Search results for "component"
showing 10 items of 1682 documents
Multiple factor analysis: principal component analysis for multitable and multiblock data sets
2013
Multiple factor analysis MFA, also called multiple factorial analysis is an extension of principal component analysis PCA tailored to handle multiple data tables that measure sets of variables coll...
Prospective surveillance of multivariate spatial disease data
2012
Surveillance systems are often focused on more than one disease within a predefined area. On those occasions when outbreaks of disease are likely to be correlated, the use of multivariate surveillance techniques integrating information from multiple diseases allows us to improve the sensitivity and timeliness of outbreak detection. In this article, we present an extension of the surveillance conditional predictive ordinate to monitor multivariate spatial disease data. The proposed surveillance technique, which is defined for each small area and time period as the conditional predictive distribution of those counts of disease higher than expected given the data observed up to the previous t…
Affine-invariant rank tests for multivariate independence in independent component models
2016
We consider the problem of testing for multivariate independence in independent component (IC) models. Under a symmetry assumption, we develop parametric and nonparametric (signed-rank) tests. Unlike in independent component analysis (ICA), we allow for the singular cases involving more than one Gaussian independent component. The proposed rank tests are based on componentwise signed ranks, à la Puri and Sen. Unlike the Puri and Sen tests, however, our tests (i) are affine-invariant and (ii) are, for adequately chosen scores, locally and asymptotically optimal (in the Le Cam sense) at prespecified densities. Asymptotic local powers and asymptotic relative efficiencies with respect to Wilks’…
Gamma Kernel Intensity Estimation in Temporal Point Processes
2011
In this article, we propose a nonparametric approach for estimating the intensity function of temporal point processes based on kernel estimators. In particular, we use asymmetric kernel estimators characterized by the gamma distribution, in order to describe features of observed point patterns adequately. Some characteristics of these estimators are analyzed and discussed both through simulated results and applications to real data from different seismic catalogs.
Structure and dynamics of yukawa systems
1993
Abstract Results of molecular dynamics simulations modelling two component charge stabilized colloidal particles interacting via a Yukawa potential are presented. After cooling, the systems freeze into either substitutionally disordered imperfect crystals or into glasslike states. This freezing is characterized by the divergence of a suitable correlation time due to loss of ergodicity. Describing the structure by bond correlation functions, local orientational ordering is observed in the glassy states which is not present in the liquid. In the liquid the diffusion constant obeys an Arrhenius law. As can be deduced from the van Hove functions, in the crystal the particles only oscillate arou…
Functional Principal Component Analysis for the explorative analysis of multisite-multivariate air pollution time series with long gaps
2013
The knowledge of the urban air quality represents the first step to face air pollution issues. For the last decades many cities can rely on a network of monitoring stations recording concentration values for the main pollutants. This paper focuses on functional principal component analysis (FPCA) to investigate multiple pollutant datasets measured over time at multiple sites within a given urban area. Our purpose is to extend what has been proposed in the literature to data that are multisite and multivariate at the same time. The approach results to be effective to highlight some relevant statistical features of the time series, giving the opportunity to identify significant pollutants and…
Simulation in the Simple Linear Regression Model
2002
Summary This article presents an activity which simulates the linear regression model in order to verify the probabilistic behaviour of the resulting least-squares statistics in practice.
Linear and ellipsoidal restrictions in linear regression
1991
The problem of combining linear and ellipsoidal restrictions in linear regression is investigated. Necessary and sufficient conditions for compactness of the restriction set are proved assuring the existence of a minimax estimator. When the restriction set is not compact a minimax estimator may still exist for special loss functions arid regression designs
On the usage of joint diagonalization in multivariate statistics
2022
Scatter matrices generalize the covariance matrix and are useful in many multivariate data analysis methods, including well-known principal component analysis (PCA), which is based on the diagonalization of the covariance matrix. The simultaneous diagonalization of two or more scatter matrices goes beyond PCA and is used more and more often. In this paper, we offer an overview of many methods that are based on a joint diagonalization. These methods range from the unsupervised context with invariant coordinate selection and blind source separation, which includes independent component analysis, to the supervised context with discriminant analysis and sliced inverse regression. They also enco…
Stochastic labelling of biological images
1998
Many hypotheses made by experimental researchers can be formulated as a stochastic labelling of a given image. Some stochastic labelling methods for random closed sets are proposed in this paper. Molchanov (I. Molchanov, 1984, Theor. Probability and Math. Statist.29, 113–119) provided the probabilistic background for this problem. However, there is a lack of specific labelling models. Ayala and Simo (G. Ayala and A. Simo, 1995, Advances in Applied Probability27, 293–305) proposed a method in which, given the whole set of connected components, every component is classified in a certain phase or category in a completely random way. Alternative methods are necessary in case the random labellin…