Statistical Models Commons^™

Inversion Copulas From Nonlinear State Space Models With An Application To Inflation Forecasting, Michael S. Smith, Worapree Ole Maneesoonthorn

Michael Stanley Smith

Variational Bayes Estimation Of Discrete-Margined Copula Models With Application To Ime Series, Ruben Loaiza-Maya, Michael S. Smith

Michael Stanley Smith

Implementing Propensity Score Matching With Network Data: The Effect Of Gatt On Bilateral Trade, Luca De Benedictis, Bruno Arpino, Alessandra Mattei

Luca De Benedictis

Shining A Light On A University Special Collection With Data Visualization, Lisa Deluca, Katie M. Wissel

Kathryn Wissel, MBA, MI

Predicting Financial Distress: A Comparison Of Survival Analysis And Decision Tree Techniques, Adrian Gepp, Kuldeep Kumar

Adrian Gepp

Financial distress and then the consequent failure of a business is usually an extremely costly and disruptive event. Statistical financial distress prediction models attempt to predict whether a business will experience financial distress in the future. Discriminant analysis and logistic regression have been the most popular approaches, but there is also a large number of alternative cutting - edge data mining techniques that can be used. In this paper, a semi-parametric Cox survival analysis model and non-parametric CART decision trees have been applied to financial distress prediction and compared with each other as well as the most popular approaches. This …

An Outlier Robust Block Bootstrap For Small Area Estimation, Payam Mokhtarian, Ray Chambers

Payam Mokhtarian

Small area inference based on mixed models, i.e. models that contain both fixed and random effects, are the industry standard for this field, allowing between area heterogeneity to be represented by random area effects. Use of the linear mixed model is ubiquitous in this context, with maximum likelihood, or its close relative, REML, the standard method for estimating the parameters of this model. These parameter estimates, and in particular the resulting predicted values of the random area effects, are then used to construct empirical best linear unbiased predictors (EBLUPs) of the unknown small area means. It is now well known …

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

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

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, …

Time Series, Unit Roots, And Cointegration: An Introduction, Lonnie K. Stevans

Lonnie K. Stevans

The econometric literature on unit roots took off after the publication of the paper by Nelson and Plosser (1982) that argued that most macroeconomic series have unit roots and that this is important for the analysis of macroeconomic policy. Yule (1926) suggested that regressions based on trending time series data can be spurious. This problem of spurious correlation was further pursued by Granger and Newbold (1974) and this also led to the development of the concept of cointegration (lack of cointegration implies spurious regression). The pathbreaking paper by Granger (1981), first presented at a conference at the University of Florida …

Bicycle Commuting In Melbourne During The 2000s Energy Crisis: A Semiparametric Analysis Of Intraday Volumes, Michael S. Smith, Goeran Kauermann

Michael Stanley Smith

Cycling is attracting renewed attention as a mode of transport in western urban environments, yet the determinants of usage are poorly understood. In this paper we investigate some of these using intraday bicycle volumes collected via induction loops located at ten bike paths in the city of Melbourne, Australia, between December 2005 and June 2008. The data are hourly counts at each location, with temporal and spatial disaggregation allowing for the impact of meteorology to be measured accurately for the first time. Moreover, during this period petrol prices varied dramatically and the data also provide a unique opportunity to assess …

Men In Black: The Impact Of New Contracts On Football Referees’ Performances, Babatunde Buraimo, Alex Bryson, Rob Simmons

Dr Babatunde Buraimo

No abstract provided.

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

Byron E. Bell

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

Byron E. Bell

No abstract provided.

A Mathematical Regression Of The U.S. Gross Private Domestic Investment 1959-2001, Byron E. Bell

Byron E. Bell

SUMMARY OF PROJECT What did I do? A study of the role the U.S. stock markets and money markets have possibly played in the Gross Private Domestic Investment (GPDI) of the United States from the year 1959 to the year 2001 and I created a Multiple Linear Regression Model (MLRM).

Are Credit Constraints In Italy Really More Binding In The South?, Claudio Lupi

Claudio Lupi

This paper is motivated by a very practical question: are there significant geographical differences in the accessibility to the credit market on the part of Italian households? The investigation is carried using robust probit model. Estimation is carried out in a Bayesian framework. The results are somewhat surprising, showing that the area where households are more likely to be credit constrained is not the South, as could be easily imagined, but rather the highly developed and industrialized North-West.