The present article offers a certain unifying approach to time series regression modelling by combining partial likelihood (PL) inference and generalized linear models. An advantage gained by resorting to PL is that the joint distribution of the response and the covariates is left unspecified,...

The present article offers a certain unifying approach to time series regression modelling by combining partial likelihood (PL) inference and generalized linear models. An advantage gained by resorting to PL is that the joint distribution of the response and the covariates is left unspecified,...

In this dissertation, a Semiparametric density ratio testing method which borrows strength from two or more samples is applied to moving windows of variable size in cluster detection. This Semiparametric cluster detection method requiresneither the prior knowledge of the underlying distribution...

The first part of the dissertation concerns financial volatility models. Financial volatility has some stylized facts, such as excess kurtosis, volatility clustering and leverage effects. A good volatility model should be able to capture all these stylized facts. Among the volatility models,...

In this dissertation we propose a new model which captures observed features of asset prices. The model reproduces the skewness and fat tails of asset returns by introducing a discretized variance gamma process as the driving innovation process, in addition to a double gamma process to reflect...

A semiparametric approach to the one-way layout is described, and its efficiency in the two-sample case relative to the common t-test is studied. The power efficiency computed for several special cases points to an intriguing behaviour where one test may be more efficient than the other over a...

A multiple-sample semiparametric density ratio model, which is equivalent to a generalized logistic regression model, can be constructedby multiplicative exponential distortions of a reference distribution. Distortion functions are assumed to be nonnegative and of a known finite-dimensional...

Fitting parametric models or the use of the empirical cumulative distribution function are problematic when it comes to the estimation of tail probabilities from small samples. A possible remedy is to fuse or combine the small samples with additional data from external sources and base the...