Zobrazeno 1 - 10
of 965
pro vyhledávání: '"Agostinelli Claudio"'
We consider robust estimation of wrapped models to multivariate circular data that are points on the surface of a $p$-torus based on the weighted likelihood methodology.Robust model fitting is achieved by a set of weighted likelihood estimating equat
Externí odkaz:
http://arxiv.org/abs/2401.04686
We propose a MANOVA test for semicontinuous data that is applicable also when the dimensionality exceeds the sample size. The test statistic is obtained as a likelihood ratio, where numerator and denominator are computed at the maxima of penalized li
Externí odkaz:
http://arxiv.org/abs/2401.04036
Autor:
Valdora, Marina, Agostinelli, Claudio
Robust estimators for Generalized Linear Models (GLMs) are not easy to develop because of the nature of the distributions involved. Recently, there has been an increasing interest in this topic, especially in the presence of a possibly large number o
Externí odkaz:
http://arxiv.org/abs/2312.04661
This paper considers generalised network, intended as networks where (a) the edges connecting the nodes are nonlinear, and (b) stochastic processes are continuously indexed over both vertices and edges. Such topological structures are normally repres
Externí odkaz:
http://arxiv.org/abs/2309.15855
The Seemingly Unrelated Regressions (SUR) model is a wide used estimation procedure in econometrics, insurance and finance, where very often, the regression model contains more than one equation. Unknown parameters, regression coefficients and covari
Externí odkaz:
http://arxiv.org/abs/2107.00975
Publikováno v:
Saraceno, G., Agostinelli, C. & Greco, L. Robust estimation for multivariate wrapped models. METRON (2021)
A weighted likelihood technique for robust estimation of a multivariate Wrapped Normal distribution for data points scattered on a p-dimensional torus is proposed. The occurrence of outliers in the sample at hand can badly compromise inference for st
Externí odkaz:
http://arxiv.org/abs/2010.08444
Many real-life data sets can be analyzed using Linear Mixed Models (LMMs). Since these are ordinarily based on normality assumptions, under small deviations from the model the inference can be highly unstable when the associated parameters are estima
Externí odkaz:
http://arxiv.org/abs/2010.05593
Local general depth ($LGD$) functions are used for describing the local geometric features and mode(s) in multivariate distributions. In this paper, we undertake a rigorous systematic study of $LGD$ and establish several analytical and statistical pr
Externí odkaz:
http://arxiv.org/abs/2008.11957
One of the most common problems that any technique encounters is the high dimensionality of the input data. This yields several problems in the subsequently statistical methods due to so called "curse of dimensionality". Several dimension reduction m
Externí odkaz:
http://arxiv.org/abs/2008.10725