Journal of the Italian Statistical Society
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Bootstrap prediction regions for multivariate autoregressive processes
Journal of the Italian Statistical Society - Tập 14 - Trang 179-207 - 2005
Two new methods for improving prediction regions in the context of vector
autoregressive (VAR) models are proposed. These methods, which are based on the
bootstrap technique, take into account the uncertainty associated with the
estimation of the model order and parameters. In particular, by exploiting an
independence property of the prediction error, we will introduce a bootstrap
procedure that a...
Non parametric mixture priors based on an exponential random scheme
Journal of the Italian Statistical Society - Tập 11 - Trang 1-20 - 2002
We propose a general procedure for constructing nonparametric priors for
Bayesian inference. Under very general assumptions, the proposed prior selects
absolutely continuous distribution functions, hence it can be useful with
continuous data. We use the notion ofFeller-type approximation, with a random
scheme based on the natural exponential family, in order to construct a large
class of distribut...
Childcare and participation at work in North-East Italy: Why do Italian and foreign mothers behave differently?
Journal of the Italian Statistical Society - Tập 24 - Trang 339-358 - 2015
This paper examines two of the decision-making processes following the birth of
a child: whether a working mother should continue with her job, and whether the
couple should provide the child with formal childcare. Focusing on Padova and
its district, this paper discusses differences in the strategies used by Italian
and foreign mothers, controlling for socio-economic status and opinions on
women’...
A bivariate F distribution with marginals on arbitrary numerator and denominator degrees of freedom, and related bivariate beta and t distributions
Journal of the Italian Statistical Society - - 2009
Asymptotics of the weighted least squares estimation for AR(1) processes with applications to confidence intervals
Journal of the Italian Statistical Society - Tập 27 Số 3 - Trang 479-490 - 2018
Nonparametric semi-supervised classification with application to signal detection in high energy physics
Journal of the Italian Statistical Society - Tập 31 - Trang 531-550 - 2021
Model-independent searches in particle physics aim at completing our knowledge
of the universe by looking for new possible particles not predicted by the
current theories. Such particles, referred to as signal, are expected to behave
as a deviation from the background, representing the known physics. Information
available on the background can be incorporated in the search, in order to
identify po...
Further results on orthogonal arrays for the estimation of global sensitivity indices based on alias matrix
Journal of the Italian Statistical Society - Tập 24 Số 3 - Trang 411-426 - 2015
Bahadur efficiency and local optimality of a test for the exponential distribution based on the gini statistic
Journal of the Italian Statistical Society - Tập 5 - Trang 163-175 - 1996
The sample scale-free Gini index is known to be a powerful test of
exponentiality against a broad class of alternatives. To understand better the
efficiency properties of this test we calculate its Bahadur efficiency for most
commonly used parametric alternatives to the exponential distribution. Using
variational arguments and the Bahadur-Raghavachari inequality for exact slopes
we find the condit...
Influence diagnostic analysis in the possibly heteroskedastic linear model with exact restrictions
Journal of the Italian Statistical Society - Tập 25 - Trang 227-249 - 2015
The local influence method has proven to be a useful and powerful tool for
detecting influential observations on the estimation of model parameters. This
method has been widely applied in different studies related to econometric and
statistical modelling. We propose a methodology based on the Lagrange multiplier
method with a linear penalty function to assess local influence in the possibly
hetero...
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