Statistics and Probability Commons^™

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) …

Innovationspotenzialanalyse Für Die Neuen Technologien Für Das Verwalten Und Analysieren Von Großen Datenmengen (Big Data Management), Volker Markl, Alexander Löser, Thomas Hoeren, Helmut Krcmar, Holmer Hemsen, Michael Schermann, Matthias Gottlieb, Christoph Buchmüller, Philip Uecker, Till Bitter

Faculty Book Gallery

Durch die Digitalisierung von Wirtschaft und Gesellschaft ist ein rasantes Anwachsen von Datenbeständen zu beobachten. In fast allen Unternehmenssowie Wissenschaftsbereichen werden bereits heute schon Unmengen an Daten erzeugt, deren Größe, Erfassungsgeschwindigkeit oder Heterogenität die Fähigkeiten gängiger Datenbanksoftwareprodukte zur Verwaltung und zur Analyse übersteigt. Dieses Phänomen, welches unter dem Schlagwort „Big Data“ popularisiert wurde, stellt eine große Chance für Unternehmen, Wissenschaft und Gesellschaft dar. Allerdings ergibt sich aufgrund der neuen Komplexität der Daten und Analysen eine Vielzahl an Herausforderungen technischer, wirtschaftlicher und rechtlicher Natur. Diese Studie analysiert die Chancen und Herausforderungen von Big Data insbesondere im Hinblick auf eine nachhaltige Wettbewerbsfä- …

Robust Regression Estimators When There Are Tied Values, Rand R. Wilcox, Florence Clark

Journal of Modern Applied Statistical Methods

It is well known that when using the ordinary least squares regression estimator, outliers among the dependent variable can result in relatively poor power. Many robust regression estimators have been derived that address this problem, but the bulk of the results assume that the dependent variable is continuous. It is demonstrated that when there are tied values, several robust regression estimators can perform poorly in terms of controlling the Type I error probability, even with a large sample size. The presence of tied values does not necessarily mean that they perform poorly, but there is the issue of whether there …

A Generalized Class Of Estimators For Finite Population Variance In Presence Of Measurement Errors, Prayas Sharma, Rajesh Singh

Journal of Modern Applied Statistical Methods

The problem of estimating the population variance is presented using auxiliary information in the presence of measurement errors. The estimators in this article use auxiliary information to improve efficiency and assume that measurement error is present both in study and auxiliary variable. A numerical study is carried out to compare the performance of the proposed estimator with other estimators and the variance per unit estimator in the presence of measurement errors.

Comparison Of Three Calculation Methods For A Bayesian Inference Of P(Π1 > Π2), Yohei Kawasaki, Asanao Shimokawa, Etsuo Miyaoka

Journal of Modern Applied Statistical Methods

In Bayesian inference, some researchers have examined the difference of binominal proportions using θ = P(π₁ > π₂ − Δ₀|X₁,X₂), where X_i denote binomial random variable with parameter π_i. An approximate method and the MCMC method are compared with an exact method for θ, and results of actual clinical trials using θ are presented.

Testing The Assumption Of Non-Differential Misclassification In Case-Control Studies, Tze-San Lee, Qin Hui

Journal of Modern Applied Statistical Methods

One of the not yet solved issues regarding the misclassification in case-control studies is whether the misclassification rates are the same for both cases and controls. Currently, a common practice is to assume that the rates are the same, that is, the non-differential misclassification assumption. However, it has been suspected that this assumption may not be valid in practical applications. Unfortunately, no test is available so far to test the validity of the non-differential misclassification assumption. A method is presented to test the validity of non-differential misclassification assumption in case-control studies with 2 × 2 tables when validation data are …

Akaike Information Criterion To Select The Parametric Detection Function For Kernel Estimator Using Line Transect Data, Omar Eidous, Samar Al-Salman

Journal of Modern Applied Statistical Methods

Among different candidate parametric detection functions, it is suggested to use Akaike Information Criterion (AIC) to select the most appropriate one of them to fit line transect data. Four different detection functions are considered in this paper. Two of them are taken to satisfy the shoulder condition assumption and the other two estimators do not satisfy this condition. Once the appropriate detection function is determined, it also can be used to select the smoothing parameter of the nonparametric kernel estimator. For a wide range of target densities, a simulation results show the reasonable and good performances of the …

Bayesian Joinpoint Regression Model For Childhood Brain Cancer Mortality, Ram C. Kafle, Netra Khanal, Chris P. Tsokos

Journal of Modern Applied Statistical Methods

The Bayesian approach of joinpoint regression is widely used to analyze trends in cancer mortality, incidence and survival data. The Bayesian joinpoint regression model was used to study the childhood brain cancer mortality rate and its average percentage change (APC) per year. Annual observed mortality counts of children ages 0-19 from 1969-2009 obtained from Surveillance Epidemiology and End Results (SEER) database of National Cancer Institute (NCI) were analyzed. It was assumed that death counts are probabilistically characterized by the Poisson distribution and they were modeled using log link function. Results were compared with the mortality trend obtained using joinpoint software …

Ordered Logit Regression Modeling Of The Self-Rated Health In Hawai‘I, With Comparisons To The Ols Model, Hosik Min

Journal of Modern Applied Statistical Methods

Despite the ordinal nature of Self-Rated Health (SRH) variable, logistic regression models or regression models have been used without adequate justification for these applications. It is shown that ordered-logit regression model is the appropriate statistical strategy to estimate SRH, whereas the Ordinary LeastSquares model leads to biased conclusions.

