Statistics and Probability Commons^™

Progressive Reliability Method And Its Application To Offshore Mooring Systems, Mir Emad Mousavi, Paolo Gardoni, Mehdi Maadooliat

Mathematics, Statistics and Computer Science Faculty Research and Publications

Assessing the reliability of complex systems (e.g. structures) is essential for a reliability-based optimal design that balances safety and costs of such systems. This paper proposes the Progressive Reliability Method (PRM) for the quantification of the reliability of complex systems. The proposed method is a closed-form solution for calculating the probability of failure. The new method is flexible to the definition of “failure” (i.e., can consider serviceability and ultimate-strength failures) and uses the rules of probability theory to estimate the failure probability of the system or its components. The method is first discussed in general and then illustrated in two …

Assessing Protein Conformational Sampling Methods Based On Bivariate Lag-Distributions Of Backbone Angles, Mehdi Maadooliat, Xin Gao, Jianhua Z. Huang

Mathematics, Statistics and Computer Science Faculty Research and Publications

Despite considerable progress in the past decades, protein structure prediction remains one of the major unsolved problems in computational biology. Angular-sampling-based methods have been extensively studied recently due to their ability to capture the continuous conformational space of protein structures. The literature has focused on using a variety of parametric models of the sequential dependencies between angle pairs along the protein chains. In this article, we present a thorough review of angular-sampling-based methods by assessing three main questions: What is the best distribution type to model the protein angles? What is a reasonable number of components in a mixture model …

Observed Versus Gcm-Generated Local Tropical Cyclone Frequency: Comparisons Using A Spatial Lattice, Sarah Strazzo, Daniel J. Halperin, James Elsner, Tim Larow, Ming Zhao

Publications

Of broad scientific and public interest is the reliability of global climate models (GCMs) to simulate future regional and local tropical cyclone (TC) occurrences. Atmospheric GCMs are now able to generate vortices resembling actual TCs, but questions remain about their fidelity to observed TCs. Here the authors demonstrate a spatial lattice approach for comparing actual with simulated TC occurrences regionally using observed TCs from the International Best Track Archive for Climate Stewardship (IBTrACS) dataset and GCM-generated TCs from the Geophysical Fluid Dynamics Laboratory (GFDL) High Resolution Atmospheric Model (HiRAM) and Florida State University (FSU) Center for Ocean–Atmospheric Prediction Studies (COAPS) …

Mathematical Engineering And Control With Applications, Mamdouh M. El Kady, Martin Bohner, J. Liang, Mouffak Benchohra

Mathematics and Statistics Faculty Research & Creative Works

No abstract provided.

As Strong As The Weakest Link: Mining Diverse Cliques In Weighted Graphs, Petko Bogdanov, Ben Baumer, Prithwish Basu, Amotz Bar-Noy, Ambuj K. Singh

Statistical and Data Sciences: Faculty Publications

Mining for cliques in networks provides an essential tool for the discovery of strong associations among entities. Applications vary, from extracting core subgroups in team performance data arising in sports, entertainment, research and business; to the discovery of functional complexes in high-throughput gene interaction data. A challenge in all of these scenarios is the large size of real-world networks and the computational complexity associated with clique enumeration. Furthermore, when mining for multiple cliques within the same network, the results need to be diversified in order to extract meaningful information that is both comprehensive and representative of the whole dataset. We …

Revised Estimates Of World Wide Anemia, Kentron R. Wride, Dr. Gilbert W. Fellingham

Journal of Undergraduate Research

The stated mission of the World Health Organization (WHO) is to improve health around the world. One aspect of this mission involves preparing reliable models to describe patterns of health world wide. WHO has built a summary data file based on nearly 700 published and unpublished reports of anemia rates of women worldwide. Fellingham et. al (1996) prepared a preliminary report of the first model developed from this data as well as the resulting estimates of world wide anemia. The study was based on 448 records from 83 countries. The data included the mean hemoglobin concentration, sample size, a country …

Community College Consortium Promotes Open Educational Practices Through Outreach And Collaboration, Una T. Daly, Lisa Storm, Barbara Illowsky

SJSU Open Access Conference

The Community College Consortium for Open Educational Resources (CCCOER) is a community of practice focused on awareness and promoting best practices for OER discovery and adoption including open textbooks, open MOOCs, and open repositories to enhance learning and teaching. Through monthly outreach webinars with OER leaders and online advisory meetings, the community shares their projects and expertise encouraging collaboration across institutions, disciplines, and higher education sectors. Hear from the consortium director and two leaders of the community college OER movement.

