Statistics and Probability Commons^™

Defeatism Defeated, Max Baker-Hytch, Matthew A. Benton

SPU Works

Many epistemologists are enamored with a defeat condition on knowledge. In this paper we present some implementation problems for defeatism, understood along either internalist or externalist lines. We then propose that one who accepts a knowledge norm of belief, according to which one ought to believe only what one knows, can explain away much of the motivation for defeatism. This is an important result, because on the one hand it respects the plausibility of the intuitions about defeat shared by many in epistemology; but on the other hand, it obviates the need to provide a unified account of defeat which …

Spin Glass Reflection Of The Decoding Transition For Quantum Error Correcting Codes, Alexey Kovalev, Leonid P. Pryadko

Department of Physics and Astronomy: Faculty Publications

We study the decoding transition for quantum error correcting codes with the help of a mapping to random-bond Wegner spin models. Families of quantum low density parity-check (LDPC) codes with a finite decoding threshold lead to both known models (e.g., random bond Ising and random plaquette Z₂ gauge models) as well as unexplored earlier generally non-local disordered spin models with non-trivial phase diagrams. The decoding transition corresponds to a transition from the ordered phase by proliferation of "post-topological" extended defects which generalize the notion of domain walls to non-local spin models. In recently discovered quantum LDPC code families with …

The Role Of Citizens In Detecting And Responding To A Rapid Marine Invasion, Steven B. Scyphers, Sean P. Powers, J. Lad Akins, J. Marcus Drymon, Charles W. Martin, Zeb H. Schobernd, Pamela J. Schofield, Robert L. Shipp, Theodore S. Switzer

University Faculty and Staff Publications

Documenting and responding to species invasions requires innovative strategies that account for ecological and societal complexities. We used the recent expansion of Indo-Pacific lionfish (Pterois volitans/miles) throughout northern Gulf of Mexico coastal waters to evaluate the role of stakeholders in documenting and responding to a rapid marine invasion. We coupled an online survey of spearfishers and citizen science monitoring programs with traditional fishery-independent data sources and found that citizen observations documented lionfish 1–2 years earlier and more frequently than traditional reef fish monitoring programs. Citizen observations first documented lionfish in 2010 followed by rapid expansion and proliferation in …

Association Between Respiratory Syncytial Virus Activity And Pneumococcal Disease In Infants: A Time Series Analysis Of Us Hospitalization Data., Daniel M. Weinberger, Keith P. Klugman, Claudia A. Steiner, Lone Simonsen, Cécile Viboud

Epidemiology Faculty Publications

BACKGROUND:

The importance of bacterial infections following respiratory syncytial virus (RSV) remains unclear. We evaluated whether variations in RSV epidemic timing and magnitude are associated with variations in pneumococcal disease epidemics and whether changes in pneumococcal disease following the introduction of seven-valent pneumococcal conjugate vaccine (PCV7) were associated with changes in the rate of hospitalizations coded as RSV.

METHODS AND FINDINGS:

We used data from the State Inpatient Databases (Agency for Healthcare Research and Quality), including >700,000 RSV hospitalizations and >16,000 pneumococcal pneumonia hospitalizations in 36 states (1992/1993-2008/2009). Harmonic regression was used to estimate the timing of the average seasonal …

Genomic-Enabled Prediction Of Ordinal Data With Bayesian Logistic Ordinal Regression, Osval A. Montesinos-López, Abelardo Montesinos-López, José Crossa, Juan Burgueño, Kent M. Eskridge

Department of Statistics: Faculty Publications

Most genomic-enabled prediction models developed so far assume that the response variable is continuous and normally distributed. The exception is the probit model, developed for ordered categorical phenotypes. In statistical applications, because of the easy implementation of the Bayesian probit ordinal regression (BPOR) model, Bayesian logistic ordinal regression (BLOR) is implemented rarely in the context of genomic-enabled prediction [sample size (n) is much smaller than the number of parameters (p)]. For this reason, in this paper we propose a BLOR model using the Pólya-Gamma data augmentation approach that produces a Gibbs sampler with similar full conditional distributions of the BPORmodel …

