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Fast Function-On-Scalar Regression With Penalized Basis Expansions, Philip T. Reiss, Lei Huang, Maarten Mennes 2009 New York University

Fast Function-On-Scalar Regression With Penalized Basis Expansions, Philip T. Reiss, Lei Huang, Maarten Mennes

Lei Huang

Regression models for functional responses and scalar predictors are often fitted by means of basis functions, with quadratic roughness penalties applied to avoid overfitting. The fitting approach described by Ramsay and Silverman in the 1990s amounts to a penalized ordinary least squares (P-OLS) estimator of the coefficient functions. We recast this estimator as a generalized ridge regression estimator, and present a penalized generalized least squares (P-GLS) alternative. We describe algorithms by which both estimators can be implemented, with automatic selection of optimal smoothing parameters, in a more computationally efficient manner than has heretofore been available. We discuss pointwise confidence intervals ...


On K4 Of The Gaussian And Eisenstein Integers, Mathieu Dutour Sikiric, Herbert Gangl, Paul Gunnells, Jonathan Hanke, Achill Schürmann, Dan Yasaki 2009 University of Massachusetts - Amherst

On K4 Of The Gaussian And Eisenstein Integers, Mathieu Dutour Sikiric, Herbert Gangl, Paul Gunnells, Jonathan Hanke, Achill Schürmann, Dan Yasaki

Paul Gunnells

Abstract. In this paper we investigate the structure of the algebraic K-groups K4(Z[i]) and K4(Z[ρ]), where i := √ −1 and ρ := (1 + √ −3)/2. We exploit the close connection between homology groups of GLn(R) for n 6 5 and those of related classifying spaces, then compute the former using Voronoi’s reduction theory of positive definite quadratic and Hermitian forms to produce a very large finite cell complex on which GLn(R) acts. Our main results are (i) K4(Z[i]) is a finite abelian 3-group, and (ii) K4(Z[ρ]) is trivial.


A Prospective Cohort Study Of Modifiable Risk Factors For Gestational Diabetes Among Hispanic Women: Design And Baseline Characteristics, Lisa Chasen-Taber, R. T. Fortner, A. Gollenberg, John Buonaccorsi, N. Dole, G. Markenson 2009 University of Massachusetts - Amherst

A Prospective Cohort Study Of Modifiable Risk Factors For Gestational Diabetes Among Hispanic Women: Design And Baseline Characteristics, Lisa Chasen-Taber, R. T. Fortner, A. Gollenberg, John Buonaccorsi, N. Dole, G. Markenson

John Buonaccorsi

OBJECTIVES: Women diagnosed with gestational diabetes mellitus (GDM) are at high risk for future diabetes, with rates of GDM consistently higher in Hispanic than non-Hispanic white women. Currently recognized risk factors for GDM are absent in up to half of affected women, and studies addressing modifiable risk factors for GDM in Hispanic women are sparse. METHODS: Proyecto Buena Salud is an ongoing prospective cohort study of Hispanic women in Massachusetts designed to assess physical activity, psychosocial stress, and GDM risk. Bilingual interviewers recruit prenatal care patients early in pregnancy and assess activity, trait anxiety, perceived stress, and depressive symptoms using ...


Gibbs Sampling For A Bayesian Hierarchical General Linear Model, Alicia A. Johnson, Galin L. Jones 2009 University of Minnesota - Twin Cities

Gibbs Sampling For A Bayesian Hierarchical General Linear Model, Alicia A. Johnson, Galin L. Jones

Alicia A. Johnson

No abstract provided.


The 1905 Einstein Equation In A General Mathematical Analysis Model Of Quasars, Byron E. Bell 2009 DePaul University and Columbia College Chicago

The 1905 Einstein Equation In A General Mathematical Analysis Model Of Quasars, Byron E. Bell

Byron E. Bell

No abstract provided.