• Una Daly, Director of Community College Outreach, OpenCourseWare Consortium. Building a community to promote awareness and shared knowledge of …

Hypothesis Testing For An Extended Cox Model With Time-Varying Coefficients, Takumi Saegusa, Chongzhi Di, Ying Qing Chen

UW Biostatistics Working Paper Series

The log-rank test has been widely used to test a treatment effect under the Cox model for censored time-to-event outcomes, though it may lose power substantially when the model's proportional hazards assumption does not hold. In this paper, we consider an extended Cox model that uses B-splines or smoothing splines to model a time-varying treatment effect and propose score test statistics for the treatment effect. Our proposed new tests combine statistical evidence from both the magnitude and the shape of the time-varying hazard ratio function, and thus are omnibus and powerful against various types of alternatives. In addition, the new …

Challenges In Estimating The Causal Effect Of An Intervention With Pre-Post Data (Part 1): Definition & Identification Of The Causal Parameter, Ann M. Weber, Mark J. Van Der Laan, Maya L. Petersen

U.C. Berkeley Division of Biostatistics Working Paper Series

There is mixed evidence of the effectiveness of interventions operating on a large scale. Although the lack of consistent results is generally attributed to problems of implementation or governance of the program, the failure to find a statistically significant effect (or the success of finding one) may be due to choices made in the evaluation. To demonstrate the potential limitations and pitfalls of the usual analytic methods used for estimating causal effects, we apply the first half of a roadmap for causal inference to a pre-post evaluation of a community-level, national nutrition program. Selection into the program was non-random and …

Variable Importance And Prediction Methods For Longitudinal Problems With Missing Variables, Ivan Diaz, Alan E. Hubbard, Anna Decker, Mitchell Cohen

U.C. Berkeley Division of Biostatistics Working Paper Series

In this paper we present prediction and variable importance (VIM) methods for longitudinal data sets containing both continuous and binary exposures subject to missingness. We demonstrate the use of these methods for prognosis of medical outcomes of severe trauma patients, a field in which current medical practice involves rules of thumb and scoring methods that only use a few variables and ignore the dynamic and high-dimensional nature of trauma recovery. Well-principled prediction and VIM methods can thus provide a tool to make care decisions informed by the high-dimensional patient’s physiological and clinical history. Our VIM parameters can be causally interpreted …

The Kalman Filter For Linear Systems On Time Scales, Martin Bohner, Nick Wintz

Mathematics and Statistics Faculty Research & Creative Works

We introduce the Kalman filter for linear systems on time scales, which includes the discrete and continuous versions as special cases. When the system is also stochastic, we show that the Kalman filter is an observer that estimates the system when the state is corrupted by noisy measurements. Finally, we show that the duality of the Kalman filter and the Linear Quadratic Regulator (LQR) is preserved in their unification on time scales. A numerical example is provided. © 2013 Elsevier Ltd.

Targeted Learning Of An Optimal Dynamic Treatment, And Statistical Inference For Its Mean Outcome, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Suppose we observe n independent and identically distributed observations of a time-dependent random variable consisting of baseline covariates, initial treatment and censoring indicator, intermediate covariates, subsequent treatment and censoring indicator, and a final outcome. For example, this could be data generated by a sequentially randomized controlled trial, where subjects are sequentially randomized to a first line and second line treatment, possibly assigned in response to an intermediate biomarker, and are subject to right-censoring. In this article we consider estimation of an optimal dynamic multiple time-point treatment rule defined as the rule that maximizes the mean outcome under the dynamic treatment, …

Sparse Median Graphs Estimation In A High Dimensional Semiparametric Model, Fang Han, Han Liu, Brian Caffo

Johns Hopkins University, Dept. of Biostatistics Working Papers

In this manuscript a unified framework for conducting inference on complex aggregated data in high dimensional settings is proposed. The data are assumed to be a collection of multiple non-Gaussian realizations with underlying undirected graphical structures. Utilizing the concept of median graphs in summarizing the commonality across these graphical structures, a novel semiparametric approach to modeling such complex aggregated data is provided along with robust estimation of the median graph, which is assumed to be sparse. The estimator is proved to be consistent in graph recovery and an upper bound on the rate of convergence is given. Experiments on both …

Growth Of Tropical Dasyatid Rays Estimated Using A Multi-Analytical Approach, Owen R. O'Shea, Matias Braccini, Rory Mcauley, Conrad W. Speed, Mark G. Meekan