Establishment And Persistence Of Yellow-Flowered Alfalfa No-Till Interseeded Into Crested Wheatgrass Stands, Christopher G. Misar, Lan Xu, Roger N. Gates, Arvid Boe, Patricia S. Johnson, Christopher S. Schauer, John R. Rickertsen, Walter Stroup

Department of Statistics: Faculty Publications

Crested wheatgrass [Agropyron cristatum (L.) Gaertn., A. desertorum

(Fisch. ex Link) Schult., and related taxa] often exists

in near monoculture stands in the northern Great Plains.

Introducing locally adapted yellow-flowered alfalfa [Medicago

sativa L. subsp. falcata (L.) Arcang.] would complement crested

wheatgrass. Our objective was to evaluate effects of seeding

date, clethodim {(E) -2-[1-[[(3-chloro-2-propenyl)oxy]imino]

propyl]-5-[2-(ethylthio)propyl]-3-hydroxy-2-cyclohexen-1-one}

sod suppression, and seeding rate on initial establishment and

stand persistence of Falcata, a predominantly yellow-flowered

alfalfa, no-till interseeded into crested wheatgrass. Research was

initiated in August 2008 at Newcastle, WY; Hettinger, ND;

Fruitdale, SD; and Buffalo, SD. Effects of treatment …

Effect Of Dexamethasone Prodrug On Inflamed Temporomandibular Joints In Juvenile Rats, Mitchell Knudsen, Matthew Bury, Callie Holwegner, Adam L. Reinhardt, Fang Yuan, Yijia Zhang, Peter Giannini, D. B. Marx, Dong Wang, Richard A. Reinhardt

Department of Statistics: Faculty Publications

Introduction: Juvenile idiopathic arthritis (JIA) often causes inflammation of the temporomandibular joint (TMJ) and has been treated with both systemic and intra-articular steroids, with concerns about effects on growing bones. In this study, we evaluated the impact of a macromolecular prodrug of dexamethasone (P-DEX) with inflammation-targeting potential applied systemically or directly to the TMJ.

Methods: Joint inflammation was initiated by injecting two doses of complete Freund’s adjuvant (CFA) at 1-month intervals into the right TMJs of 24 growing Sprague–Dawley male rats (controls on left side). Four additional rats were not manipulated. With the second CFA injection, animals received (1) 5 …

Threshold Models For Genome-Enabled Prediction Of Ordinal Categorical Traits In Plant Breeding, Osval A. Montesinos-López, Abelardo Montesinos-López, Paulino Pérez-Rodríguez, Gustavo De Los Campos, Kent M. Eskridge, José Crossa

Department of Statistics: Faculty Publications

Categorical scores for disease susceptibility or resistance often are recorded in plant breeding. The aim of this study was to introduce genomic models for analyzing ordinal characters and to assess the predictive ability of genomic predictions for ordered categorical phenotypes using a threshold model counterpart of the Genomic Best Linear Unbiased Predictor (i.e., TGBLUP). The threshold model was used to relate a hypothetical underlying scale to the outward categorical response. We present an empirical application where a total of nine models, five without interaction and four with genomic x environment interaction (G·E) and genomic additive x additive x environment interaction …

Measuring Peer Socialization For Adolescent Substance Use:A Comparison Of Perceived And Actual Friends’ Substance Use Effects, Arielle R. Deutsch, Pavel Chernyavskiy, Douglas Steinley, Wendy S. Slutske

Department of Statistics: Faculty Publications

Objective: There has been an increase in the use of social network analysis in studies of peer socialization effects on adolescent substance use. Some researchers argue that social network analyses provide more accurate measures of peer substance use, that the alternate strategy of assessing perceptions of friends’ drug use is biased, and that perceptions of peer use and actual peer use represent different constructs. However, there has been little research directly comparing the two effects, and little is known about the extent to which the measures differ in the magnitude of their influence on adolescent substance use, as well as …

