196,124 research outputs found
Modelling short-term effects of ozone on morbidity: an application to the city of Milano, Italy, 1995-2003.
No full textIn this paper, we explore a range of concerns that arise in measuring
short-term effects of ozone on health. In particular, we tackle the problem of measuring
exposure using alternative daily measures of ozone derived from hourly concentrations.
We adopt the exposure paradigm of Chiogna and Bellini (Environmetrics
13:55–69, 2002) extending it to ozone concentrations, and we compare its performances
with respect to traditional exposure measures by exploiting model selection.
To investigate the stability of model selection, we then apply the idea of bootstrapping
the modelling process
Short term ozone effects on morbidity for the city of Milano, Italy, 1996-2003.
No full textIn this paper, we explore a range of concerns that arise in measuring short term ozone effects on health. In particular, we tackle the problem of measuring exposure using alternative daily measures of ozone derived from hourly concentrations. We adopt the exposure paradigm of Chiogna and Bellini (2002), and we compare its performances with respect to traditional exposure measures by exploiting model selection. For investigating model selection stability issues, we then apply the idea of bootstrapping the modelling process
A note on the asymptotic distribution of the maximum likelihood estimator for the scalar Skew-normal distribution
No full textWe consider likelihood based inference for the parameter of a skewnormal
distribution. One of the problems shown by this model is the singularity
of the Fisher information matrix when skewness is absent. We derive the rate of
convergence to the asymptotic distribution of the maximum likelihood estimator
and study an alternative parameterization which overcomes problems related to the
singularity of the information matrix
Additive regression modelling for zero inflated Poisson distribution
No full textin S. Zani and A. Cerioli (Eds
Exploratory analysis of epidemiological time series by means of transfer function models
No full textEffectiveness of combinations of Gaussian graphical models for model building
No full textCombining statistical models is an useful approach in all the research area where a global picture of the problem needs to be constructed by binding together evidence from different sources [M.S. Massa and S.L. Lauritzen Combining Statistical Models, M. Viana and H. Wynn, eds., American Mathematical Society, Providence, RI, 2010, pp. 239-259]. In this paper, we investigate the effectiveness of combining a fixed number of Gaussian graphical models respecting some consistency assumptions in problems of model building. In particular, we use the meta-Markov combination of Gaussian graphical models as detailed in Massa and Lauritzen and compare model selection results obtained by combining selections over smaller sets of variables with selection results over all variables of interest. In order to do so, we carry out some simulation studies in which different criteria are considered for the selection procedures. We conclude that the combination performs, generally, better than global estimation, is computationally simpler by virtue of having fewer and simpler models to work on, and has an intuitive appeal to a wide variety of contexts. © 2013 Copyright Taylor and Francis Group, LLC
Searching for a source of difference in undirected graphical models for count data - an empirical study
No full textA study is presented for exploring the possibility of applying the source set approach (Djordjilovic V, Chiogna M.(2018)), developed under the assumption of normality, to count data, after data transformation. Some explanations about the source set approach, data trans- formations and the simulation setting are provided. The suggestion is given that the deviance-based or quantile randomized residuals could provide a better basis for data transformation when coupled with source set analysis, along with standard trasformations such as log transformation or square root transformation
Semiparametric zero-inflated Poisson models with application to animal abundance studies
No full textThis paper describes a framework for flexibly modeling zero-inflated data. Semiparametric regression based on
penalized regression splines for zero-inflated Poisson models is introduced. Moreover, an EM-type algorithm is
developed to perform maximum likelihood estimation. As an illustration, a study of animal abundance is tackled.
In fact, abundance often shows excess of zeroes and is a complicated function of the explanatory variables. In
particular, the relationships between avian abundance and environmental variables indicating land use are tackled
Hierarchical space-time modelling of epidemic dynamics: an application to measles outbreaks
No full textHow infectious diseases spread in space and time is an important question
that has received considerable theoretical attention. There are, however, few
empirical studies to support theoretical approaches, because data is scarce. In this
paper we propose to model the epidemic spread of measles in the London boroughs
between 1960 and 1970 by an extension of the Kriged Kalman filter (Mardia et
al., 1998) to count data. Results show the flexibility of our approach in describing
complex spatio-temporal dynamic
A Quantile-based Test for Detecting Differential Expression in Microarray Data
No full textNello scorso decennio lo sviluppo di metodi statistici per l’analisi di dati di microarray è stato oggetto di crescente interesse. Un problema cruciale in questo campo è l’identificazione di geni che mostrano una differente espressione tra due o più gruppi, come ad esempio tra tessuti sani e malati. Un grande numero di strumenti statistici è stato proposto per questo compito, la maggior parte dei quali ha l’obiettivo di testare un’ipotesi di uguaglianza tra medie. Lo scopo del presente lavoro è di introdurre una statistica semplice basata sui quantili, in grado di testare differenze a diversi livelli della distribuzione, e che gode della proprieta desiderabile di invarianza rispetto a trasformazioni monotone dei dati
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