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In many scientific studies, the response variable bears a generalized nonlinear regression relationship with a certain covariate of interest, which may, however, be confounded by other covariates with unknown functional form. We propose a new class of models, the partly parametric generalized...
Persistent link: https://www.econbiz.de/10009466085
This dissertation studies the question of nonlinearities in the Phillips curve relationshipin France, Germany and Italy. The implications from the theoretical models are that themechanisms that make the Phillips curve nonlinear can work through different channels.Therefore, this thesis not just...
Persistent link: https://www.econbiz.de/10009471618
The field of nonlinear regression is a long way from reaching a consensus. Once a method decides to explore nonlinear combinations of predictors, a number of questions are raised, such as what nonlinear combinations to permit and how best to search the resulting model space. Genetic Association...
Persistent link: https://www.econbiz.de/10009480508
When using derivative instruments such as futures to hedge a portfolio of risky assets, the primary objective is to estimate the optimal hedge ratio (OHR). When agents have mean-variance utility and the futures price follows a martingale, the OHR is equivalent to the minimum variance hedge...
Persistent link: https://www.econbiz.de/10009440947
The lognormal distribution is useful in modeling continuous random variables which are greater than or equal to zero. Example scenarios in which the lognormal distribution is used include, among many others: in medicine, latent periods of infectious diseases; in environmental science, the...
Persistent link: https://www.econbiz.de/10009457140
This paper presents the design and implementation of a new comparative analytical framework for studying the usability of modern high breakdown robust estimators. The emphasis is on finding the intrinsic limits, in terms of size and relative spatial accuracy, of such techniques in solving the...
Persistent link: https://www.econbiz.de/10009481770
We introduce a new method to robustifying inference that can be applied in any situation where a parametric likelihood is available. The key feature is that data from the postulated parametric models are assumed to be measured with error where the measurement error distribution is chosen to...
Persistent link: https://www.econbiz.de/10009431189