A Copula Based Approach For Design Of Multivariate Random Forests For Drug Sensitivity Prediction, Saad Haider, Raziur Rahman, Souparno Ghosh, Ranadip Pal

Department of Statistics: Faculty Publications

Modeling sensitivity to drugs based on genetic characterizations is a significant challenge in the area of systems medicine. Ensemble based approaches such as Random Forests have been shown to perform well in both individual sensitivity prediction studies and team science based prediction challenges. However, Random Forests generate a deterministic predictive model for each drug based on the genetic characterization of the cell lines and ignores the relationship between different drug sensitivities during model generation. This application motivates the need for generation of multivariate ensemble learning techniques that can increase prediction accuracy and improve variable importance ranking by incorporating the relationships …

Design Of Probabilistic Random Forests With Applications To Anticancer Drug Sensitivity Prediction, Raziur Rahman, Saad Haider, Souparno Gosh, Ranadip Pal

Department of Statistics: Faculty Publications

Random forests consisting of an ensemble of regression trees with equal weights are frequently used for design of predictive models. In this article, we consider an extension of the methodology by representing the regression trees in the form of probabilistic trees and analyzing the nature of heteroscedasticity. The probabilistic tree representation allows for analytical computation of confidence intervals (CIs), and the tree weight optimization is expected to provide stricter CIs with comparable performance in mean error. We approached the ensemble of probabilistic trees’ prediction from the perspectives of a mixture distribution and as a weighted sum of correlated random variables. …

S1: Supplementary Information For Article: A Copula Based Approach For Design Of Multivariate Random Forests For Drug Sensitivity Prediction, Saad Haider, Raziur Rahman, Souparno Ghosh, Ranadip Pal

Department of Statistics: Faculty Publications

Changes in performance with prior feature selection

Random forest (RF) is designed to create uncorrelated trees using random subsets of features in each node of each tree. RF by itself is a great tool for feature selection from a high dimensional set of features. But we observed that the prediction accuracy is improved when a prior feature selection (RELIEFF) [1] approach is implemented. Table A shows the performance of RF, VMRF and CMRF with and without RELIEFF feature selection in 2 drug sets of GDSC.

Performance Analysis for drugsets consisting of more 8 than two drugs

We have generated empirical …

Bounded, Asymptotically Stable, And L^1 Solutions Of Caputo Fractional Differential Equations, Muhammad Islam

Mathematics Faculty Publications

The existence of bounded solutions, asymptotically stable solutions, and L¹ solutions of a Caputo fractional differential equation has been studied in this paper. The results are obtained from an equivalent Volterra integral equation which is derived by inverting the fractional differential equation. The kernel function of this integral equation is weakly singular and hence the standard techniques that are normally applied on Volterra integral equations do not apply here. This hurdle is overcomed using a resolvent equation and then applying some known properties of the resolvent. In the analysis Schauder's fixed point theorem and Liapunov's method have been employed. …

Bayesian Change-Point Analysis In Linear Regression Model With Scale Mixtures Of Normal Distributions, Shuaimin Kang

Dissertations, Master's Theses and Master's Reports - Open

In this thesis, we consider Bayesian inference on the detection of variance change-point models with scale mixtures of normal (for short SMN) distributions. This class of distributions is symmetric and thick-tailed and includes as special cases: Gaussian, Student-t, contaminated normal, and slash distributions. The proposed models provide greater flexibility to analyze a lot of practical data, which often show heavy-tail and may not satisfy the normal assumption.

