Physical Sciences and Mathematics Commons^™

The Most Representative Composite Rank Ordering Of Multi-Attribute Objects By The Particle Swarm Optimization, Sudhanshu K. Mishra

Sudhanshu K Mishra

Rank-ordering of individuals or objects on multiple criteria has many important practical applications. A reasonably representative composite rank ordering of multi-attribute objects/individuals or multi-dimensional points is often obtained by the Principal Component Analysis, although much inferior but computationally convenient methods also are frequently used. However, such rank ordering – even the one based on the Principal Component Analysis – may not be optimal. This has been demonstrated by several numerical examples. To solve this problem, the Ordinal Principal Component Analysis was suggested some time back. However, this approach cannot deal with various types of alternative schemes of rank ordering, mainly …

Corso Di Analisi Delle Serie Storiche A.A 2008/2009- Laboratorio Di Stata: Lezione 4 –Analisi Classica Delle Serie Storiche Ii (Formato Pdf), Carlo Drago

Carlo Drago

No abstract provided.

Corso Di Analisi Delle Serie Storiche A.A 2008/2009- Laboratorio Di Stata: Lezione 5 –Analisi Moderna Delle Serie Storiche (Formato Pdf), Carlo Drago

Carlo Drago

No abstract provided.

Basic Statistics-I, Durgesh Chandra Pathak

Durgesh Chandra Pathak

It's a presentation that I prepared for JRF-students in Development Studies.

Notes On The Two-Body Problem, Cathy Kessel

Cathy Kessel

No abstract provided.

Financial Distress And Idiosyncratic Volatility: An Empirical Investigation, Lorán Chollete, Jing Chen, Rina Ray

Lorán Chollete

No abstract provided.

Financial Implications Of Extreme And Rare Events, Lorán Chollete, Dwight Jaffee

Lorán Chollete

No abstract provided.

Dependence Of Macro Variables In The Us Economy, Lorán Chollete, Cathy Ning

Lorán Chollete

No abstract provided.

Modeling International Financial Returns With A Multivariate Regime-Switching Copula, Lorán Chollete, Andreas Heinen, Alfonso Valdesogo

Lorán Chollete

No abstract provided.

Uniqueprimer - A Web Utility For Design Of Specific Pcr Primers And Probes, Torstein Tengs

Dr. Torstein Tengs

We have developed a web-based tool for design of specific PCR primers and probes. The program allows you to enter primer sequence information as well as an optional probe, and sequence similarity searches (MegaBLAST) will be performed to see if the sequences match the same sequence entry in the specified database. If primers (and probe) match, this will be reported. The program can handle overlapping amplicons, amplification from a single primer, ambiguous bases and other problematic cases.

Optimal Experimental Design With The Sigma Point Method, René Schenkendorf, Andreas Kremling, Michael Mangold

René Schenkendorf

Using mathematical models for a quantitative description of dynamical systems requires the identification of uncertain parameters by minimising the difference between simulation and measurement. Owing to the measurement noise also, the estimated parameters possess an uncertainty expressed by their variances. To obtain highly predictive models, very precise parameters are needed. The optimal experimental design (OED) as a numerical optimisation method is used to reduce the parameter uncertainty by minimising the parameter variances iteratively. A frequently applied method to define a cost function for OED is based on the inverse of the Fisher information matrix. The application of this traditional method …

A Program Evaluation Of A Polypharmacy Sub-Population: Medications, Emergency Room Visits, And Hospitalizations, Brian W. Bresnahan, Kent M. Koprowicz, Sanchita Roy Choudhury, Ed Wong

Kent M Koprowicz

No abstract provided.

Hierarchical Hidden Markov Model With Application To Joint Analysis Of Chip-Chip And Chip-Seq Data, Hyungwon Choi, Debashis Ghosh, Zhaohui S. Qin

Debashis Ghosh

Motivation: Identication of transcription factor binding sites (TFBS) is a fundamental problem in understanding the mechanism of gene regulation. The ChIP-chip technology has accelerated this eort by providing a simultaneous genome-wide map of TFBS in a high-throughput fashion. Recently, a sequencing-based ChIP-seq has appeared as a promising alternative that can identify targets with an improved sensitivity/specicity in high resolution. However, studies have suggested that distinct experimental platforms can be complementary in TFBS identication. The availability of data obtained from multiple platforms motivates a meta-analysis for improved identication of candidate motifs.

