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Full-Text Articles in Statistical Models

Depicting Estimates Using The Intercept In Meta-Regression Models: The Moving Constant Technique, Blair T. Johnson Dr., Tania B. Huedo-Medina Dr. Aug 2014

Depicting Estimates Using The Intercept In Meta-Regression Models: The Moving Constant Technique, Blair T. Johnson Dr., Tania B. Huedo-Medina Dr.

Blair T. Johnson

In any scientific discipline, the ability to portray research patterns graphically often aids greatly in interpreting a phenomenon. In part to depict phenomena, the statistics and capabilities of meta-analytic models have grown increasingly sophisticated. Accordingly, this article details how to move the constant in weighted meta-analysis regression models (viz. “meta-regression”) to illuminate the patterns in such models across a range of complexities. Although it is commonly ignored in practice, the constant (or intercept) in such models can be indispensible when it is not relegated to its usual static role. The moving constant technique makes possible estimates and confidence intervals at …


A General Framework For Infrastructure System Reliability Modelling And Analysis, Payam Mokhtarian, Mohammad-Reza Namazi-Rad, Tin Kin Ho, Mahmoud Efatmaneshnik Mar 2014

A General Framework For Infrastructure System Reliability Modelling And Analysis, Payam Mokhtarian, Mohammad-Reza Namazi-Rad, Tin Kin Ho, Mahmoud Efatmaneshnik

Payam Mokhtarian

An infrastructure system is inherently complex, with layers of both explicitly defined and hidden or subtle interfaces with other infrastructure systems and human users. High availability is desired, which implies stringent requirements on reliability and safety. Reliability analysis typically starts at component or sub-system level and aggregates through the system functional hierarchy. Because of the system complexity, incorporating occurrences of all possible interactions and scenarios is not always practical and failure data is often limited. Moreover, there are unobserved events among the sub-systems distributing either randomly or with temporal trend. To facilitate reliability analysis amid the complex environment and uncertain …


A Probabilistic Predictive Model For Residential Mobility In Australia, Mohammad-Reza Namazi-Rad, Nagesh Shukla, Albert Munoz, Payam Mokhtarian, Jun Ma Mar 2014

A Probabilistic Predictive Model For Residential Mobility In Australia, Mohammad-Reza Namazi-Rad, Nagesh Shukla, Albert Munoz, Payam Mokhtarian, Jun Ma

Payam Mokhtarian

Household relocation modelling is an integral part of the planning process as residential movements influence the demand for community facilities and services. Department of Families, Housing, Community Services and Indigenous Affairs (FaHCSIA) created the Household, Income and Labour Dynamics in Australia (HILDA) program to collect reliable longitudinal data on family and household dynamics. Socio-demographic information (such as general health situation and well-being, lifestyle changes, residential mobility, income and welfare dynamics, and labour market dynamics) is collected from the sampled individuals and households. The data shows that approximately 17% of Australian households and 13% of couple families in the HILDA sample …


From Amazon To Apple: Modeling Online Retail Sales, Purchase Incidence And Visit Behavior, Anastasios Panagiotelis, Michael S. Smith, Peter Danaher Dec 2013

From Amazon To Apple: Modeling Online Retail Sales, Purchase Incidence And Visit Behavior, Anastasios Panagiotelis, Michael S. Smith, Peter Danaher

Michael Stanley Smith

In this study we propose a multivariate stochastic model for website visit duration, page views, purchase incidence and the sale amount for online retailers. The model is constructed by composition from carefully selected distributions, and involves copula components. It allows for the strong nonlinear relationships between the sales and visit variables to be explored in detail, and can be used to construct sales predictions. The model is readily estimated using maximum likelihood, making it an attractive choice in practice given the large sample sizes that are commonplace in online retail studies. We examine a number of top-ranked U.S. online retailers, …


Spectral Density Shrinkage For High-Dimensional Time Series, Mark Fiecas, Rainer Von Sachs Dec 2013

Spectral Density Shrinkage For High-Dimensional Time Series, Mark Fiecas, Rainer Von Sachs

Mark Fiecas

Time series data obtained from neurophysiological signals is often high-dimensional and the length of the time series is often short relative to the number of dimensions. Thus, it is difficult or sometimes impossible to compute statistics that are based on the spectral density matrix because these matrices are numerically unstable. In this work, we discuss the importance of regularization for spectral analysis of high-dimensional time series and propose shrinkage estimation for estimating high-dimensional spectral density matrices. The shrinkage estimator is derived from a penalized log-likelihood, and the optimal penalty parameter has a closed-form solution, which can be estimated using the …