On Comparison Of Exponential And Hyperbolic Exponential Growth Models In Height/Diameter Increment Of Pines (Pinus Caribaea), S. O. Oyamakin, A. U. Chukwu, T. A. Bamiduro

Journal of Modern Applied Statistical Methods

A new tree growth model called the hyperbolic exponential nonlinear growth model is suggested. Its ability in model prediction was compared with the Malthus or exponential growth model an approach which mimicked the natural variability of heights/diameter increment with respect to age and therefore provides more realistic height/diameter predictions as demonstrated by the results of the Kolmogorov Smirnov test and Shapiro-Wilk test. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the Hyperbolic exponential nonlinear growth models better than the ordinary exponential growth model without violating …

Approximation Multivariate Distribution Of Main Indices Of Tehran Stock Exchange With Pair-Copula, G. Parham, A. Daneshkhah, O. Chatrabgoun

Journal of Modern Applied Statistical Methods

The multivariate distribution of five main indices of Tehran stock exchange is approximated using a pair-copula model. A vine graphical model is used to produce an n-dimensional copula. This is accomplished using a flexible copula called a minimum information (MI) copula as a part of pair-copula construction. Obtained results show that the achieved model has a good level of approximation.

On Some Properties Of A Heterogeneous Transfer Function Involving Symmetric Saturated Linear (Satlins) With Hyperbolic Tangent (Tanh) Transfer Functions, Christopher Godwin Udomboso

Journal of Modern Applied Statistical Methods

For transfer functions to map the input layer of the statistical neural network model to the output layer perfectly, they must lie within bounds that characterize probability distributions. The heterogeneous transfer function, SATLINS_TANH, is established as a Probability Distribution Function (p.d.f), and its mean and variance are shown.

Distribution Of The Ratio Of Normal And Rice Random Variables, Nayereh B. Khoolenjani, Kavoos Khorshidian

Journal of Modern Applied Statistical Methods

The ratio of independent random variables arises in many applied problems. The distribution of the ratio |X/Y| is studied when X and Y are independent Normal and Rice random variables, respectively. Ratios of such random variables have extensive applications in the analysis of noises in communication systems. The exact forms of probability density function (PDF), cumulative distribution function (CDF) and the existing moments are derived in terms of several special functions. As a special case, the PDF and CDF of the ratio of independent standard Normal and Rayleigh random variables have been obtained. Tabulations of associated percentage points …

Vol. 12, No. 2 (Full Issue), Jmasm Editors

Journal of Modern Applied Statistical Methods

No abstract provided.

Application Of The Rasch Model To Measure Five Dimensions Of Wellness In Community-Dwelling Older Adults, Kelley A. Strout Dr

Nursing Faculty Scholarship

Background and Purpose: Nurse researchers and practicing nurses need reliable and valid instruments to measure key clinical concepts. The purpose of this research was to develop an innovative method to measure dimensions of wellness among older adults. Method: A sample of 5,604 community-dwelling older adults was drawn from members of the COLLAGE consortium. The Wellness Assessment Tool (WEL) of the COLLAGE assessment system provided the data used to create the scores. Application of the Rasch analysis and Masters' partial credit method resulted in logit values for each item within the five dimensions of wellness as well as logit values for …

A Study On The Correlation Of Bivariate And Trivariate Normal Models, Maria Del Pilar Orjuela

FIU Electronic Theses and Dissertations

Suppose two or more variables are jointly normally distributed. If there is a common relationship between these variables it would be very important to quantify this relationship by a parameter called the correlation coefficient which measures its strength, and the use of it can develop an equation for predicting, and ultimately draw testable conclusion about the parent population.

This research focused on the correlation coefficient ρ for the bivariate and trivariate normal distribution when equal variances and equal covariances are considered. Particularly, we derived the maximum Likelihood Estimators (MLE) of the distribution parameters assuming all of them are unknown, and …

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 …

Diabetes Care Management During Cancer Treatment, Gregory R. Harper Md, Phd, Janelle M. Sharma Dnp, Crnp, Cara Habeck Rn, Cde, Cathy A. Coyne Phd, Mph, Hope Kincaid Mph, Cph, Roya Hamadani Mph, Ada M. Rivera Mba, Cph, Gretchen Perilli Md, Nicole R. Sully Do

Department of Family Medicine

No abstract provided.

Hierarchical Vector Auto-Regressive Models And Their Applications To Multi-Subject Effective Connectivity, Cristina Gorrostieta, Mark Fiecas, Hernando Ombao, Erin Burke, Steven Cramer

Mark Fiecas