Results: In this work, we propose a hierarchical hidden Markov …

A Double-Layered Mixture Model For The Joint Analysis Of Dna Copy Number And Gene Expression Data, Debashis Ghosh

Debashis Ghosh

Copy number aberration is a common form of genomic instability in cancer. Gene expression is closely tied to cytogenetic events by the central dogma of molecular biology, and serves as a mediator of copy number changes in disease phenotypes. Accordingly, it is of interest to develop proper statistical methods for jointly analyzing copy number and gene expression data. This work describes a novel Bayesian inferential approach for a double-layered mixture model (DLMM) which directly models the stochastic nature of copy number data and identifies abnormally expressed genes due to aberrant copy number. Simulation studies were conducted to illustrate the robustness …

Discrete Nonparametric Algorithms For Outlier Detection With Genomic Data, Debashis Ghosh

Debashis Ghosh

In high-throughput studies involving genetic data such as from gene expression microarrays, differential expression analysis between two or more experimental conditions has been a very common analytical task. Much of the resulting literature on multiple comparisons has paid relatively little attention to the choice of test statistic. In this article, we focus on the issue of choice of test statistic based on a special pattern of differential expression. The approach here is based on recasting multiple comparisons procedures for assessing outlying expression values. A major complication is that the resulting p-values are discrete; some theoretical properties of sequential testing procedures …

A Double-Layered Mixture Model For The Joint Analysis Of Dna Copy Number And Gene Expression Data, Debashis Ghosh

Debashis Ghosh

Copy number aberration is a common form of genomic instability in cancer. Gene expression is closely tied to cytogenetic events by the central dogma of molecular biology, and serves as a mediator of copy number changes in disease phenotypes. Accordingly, it is of interest to develop proper statistical methods for jointly analyzing copy number and gene expression data. This work describes a novel Bayesian inferential approach for a double-layered mixture model (DLMM) which directly models the stochastic nature of copy number data and identifies abnormally expressed genes due to aberrant copy number. Simulation studies were conducted to illustrate the robustness …

Discrete Nonparametric Algorithms For Outlier Detection With Genomic Data, Debashis Ghosh

Debashis Ghosh

In high-throughput studies involving genetic data such as from gene expression microarrays, differential expression analysis between two or more experimental conditions has been a very common analytical task. Much of the resulting literature on multiple comparisons has paid relatively little attention to the choice of test statistic. In this article, we focus on the issue of choice of test statistic based on a special pattern of differential expression. The approach here is based on recasting multiple comparisons procedures for assessing outlying expression values. A major complication is that the resulting p-values are discrete; some theoretical properties of sequential testing procedures …

An Examination Of The Persistence Of The Residual Child Welfare System In The United States: Addressing Charges Of Radical Theoretical Myopia With Implications For Social Work Practice, Peter Cabrera

Elián P. Cabrera-Nguyen

The United States follows what has been termed a residual approach to its public child welfare system. This article describes the residual model and contrasts it with the policies of other industrialized nations. It also explores the causes and persistence of the residual model in the United States through the lens of structural-functionalist theory. By doing so, this article attempts to respond to critics of structural social work who maintain that it is overly reliant on conflict theory and has nothing to offer in terms of distinct practice methods. Suggestions for a structurally informed social work practice are made.

Multilevel Functional Principal Component Analysis, Chong-Zhi Di, Ciprian M. Crainiceanu, Brian S. Caffo, Naresh M. Punjabi

Chongzhi Di

The Sleep Heart Health Study (SHHS) is a comprehensive landmark study of sleep and its impacts on health outcomes. A primary metric of the SHHS is the in-home polysomnogram, which includes two electroencephalographic (EEG) channels for each subject, at two visits. The volume and importance of this data presents enormous challenges for analysis. To address these challenges, we introduce multilevel functional principal component analysis (MFPCA), a novel statistical methodology designed to extract core intra- and inter-subject geometric components of multilevel functional data. Though motivated by the SHHS, the proposed methodology is generally applicable, with potential relevance to many modern scientific …

Nonparametric Signal Extraction And Measurement Error In The Analysis Of Electroencephalographic Activity During Sleep, Ciprian M. Crainiceanu, Brian S. Caffo, Chong-Zhi Di, Naresh M. Punjabi

