Fourier analysis of stationary time series in function space
SteamAdm
We develop the basic building blocks of a frequency domain framework for drawing statistical inferences on the second-order structure of a stationary sequence of functional
Category: 2013
Metric Gauge Fields in Deformed Special Relativity
SteamAdm
We show that, in the framework of Deformed Special Relativity (DSR), namely a (four-dimensional) generalization of the (local) space-time struc- ture based on an energy-dependent
Validity of covariance models for the analysis of geographical variation
SteamAdm
Due to the availability of large molecular data-sets, covariance models are increasingly used to describe the structure of genetic variation as an alternative to more
Calibration estimation in dual frame surveys
SteamAdm
Survey statisticians make use of the available auxiliary information to improve estimates. One important example is given by calibration estimation, that seeks for new weights
Multiple Hidden Markov Models for Categorical Time Series
SteamAdm
We introduce multiple hidden Markov models (MHMMs) where an observed multivariate categorical time series depends on an unobservable multivariate Mar- kov chain. MHMMs provide an
Multivariate Markov-Switching models and tail risk interdependence
SteamAdm
Markov switching models are often used to analyze financial returns because of their ability to capture frequently observed stylized facts. In this paper we consider
A test for directional-linear independence, with applications to wildfire orientation and size
SteamAdm
The relation between wildfire orientation and size is analyzed by means of a nonparametric test for directional-linear independence. The test statistic is designed for assessing
Comparing composite likelihood methods based on pairs for spatial Gaussian random fieldsM
SteamAdm
In the last years there has been a growing interest in proposing methods for estimating covariance functions for geostatistical data. Among these, maximum likelihood estimators
Bayesian Modeling and MCMC Computation in Linear Logistic Regression for Presence-only Data
SteamAdm
Presence-only data are referred to situations in which, given a censoring mechanism, a binary response can be observed only with respect to on outcome, usually
Disease Mapping via Negative Binomial Regression M-quantiles
SteamAdm
We introduce a semi-parametric approach to ecological regression for disease mapping, based on modelling the regression M-quantiles of a Negative Binomial variable. The proposed method