Search results for "multivariate"
showing 10 items of 1520 documents
On statistical inference for the random set generated Cox process with set-marking.
2007
Cox point process is a process class for hierarchical modelling of systems of non-interacting points in ℝd under environmental heterogeneity which is modelled through a random intensity function. In this work a class of Cox processes is suggested where the random intensity is generated by a random closed set. Such heterogeneity appears for example in forestry where silvicultural treatments like harvesting and site-preparation create geometrical patterns for tree density variation in two different phases. In this paper the second order property, important both in data analysis and in the context of spatial sampling, is derived. The usefulness of the random set generated Cox process is highly…
Multivariate statistical analysis for exploring road crash-related factors in the Franche-Comté region of France
2021
Understanding and modelling road crash data is crucial in fulfilling safety goals by helping national authorities to take necessary measures to reduce crash frequency and severity. This work aims at giving a multivariate statistical analysis of road crash data from the French region of Franche-Comte with special attention to road crash gravity. The first step for this multivariate analysis was to perform Multiple Correspondence Analysis in order to assess associations between the road crash injury and several important accident-related factors and circumstances. Log-linear models are used next in order to detect associations between road crash severity and related factors such as al-cohol/d…
An approximation to maximum likelihood estimates in reduced models
1990
SUMMARY An approximation to the maximum likelihood estimates of the parameters in a model can be obtained from the corresponding estimates and information matrices in an extended model, i.e. a model with additional parameters. The approximation is close provided that the data are consistent with the first model. Applications are described to log linear models for discrete data, to models for multivariate normal distributions with special covariance matrices and to mixed discrete-continuous models.
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…
Clusters of effects curves in quantile regression models
2018
In this paper, we propose a new method for finding similarity of effects based on quantile regression models. Clustering of effects curves (CEC) techniques are applied to quantile regression coefficients, which are one-to-one functions of the order of the quantile. We adopt the quantile regression coefficients modeling (QRCM) framework to describe the functional form of the coefficient functions by means of parametric models. The proposed method can be utilized to cluster the effect of covariates with a univariate response variable, or to cluster a multivariate outcome. We report simulation results, comparing our approach with the existing techniques. The idea of combining CEC with QRCM per…
Multivariate Nonparametric Tests
2004
Multivariate nonparametric statistical tests of hypotheses are described for the one-sample location problem, the several-sample location problem and the problem of testing independence between pairs of vectors. These methods are based on affine-invariant spatial sign and spatial rank vectors. They provide affine-invariant multivariate generalizations of the univariate sign test, signed-rank test, Wilcoxon rank sum test, Kruskal–Wallis test, and the Kendall and Spearman correlation tests. While the emphasis is on tests of hypotheses, certain references to associated affine-equivariant estimators are included. Pitman asymptotic efficiencies demonstrate the excellent performance of these meth…
Fourth Moments and Independent Component Analysis
2015
In independent component analysis it is assumed that the components of the observed random vector are linear combinations of latent independent random variables, and the aim is then to find an estimate for a transformation matrix back to these independent components. In the engineering literature, there are several traditional estimation procedures based on the use of fourth moments, such as FOBI (fourth order blind identification), JADE (joint approximate diagonalization of eigenmatrices), and FastICA, but the statistical properties of these estimates are not well known. In this paper various independent component functionals based on the fourth moments are discussed in detail, starting wi…
Test of the Latent Dimension of a Spatial Blind Source Separation Model
2024
We assume a spatial blind source separation model in which the observed multivariate spatial data is a linear mixture of latent spatially uncorrelated random fields containing a number of pure white noise components. We propose a test on the number of white noise components and obtain the asymptotic distribution of its statistic for a general domain. We also demonstrate how computations can be facilitated in the case of gridded observation locations. Based on this test, we obtain a consistent estimator of the true dimension. Simulation studies and an environmental application in the Supplemental Material demonstrate that our test is at least comparable to and often outperforms bootstrap-bas…
Firm Size and Volatility Analysis in the Spanish Stock Market
2011
In this article, three strongly related questions are studied. First, volatility spillovers between large and small firms in the Spanish stock market are analyzed by using a conditional CAPM with an asymmetric multivariate GARCH-M covariance structure. Results show that there exist bidirectional volatility spillovers between both types of firms, especially after bad news. Second, the volatility feedback hypothesis explaining the volatility asymmetry feature is investigated. Results show significant evidence for this hypothesis. Finally, the study uncovers that conditional beta coefficient estimates within the used model are insensitive to sign and size asymmetries in the unexpected shock re…
Managing satisfaction in cultural events: Exploring the role of core and peripheral product
2017
1.INTRODUCTIONSatisfaction is a key concept within the marketing discipline and specifically within the area of consumer behaviour. Satisfaction in the arts is mostly derived from a combination of three elements: the subjective and experiential aspects of the cultural product, the quality of the venue and the quality of the associated peripheral services (Hume, 2008a). According to this author, studies on satisfaction with cultural events are key to understanding customer motives to repurchase subscription which can increase the arts organization's profitability, this being a main goal of the currently complex entertainment arena.This study focuses on satisfaction among visitors of an art e…