance in CMOS VLSI circuit design through technology scaling, process variability has significantly increased uncertainties in the response of sub-45nm CMOS circuits. To address this challenge and obtain reliable fabricated chips, statistical timing analysis and library characterization tools have become significantly important. CPU-time intensive Monte Carlo (MC) simulations embedde...

The diurnal pattern of growth hormone (GH) serum levels depends on the frequency and amplitude of GH secretory events, the kinetics of GH infusion into and clearance from the circulation, and the feedback of GH on its secretion. We present a two-dimensional linear differential equation model based on these physiological principles to describe GH diurnal patterns. The model characterizes the ons...

Language on the Internet and social media varies due to time, geography and social factors. For example, consider an online chat forum where people from different regions across the world interact. In such scenarios, it is important to track and detect regional variation in language. A person from the UK, who is in conversation with someone from the USA could say “he is stuck in the lift” to me...

The cluster variation method (CVM) is a hierarchy of approximate variational techniques for discrete (Ising–like) models in equilibrium statistical mechanics, improving on the mean–field approximation and the Bethe–Peierls approximation, which can be regarded as the lowest level of the CVM. In recent years it has been applied both in statistical physics and to inference and optimization problem...

Cardiopulmonary bypass (CPB) is a complex clinical process that takes place within an extremely complex care deliver system. During the past 50 years, many technicaland device-related improvements have been implemented. However, there remains enormous opportunity to improve. As has been shown in other industries, understanding variation is the key to improvement of any process, and Statistical ...

Quantifying the variation in the human plasma proteome is an essential prerequisite for disease-specific biomarker detection. We report here on the longitudinal and individual variation in human plasma characterized by two-dimensional difference gel electrophoresis (2-D DIGE) using plasma samples from eleven healthy subjects collected three times over a two week period. Fixed-effects modeling w...