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Applied Statistics

2013

Articles 1 - 6 of 6

Full-Text Articles in Mathematics

A Study Of Non-Central Skew T Distributions And Their Applications In Data Analysis And Change Point Detection, Abeer Hasan Jul 2013

A Study Of Non-Central Skew T Distributions And Their Applications In Data Analysis And Change Point Detection, Abeer Hasan

Abeer Hasan

Over the past three decades there has been a growing interest in searching for distribution
families that are suitable to analyze skewed data with excess kurtosis. The search started
by numerous papers on the skew normal distribution. Multivariate t distributions started to
catch attention shortly after the development of the multivariate skew normal distribution.
Many researchers proposed alternative methods to generalize the univariate t distribution to
the multivariate case. Recently, skew t distribution started to become popular in research.
Skew t distributions provide more exibility and better ability to accommodate long-tailed
data than skew normal distributions.
In this dissertation, a new …

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Iterative Statistical Verification Of Probabilistic Plans, Colin M. Potts May 2013

Iterative Statistical Verification Of Probabilistic Plans, Colin M. Potts

Lawrence University Honors Projects

Artificial intelligence seeks to create intelligent agents. An agent can be anything: an autopilot, a self-driving car, a robot, a person, or even an anti-virus system. While the current state-of-the-art may not achieve intelligence (a rather dubious thing to quantify) it certainly achieves a sense of autonomy. A key aspect of an autonomous system is its ability to maintain and guarantee safety—defined as avoiding some set of undesired outcomes. The piece of software responsible for this is called a planner, which is essentially an automated problem solver. An advantage computer planners have over humans is their ability to consider and …

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Quantitative Interpretation Of A Genetic Model Of Carcinogenesis Using Computer Simulations, Donghai Dai, Brandon Beck, Xiaofang Wang, Cory Howk, Yi Li Apr 2013

Quantitative Interpretation Of A Genetic Model Of Carcinogenesis Using Computer Simulations, Donghai Dai, Brandon Beck, Xiaofang Wang, Cory Howk, Yi Li

Donghai Dai

The genetic model of tumorigenesis by Vogelstein et al. (V theory) and the molecular definition of cancer hallmarks by Hanahan and Weinberg (W theory) represent two of the most comprehensive and systemic understandings of cancer. Here, we develop a mathematical model that quantitatively interprets these seminal cancer theories, starting from a set of equations describing the short life cycle of an individual cell in uterine epithelium during tissue regeneration. The process of malignant transformation of an individual cell is followed and the tissue (or tumor) is described as a composite of individual cells in order to quantitatively account for intra-tumor …

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Some Minor-Closed Classes Of Signed Graphs, Dan Slilaty, Xiangqian Zhou Feb 2013

Some Minor-Closed Classes Of Signed Graphs, Dan Slilaty, Xiangqian Zhou

Mathematics and Statistics Faculty Publications

We define four minor-closed classes of signed graphs in terms of embeddability in the annulus, projective plane, torus, and Klein bottle. We give the full list of 20 excluded minors for the smallest class and make a conjecture about the largest class.

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Correlation Coefficient Of Interval Neutrosophic Set, Said Broumi, Florentin Smarandache Jan 2013

Correlation Coefficient Of Interval Neutrosophic Set, Said Broumi, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

In this paper we introduce for the first time the concept of correlation coefficients of interval valued neutrosophic set (INS for short). Respective numerical examples are presented.

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New Microarray Image Segmentation Using Segmentation Based Contours Method, Yuan Cheng Jan 2013

New Microarray Image Segmentation Using Segmentation Based Contours Method, Yuan Cheng

Doctoral Dissertations

The goal of the research developed in this dissertation is to develop a more accurate segmentation method for Affymetrix microarray images. The Affymetrix microarray biotechnologies have become increasingly important in the biomedical research field. Affymetrix microarray images are widely used in disease diagnostics and disease control. They are capable of monitoring the expression levels of thousands of genes simultaneously. Hence, scientists can get a deep understanding on genomic regulation, interaction and expression by using such tools.

We also introduce a novel Affymetrix microarray image simulation model and how the Affymetrix microarray image is simulated by using this model. This simulation …

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