Fisheries Research Articles

We studied the age and growth of four sympatric stingrays: reticulate whipray, Himanutra uarnak (n=19); blue mask, Neotrygon kuhlii (n=34); cowtail, Pastinachus atrus (n=32) and blue-spotted fantail, Taeniura lymma (n=40) rays at Ningaloo Reef, a fringing coral reef on the north-western coast of western Australia. Age estimates derived from band counts within sectioned vertebrae ranged between 1 and 27 years (H. uarnak, 1 - 25 yrs.; N. kuhlii, 1.5 - 13 yrs.; P. atrus, 1 - 27 yrs. and T. lymma, 1 -11 yrs.). Due to limitations of sample sizes, we combined several analytical methods …

Minkowski And Beckenbach-Dresher Inequalities And Functionals On Time Scales, Rabia Bibi, Martin Bohner, Josip Pečarić, Sanja Varǒsanec

Mathematics and Statistics Faculty Research & Creative Works

We obtain integral forms of the Minkowski inequality and Beckenbach-Dresher inequality on time scales. Also, we investigate a converse of Minkowski's inequality and several functionals arising from the Minkowski inequality and the Beckenbach-Dresher inequality. © ELEMENT, Zagreb.

Control Chart Development For The Coefficient Of Variation, Geraldine Madariaga, Dr. C. Shane Reese

Journal of Undergraduate Research

Industries use control charts to evaluate whether or not a process is “in control” or producing parts that meet the standards of quality. Control charts are based on the principle that variation between samples can be predicted based on sampling distributions. Parts are measured and the computed test statistic is plotted within limits that are based on the standard deviation or quantiles of the sampling distribution of the test statistic.

Adapting Data Adaptive Methods For Small, But High Dimensional Omic Data: Applications To Gwas/Ewas And More, Sara Kherad Pajouh, Alan E. Hubbard, Martyn T. Smith

U.C. Berkeley Division of Biostatistics Working Paper Series

Exploratory analysis of high dimensional "omics" data has received much attention since the explosion of high-throughput technology allows simultaneous screening of tens of thousands of characteristics (genomics, metabolomics, proteomics, adducts, etc., etc.). Part of this trend has been an increase in the dimension of exposure data in studies of environmental exposure and associated biomarkers. Though some of the general approaches, such as GWAS, are transferable, what has received less focus is 1) how to derive estimation of independent associations in the context of many competing causes, without resorting to a misspecified model, and 2) how to derive accurate small-sample inference …

Estimation Of Variation For High-Throughput Molecular Biological Experiments With Small Sample Size, Danni Yu

Open Access Dissertations

Motivation: In the quantification of molecular components, a large variation can affect and even potentially mislead the biological conclusions. Meanwhile, the high-throughput experiments often involve a small number of samples due to the limitation of cost and time. In such cases, the stochastic information may dominate the outcome of an experiment because there may not be enough samples to present the true biological information. It is challenging to distinguish the changes in phenotype from the stochastic variation.

Methods: Since the biological molecules have been quantified with different technologies, different statistical methods are required. Focusing on three types of important high-throughput …

Different Types Of Backward Bifurcations Due To Density-Dependent Treatments, Baojun Song, Wen Du, Jie Lou

Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works

A set of deterministic SIS models with density-dependent treatments are studied to understand the disease dynamics when different treatment strategies are applied. Qualitative analyses are carried out in terms of general treatment functions. It has become customary that a backward bifurcation leads to bistable dynamics. However, this study finds that finds that bistability may not be an option at all; the disease-free equilibrium could be globally stable when there is a backward bifurcation. Furthermore, when a backward bifurcation occurs, the fashion of bistability could be the coexistence of either dual stable equilibria or the disease-free equilibrium and a stable limit …

The Spatial Distribution Of Cancer Incidence In Fars Province: A Gis-Based Analysis Of Cancer Registry Data, Ali Goli, Mahbobeh Oroei, Mehdi Jalalpour, Hossein Faramarzi, Mehrdad Askarian

Civil and Environmental Engineering Faculty Publications

Background: Cancer is a major health problem in the developing countries. Variations of its incidence rate among geographical areas are due to various contributing factors. This study was performed to assess the spatial patterns of cancer incidence in the Fars Province, based on cancer registry data and to determine geographical clusters.

Methods: In this cross sectional study, the new cases of cancer were recorded from 2001 to 2009. Crude incidence rate was estimated based on age groups and sex in the counties of the Fars Province. Age standardized incidence rates (ASR) per 100,000 was calculated in each year. …