Chongzhi Di

We introduce methods for signal and associated variability estimation based on hierarchical nonparametric smoothing with application to the Sleep Heart Health Study (SHHS). SHHS is the largest electroencephalographic (EEG) collection of sleep-related data, which contains, at each visit, two quasi-continuous EEG signals for each subject. The signal features extracted from EEG data are then used in second level analyses to investigate the relation between health, behavioral, or biometric outcomes and sleep. Using subject specific signals estimated with known variability in a second level regression becomes a nonstandard measurement error problem.We propose and implement methods that take into account cross-sectional and …

Generalized Multilevel Functional Regression, Ciprian M. Crainiceanu, Ana-Maria Staicu, Chong-Zhi Di

Chongzhi Di

We introduce Generalized Multilevel Functional Linear Models (GMFLMs), a novel statistical framework for regression models where exposure has a multilevel functional structure. We show that GMFLMs are, in fact, generalized multilevel mixed models. Thus, GMFLMs can be analyzed using the mixed effects inferential machinery and can be generalized within a well-researched statistical framework. We propose and compare two methods for inference: (1) a two-stage frequentist approach; and (2) a joint Bayesian analysis. Our methods are motivated by and applied to the Sleep Heart Health Study, the largest community cohort study of sleep. However, our methods are general and easy to …

R Codes For "Multilevel Functional Principal Component Analysis" (Aoas), Chongzhi Di

Chongzhi Di

No abstract provided.

Masw Tests For Detection Of Decayed Buried Timber Within Railway Embankments, Barry A. Palynchuk Phd, Chris Bunce Phd, Steve Sather M.Eng

Barry A. Palynchuk PhD

No abstract provided.

Predicting Hearing Threshold In Nonresponsive Subjects Using A Log-Normal Bayesian Linear Model In The Presence Of Left-Censored Covariates, Byron J. Gajewski, Nannette Nicholson, Judith E. Widen

Byron J Gajewski

We provide a nontrivial example illustrating analysis of a Bayesian clinical trial. Many of the issues discussed in the article are emphasized in a recent Food and Drug Administration (FDA) guidance on use of Bayesian statistics in medical device clinical trials. Here we present a fully Bayesian data analysis for predicting hearing thresholds in subjects who cannot respond to usual hearing tests. The article begins with simple concepts such as simple linear regression and proceeds into more complex issues such as censoring in the dependent and independent variables. Throughout, we emphasize the substantive interpretation of the analysis. Of particular interest …

A Critique Of The False-Positive Report Probability, Joseph Lucke

Joseph Lucke

The false positive report probability (FPRP) was proposed as a Bayesian prophylactic against false reports of significant associations. Unfortunately, the derivation of the FPRP is unsound. A heuristic derivation fails to make its point, and a formal derivation reveals a probabilistic misrepresentation of an observation. As a result, the FPRP can yield serious inferential errors. In particular, the FPRP can use an observation that is many times more likely under the null hypothesis than under the alternative to infer that the null hypothesis is far less probable than the alternative. Contrary to its intended purpose, the FPRP can promote false …

Balance Diagnostics For Comparing The Distribution Of Baseline Covariates Between Treatment Groups In Propensity-Score Matched Samples, Peter C. Austin

Peter Austin

The propensity score is a subject’s probability of treatment, conditional on observed baseline covariates. Conditional on the true propensity score, treated and untreated subjects have similar distributions of observed baseline covariates. Propensity-score matching is a popular method of using the propensity score in the medical literature. Using this approach, matched sets of treated and untreated subjects with similar values of the propensity score are formed. Inferences about treatment effect made using propensity-score matching are valid only if, in the matched sample, treated and untreated subjects have similar distributions of measured baseline covariates. In this paper we discuss the following methods …

A Quantitative Taqman Mgb Real-Time Polymerase Chain Reaction Based Assay For Detection Of The Causative Agent Of Crayfish Plague Aphanomyces Astaci, Torstein Tengs

Dr. Torstein Tengs

Here we present the development and first validation of a TaqMan minor groove binder (MGB) real-time polymerase chain reaction (RT-PCR) method for quantitative and highly specific detection of Aphanomyces astaci, the causative agent of crayfish plague. The assay specificity was experimentally assessed by testing against DNA representative of closely related oomycetes, and theoretically assessed by additional sequence similarity analyses comparing the primers and probe sequences to available sequences in EMBL/GenBank. The target of the assay is a 59 bp unique sequence motif of A. astaci found in the internal transcribed spacer 1 of the nuclear ribosomal gene cluster. A standard …