How A Bayesian Might Estimate The Distribution Of Cronbach’S Alpha From Ordinal-Dynamic Scaled Data A Case Study Measuring Nursing Home Resident Quality Of Life, Byron J. Gajewski, Diane K. Boyle, Sarah Thompson 2009 University of Kansas Medical Center

How A Bayesian Might Estimate The Distribution Of Cronbach’S Alpha From Ordinal-Dynamic Scaled Data A Case Study Measuring Nursing Home Resident Quality Of Life, Byron J. Gajewski, Diane K. Boyle, Sarah Thompson

Diane Kay Boyle PhD, RN, FAAN

We demonstrate the utility of a Bayesian based approach for calculating intervals of Cronbach’s alpha from a psychological instrument having ordinal responses with a dynamic scale. A small number of response options on an instrument will cause traditional-based interval estimates to be biased. Ordinal-based solutions are problematic because there is no clear mechanism for handling the dynamic scale. One way to remedy the bias is to adjust with a Bayesian approach. The Bayesian approach adjusts the bias and allows theoretically simple calculations of Cronbach’s alpha and intervals. We demonstrate the calculations of the Bayesian approach while at the ...


Statistical Modeling Of Agatston Score In Multi-Ethnic Study Of Atherosclerosis (Mesa), Anna Liu, S. Ma, J. Carr, W. Post, R. Kronmal 2009 University of Massachusetts - Amherst

Statistical Modeling Of Agatston Score In Multi-Ethnic Study Of Atherosclerosis (Mesa), Anna Liu, S. Ma, J. Carr, W. Post, R. Kronmal

Anna Liu

The MESA (Multi-Ethnic Study of Atherosclerosis) is an ongoing study of the prevalence, risk factors, and progression of subclinical cardiovascular disease in a multi-ethnic cohort. It provides a valuable opportunity to examine the development and progression of CAC (coronary artery calcium), which is an important risk factor for the development of coronary heart disease. In MESA, about half of the CAC scores are zero and the rest are continuously distributed. Such data has been referred to as “zero-inflated data” and may be described using two-part models. Existing two-part model studies have limitations in that they usually consider parametric models only ...


Bayesian Inference For A Periodic Stochastic Volatility Model Of Intraday Electricity Prices, Michael S. Smith 2009 Melbourne Business School

Bayesian Inference For A Periodic Stochastic Volatility Model Of Intraday Electricity Prices, Michael S. Smith

Michael Stanley Smith

The Gaussian stochastic volatility model is extended to allow for periodic autoregressions (PAR) in both the level and log-volatility process. Each PAR is represented as a first order vector autoregression for a longitudinal vector of length equal to the period. The periodic stochastic volatility model is therefore expressed as a multivariate stochastic volatility model. Bayesian posterior inference is computed using a Markov chain Monte Carlo scheme for the multivariate representation. A circular prior that exploits the periodicity is suggested for the log-variance of the log-volatilities. The approach is applied to estimate a periodic stochastic volatility model for half-hourly electricity prices ...


Bayesian Skew Selection For Multivariate Models, Michael S. Smith, Anastasios Panagiotelis 2009 Melbourne Business School

Bayesian Skew Selection For Multivariate Models, Michael S. Smith, Anastasios Panagiotelis

Michael Stanley Smith

We develop a Bayesian approach for the selection of skew in multivariate skew t distributions constructed through hidden conditioning in the manners suggested by either Azzalini and Capitanio (2003) or Sahu, Dey and Branco~(2003). We show that the skew coefficients for each margin are the same for the standardized versions of both distributions. We introduce binary indicators to denote whether there is symmetry, or skew, in each dimension. We adopt a proper beta prior on each non-zero skew coefficient, and derive the corresponding prior on the skew parameters. In both distributions we show that as the degrees of freedom ...


Existence Of Traveling Wave Solutions For A Nonlocal Reaction-Diffusion Model Of Influenza A Drift, Joaquin Riviera, Yi Li 2009 Wright State University - Main Campus

Existence Of Traveling Wave Solutions For A Nonlocal Reaction-Diffusion Model Of Influenza A Drift, Joaquin Riviera, Yi Li

Yi Li

In this paper we discuss the existence of traveling wave solutions for a nonlocal reaction-diffusion model of Influenza A proposed in Lin et. al. (2003). The proof for the existence of the traveling wave takes advantage of the different time scales between the evolution of the disease and the progress of the disease in the population. Under this framework we are able to use the techniques from geometric singular perturbation theory to prove the existence of the traveling wave.


On The Statistical Accuracy Of Biomarker Assays Of Hiv Incidence, Ron Brookmeyer 2009 University of California, Los Angeles

On The Statistical Accuracy Of Biomarker Assays Of Hiv Incidence, Ron Brookmeyer

Ron Brookmeyer

Objective: To evaluate the statistical accuracy of estimates of current HIV incidence rates from cross-sectional surveys, and to identify characteristics of assays that improve accuracy.

