Testing for a Breakpoint in Two-Phase Linear and Logistic Regression Models

In many practical problems, it is of interest to check whether a functional relationship between an explanatory and a response variable remains unchanged over the whole domain of the explanatory variable or whether the functional form changes at certain unknown points, the so-called breakpoints. Thus, testing for the existence of a breakpoint is often an essential task. In this paper, we consider likelihood-ratio tests for different regression models such as broken line and threshold models. The problem related to the use of likelihood-ratio tests in this context concerns the determination of the null distribution of the likelihood-ratio statistic which has not been solved yet analytically. It is shown by means of Monte-Carlo experiments that the proposals of a limiting distribution discussed in the literature often yield unreliable results. It is therefore recommended to determine appropriate critical values by simulating the null distribution according to the data situation under investigation

Bayesian space-time analysis of health insurance data

Generalized linear models (GLMs) and semiparametric extensions provide a flexible framework for analyzing the claims process in non-life insurance. Currently, most applications are still based on traditional GLMs, where covariate effects are modelled in form of a linear predictor. However, these models may already be too restrictive if nonlinear effects of metrical covariates are present. Moreover, although data are often collected within longer time periods and come from different geographical regions, effects of space and time are usually totally neglected. We provide a Bayesian semiparametric approach, which allows to simultaneously incorporate effects of space, time and further covariates within a joint model. The method is applied to analyze costs of hospital treatment and accommodation for a large data set from a German health insurance company

Testing for a breakpoint in two-phase linear and logistic regression models

In many practical problems, it is of interest to check whether a functional relationship between an explanatory and a response variable remains unchanged over the whole domain of the explanatory variable or whether the functional form changes at certain unknown points, the so-called breakpoints. Thus, testing for the existence of a breakpoint is often an essential task. In this paper, we consider likelihood-ratio tests for different regression models such as broken line and threshold models. The problem related to the use of likelihood-ratio tests in this context concerns the determination of the null distribution of the likelihood-ratio statistic which has not been solved yet analytically. It is shown by means of Monte-Carlo experiments that the proposals of a limiting distribution discussed in the literature often yield unreliable results. It is therefore recommended to determine appropriate critical values by simulating the null distribution according to the data situation under investigation. (orig.)Available from TIB Hannover: RR 6137(77) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman

DNA barcoding and faunistic criteria for a revised taxonomy of Italian Ephemeroptera

<p>Mayfly (Ephemeroptera) systematics has considerably changed over the years, but many questions have yet to be answered. The synergistic connection between traditional knowledge and new data sources, producing increasingly complex information, has become a compelling issue for modern taxonomy. Molecular tests and the use of reliable reference sequence libraries may constitute effective complements to the traditional method in guiding recognition of species and giving information about taxonomic incongruences which require further examination. In the present study, we sought to verify the current Italian mayfly nomenclatural system through DNA barcoding and relevant points to reliably manage the available amount of morpho-ecological and molecular data are discussed. We investigated COI (Cytochrome oxidase I) sequence variation in 163 individuals of Italian mayflies, 126 of which were previously assigned to 24 morphologically recognised species, and 37 could be attributed only to generic taxonomic entities (“sp.”, “cf.” or “gr.”). DNA barcoding statistical tests for species delimitation hypotheses based on genetic distances and inferred gene trees were integrated with GenBank searches and surveys of the historical literature to better understand the knowledge acquired on the status and diversity of the investigated taxa. Combined criteria to define three categories of reliability were then assessed. Concurrent data allowing unambiguous identification were attained for only eight species. High intraspecific genetic distances (> 3%) and a lack of reliable reference material or convincing taxonomic information evidenced 29 critical states, deserving further investigation. Solid species names, potential cryptic species and entities about which little is known are pointed out for a future upgrade/reorganisation of the taxonomy of Italian Ephemeroptera.</p