Physical Sciences and Mathematics Commons^™

Real Options Models In Real Estate, Jin Won Choi

Electronic Thesis and Dissertation Repository

Our aim in this thesis is to investigate the usefulness of real options analysis, taking case studies of problems in real estate. In the realm of real estate, we consider the following three problems. First, we consider the valuation and usefulness of presale contracts of condominiums, which can be viewed as similar to call options on condominiums. Secondly, we consider the valuation of farm land from the perspective of land developers, who may think of farm land as being similar to call options on subdivision lots. Third, we consider the valuation of opportunities to install solar panels on properties, in …

Generalized Exponential Models With Applications, Iman Mabrouk

Electronic Thesis and Dissertation Repository

We introduce a generalized exponential model whose exact moments and normalizing constant are obtained in terms of Meijer’s generalized hypergeometric G-function. Actually, several widely utilized statistical distributions such as the gamma, Weibull and half-normal constitute particular cases thereof. The generalized inverse Gaussian distribution, which was popularized in the late seventies by Ole Barndor_Neilsen, is also extended by incorporating an additional parameter in its density function, the moments of the resulting distribution being expressed in terms of Bessel functions. A number of data sets were then fitted with diverse exponential-type models for comparison purposes. Additionally, it is shown that the …

Advances In Graph-Cut Optimization: Multi-Surface Models, Label Costs, And Hierarchical Costs, Andrew T. Delong

Electronic Thesis and Dissertation Repository

Computer vision is full of problems that are elegantly expressed in terms of mathematical optimization, or energy minimization. This is particularly true of "low-level" inference problems such as cleaning up noisy signals, clustering and classifying data, or estimating 3D points from images. Energies let us state each problem as a clear, precise objective function. Minimizing the correct energy would, hypothetically, yield a good solution to the corresponding problem. Unfortunately, even for low-level problems we are confronted by energies that are computationally hard—often NP-hard—to minimize. As a consequence, a rather large portion of computer vision research is dedicated to proposing …

Asymptotic Theory Of General Multivariate Garch Models, Weibin Jiang

Electronic Thesis and Dissertation Repository

Generalized autoregressive conditional heteroscedasticity (GARCH) models are widely used in financial markets. Parameters of GARCH models are usually estimated by the quasi-maximum likelihood estimator (QMLE). In recent years, economic theory often implies equilibrium between the levels of time series, which makes the application of multivariate models a necessity. Unfortunately the asymptotic theory of the multivariate GARCH models is far from coherent since many algorithms on the univariate case do not extend to multivariate models naturally. This thesis studies the asymptotic theory of the QMLE under mild conditions. We give some counterexamples for the parameter identifiability result in Jeantheau [1998] and …

Diagnostic Checking, Time Series And Regression, Esam Mahdi

Electronic Thesis and Dissertation Repository

In this thesis, a new univariate-multivariate portmanteau test is derived. The proposed test statistic can be used for diagnostic checking ARMA, VAR, FGN, GARCH, and TAR time series models as well as for checking randomness of series and goodness-of- fit VAR models with stable Paretian errors. The asymptotic distribution of the test statistic is derived as well as a chi-square approximation. However, the Monte-Carlo test is recommended unless the series is very long. Extensive simulation experiments demonstrate the usefulness of this test and its improved power performance compared to widely used previous multivariate portmanteau diagnostic check. The contributed R package …

Confidence Interval Estimation For Continuous Outcomes In Cluster Randomization Trials, Julia Taleban

Electronic Thesis and Dissertation Repository

Cluster randomization trials are experiments where intact social units (e.g. hospitals, schools, communities, and families) are randomized to the arms of the trial rather than individuals. The popularity of this design among health researchers is partially due to reduced contamination of treatment effects and convenience. However, the advantages of cluster randomization trials come with a price. Due to the dependence of individuals within a cluster, cluster randomization trials suffer reduced statistical efficiency and often require a complex analysis of study outcomes.

The primary purpose of this thesis is to propose new confidence intervals for effect measures commonly of interest for …