Methods: Performed mathematical and statistical analysis of the cross-sectional estimator of HIV incidence to evaluate bias and variance. Developed probability models to evaluate impact of long tails of the window period distribution on accuracy.

Results: The standard cross-sectional estimate of HIV incidence rate is estimating a time-lagged incidence where the lag time, called the shadow, depends on the mean and the coefficient of variation of window periods. Equations show how the shadow increases with the ...


Using Twitter Hash Tags To Demonstrate Basic Concepts From Network Analysis, Matt Bogard 2009 Western Kentucky University

Using Twitter Hash Tags To Demonstrate Basic Concepts From Network Analysis, Matt Bogard

Matt Bogard

Social Network Analysis focuses on finding patterns in interactions between people or entities. These patterns may be described in the form of a network. Network analysis in general has many applications including models of student integration and persistence, business to business supply chains, terrorist cells, or analysis of social media such as Facebook and Twitter. This presentation provides a reference for basic concepts from social network analysis with examples using tweets from Twitter.


The Journey To Safety: Conflict-Driven Migration Flows In Colombia, Gianfranco Piras, Nancy Lozano-Gracia, Geoffrey Hewings, Ana Maria Ibanez 2009 Regional Research Institute, West Virginia University

The Journey To Safety: Conflict-Driven Migration Flows In Colombia, Gianfranco Piras, Nancy Lozano-Gracia, Geoffrey Hewings, Ana Maria Ibanez

Gianfranco Piras

No abstract provided.


A New Perspective On Visual Word Processing Efficiency, Joseph W. Houpt, James T. Townsend 2009 Wright State University - Main Campus

A New Perspective On Visual Word Processing Efficiency, Joseph W. Houpt, James T. Townsend

Joseph W. Houpt

As a fundamental part of our daily lives, visual word processing has received much attention in the psychological literature. Despite the well established perceptual advantages of word and pseudoword context using accuracy, a comparable effect using response times has been elusive. Some researchers continue to question whether the advantage due to word context is perceptual. We use the capacity coefficient, a well established, response time based measure of efficiency to provide evidence of word processing as a particularly efficient perceptual process to complement those results from the accuracy domain.


Semiparametric Analysis Of Recurrent Events: Artificial Censoring, Truncation, Pairwise Estimation And Inference, Debashis Ghosh 2009 Penn State University

Semiparametric Analysis Of Recurrent Events: Artificial Censoring, Truncation, Pairwise Estimation And Inference, Debashis Ghosh

Debashis Ghosh

The analysis of recurrent failure time data from longitudinal studies can be complicated by the presence of dependent censoring. There has been a substantive literature that has developed based on an artificial censoring device. We explore in this article the connection between this class of methods with truncated data structures. In addition, a new procedure is developed for estimation and inference in a joint model for recurrent events and dependent censoring. Estimation proceeds using a mixed U-statistic based estimating function approach. New resampling-based methods for variance estimation and model checking are also described. The methods are illustrated by application to ...


Fast Function-On-Scalar Regression With Penalized Basis Expansions, Philip T. Reiss, Lei Huang, Maarten Mennes 2009 New York University

Fast Function-On-Scalar Regression With Penalized Basis Expansions, Philip T. Reiss, Lei Huang, Maarten Mennes

Philip T. Reiss

Regression models for functional responses and scalar predictors are often fitted by means of basis functions, with quadratic roughness penalties applied to avoid overfitting. The fitting approach described by Ramsay and Silverman in the 1990s amounts to a penalized ordinary least squares (P-OLS) estimator of the coefficient functions. We recast this estimator as a generalized ridge regression estimator, and present a penalized generalized least squares (P-GLS) alternative. We describe algorithms by which both estimators can be implemented, with automatic selection of optimal smoothing parameters, in a more computationally efficient manner than has heretofore been available. We discuss pointwise confidence intervals ...


Patent Reforms Must Focus On The U.S. Patent Office, Ron D. Katznelson 2009 Bi-Level Technologies

Patent Reforms Must Focus On The U.S. Patent Office, Ron D. Katznelson

Ron D. Katznelson

No abstract provided.


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