As to the Bayesian analysis, we specify some prior distributions for the unknown parameters in the variance change-point models with the SMN distributions. Due to the complexity of the joint posterior …

Variable Selection With False Discovery Control, Kevin He, Yanming Li, Ji Zhu, Hongliang Liu, Jeffrey E. Lee, Christopher I. Amos, Terry Hyslop, Jiashun Jin, Qinyi Wei, Yi Li

The University of Michigan Department of Biostatistics Working Paper Series

Technological advances that allow routine identification of high-dimensional risk factors have led to high demand for statistical techniques that enable full utilization of these rich sources of information for genome-wide association studies (GWAS). Variable selection for censored outcome data as well as control of false discoveries (i.e. inclusion of irrelevant variables) in the presence of high-dimensional predictors present serious challenges. In the context of survival analysis with high-dimensional covariates, this paper develops a computationally feasible method for building general risk prediction models, while controlling false discoveries. We have proposed a high-dimensional variable selection method by incorporating stability selection to control …

Tests For Gene-Environment Interactions And Joint Effects With Exposure Misclassification, Philip S. Boonstra, Bhramar Mukherjee, Stephen B. Gruber, Jaeil Ahn, Stephanie L. Schmit, Nilanjan Chatterjee

The University of Michigan Department of Biostatistics Working Paper Series

The number of methods for genome-wide testing of gene-environment interactions (GEI) continues to increase with the hope of discovering new genetic risk factors and obtaining insight into the disease-gene-environment relationship. The relative performance of these methods based on family-wise type 1 error rate and power depends on underlying disease-gene-environment associations, estimates of which may be biased in the presence of exposure misclassification. This simulation study expands on a previously published simulation study of methods for detecting GEI by evaluating the impact of exposure misclassification. We consider seven single step and modular screening methods for identifying GEI at a genome-wide level …

Voc Emissions From Beef Feedlot Pen Surfaces As Affected By Within-Pen Location, Moisture And Temperature, Bryan L. Woodbury, John E. Gilley, David B. Parker, David B. Marx, Roger A. Eigenberg

Department of Statistics: Faculty Publications

A laboratory study was conducted to evaluate the effects of pen location, moisture, and temperature on emissions of volatile organic compounds (VOC) from surface materials obtained from feedlot pens where beef cattle were fed a diet containing 30% wet distillers grain plus solubles. Surface materials were collected from the feed trough (bunk), drainage, and raised areas (mounds) within three feedlot pens. The surface materials were mixed with water to represent dry, wet, or saturated conditions and then incubated at temperatures of 5, 15, 25 and 35 C. A wind tunnel and gas chromatograph-mass spectrometer were used to collect and quantify …

The Support Vector Machine And Mixed Integer Linear Programming: Ramp Loss Svm With L1-Norm Regularization, Eric J. Hess, J. Paul Brooks

Statistical Sciences and Operations Research Publications

The support vector machine (SVM) is a flexible classification method that accommodates a kernel trick to learn nonlinear decision rules. The traditional formulation as an optimization problem is a quadratic program. In efforts to reduce computational complexity, some have proposed using an L1-norm regularization to create a linear program (LP). In other efforts aimed at increasing the robustness to outliers, investigators have proposed using the ramp loss which results in what may be expressed as a quadratic integer programming problem (QIP). In this paper, we consider combining these ideas for ramp loss SVM with L1-norm regularization. The result is four …

Firing Rate Dynamics In Recurrent Spiking Neural Networks With Intrinsic And Network Heterogeneity, Cheng Ly

Statistical Sciences and Operations Research Publications

Heterogeneity of neural attributes has recently gained a lot of attention and is increasing recognized as a crucial feature in neural processing. Despite its importance, this physiological feature has traditionally been neglected in theoretical studies of cortical neural networks. Thus, there is still a lot unknown about the consequences of cellular and circuit heterogeneity in spiking neural networks. In particular, combining network or synaptic heterogeneity and intrinsic heterogeneity has yet to be considered systematically despite the fact that both are known to exist and likely have significant roles in neural network dynamics. In a canonical recurrent spiking neural network model, …

Ua56/1 Fact Book, Wku Institutional Research

WKU Administration Documents

Statistical and demographic profile of WKU.