Now that the worst of the growing pains have been subdued, cleantech has made a respectable comeback onto the global agenda of firms, investors and economic developers alike. One might say it is bigger than ever, with a constantly proliferating range of cleantech companies and business models....

The standard methodology when building statistical models has been to use one of several algorithms to systematically search the model space for a good model. If the number of variables is small then all possible models or best subset procedures may be used, but for data sets with a large number...

Since the mid 1980's many statisticians have studied methods for combining parametric andnonparametric esimates to improve the quality of fits in a regression problem. Notably in 1987,Einsporn and Birch proposed the Model Robust Regression estimate (MRR1) in which estimatesof the parametric...

Parametric regression fitting (such as OLS) to a data setrequires specification of an underlying model. If thespecified model is different from the true model, then theparametric fit suffers to a degree that varies with the extentof model misspecification. Mays and Birch (1996)addressed this...

The content of this dissertation is divided into two main topics: 1) nonlinear profilemonitoring and 2) an improved approximate distribution for the T^2 statistic based on thesuccessive differences covariance matrix estimator. (Part 1) In an increasing number of cases the quality of a product or...

The phenomenon of overdispersion arises when categorical or count data exhibit variability larger than expected. Multinomial data commonly demonstrate this phenomenon when the counts arise from correlated or cluster observations. There are several ways of analyzing overdispersed multinomial...

With the emergence and expansion of credit derivatives, which are financial instruments that are based on corporate bonds and provide their holders a protection against default, the importance of estimating probabilities of default has reached an unprecedented level. We have developed a Bayesian...