Search results for "Multivariate statistics"

Who is willing to pay for science? On the relationship between public perception of science and the attitude to public funding of science.

2012

This article examines the relationship between the general public's understanding of science and the attitude towards public funding of scientific research. It applies a multivariate and discriminant analysis (Wilks' Lambda), in addition to a more commonly used bivariate analysis (Cramer's V), to data compiled from the Third National Survey on the Social Perception of Science and Technology in Spain (FECYT, 2006). The general conclusion is that the multivariate analysis produces information complementary to the bivariate analysis, and that the variables commonly applied in public perception studies have limited predictive value with respect to the attitude towards public funding of scientif…

Probabilistic Flood Hazard Mapping Using Bivariate Analysis Based on Copulas

2017

This study presents a methodology to extract probabilistic flood hazard maps in an area subject to flood risk, taking into account uncertainties in the definition of design hydrographs. Particularly, the authors present a new method to produce probabilistic inundation and flood hazard maps in which the hydrological input (i.e., synthetic flood design event) to a 2D hydraulic model has been obtained by using a bivariate statistical analysis (copulas) to generate flood peak discharges and volumes. This study also aims to quantify the contribution of boundary conditions’ uncertainty in order to evaluate the effect of this uncertainty source on probabilistic flood hazard mapping. Different comb…

Testing Equality of Multiple Power Spectral Density Matrices

2018

This paper studies the existence of optimal invariant detectors for determining whether P multivariate processes have the same power spectral density. This problem finds application in multiple fields, including physical layer security and cognitive radio. For Gaussian observations, we prove that the optimal invariant detector, i.e., the uniformly most powerful invariant test, does not exist. Additionally, we consider the challenging case of close hypotheses, where we study the existence of the locally most powerful invariant test (LMPIT). The LMPIT is obtained in the closed form only for univariate signals. In the multivariate case, it is shown that the LMPIT does not exist. However, the c…

Automated facies identification by Direct Push-based sensing methods (CPT, HPT) and multivariate linear discriminant analysis to decipher geomorpholo…

2021

In ad 1362, a major storm surge drowned wide areas of cultivated medieval marshland along the north‐western coast of Germany and turned them into tidal flats. This study presents a new methodological approach for the reconstruction of changing coastal landscapes developed from a study site in the Wadden Sea of North Frisia. Initially, we deciphered long‐term as well as event‐related short‐term geomorphological changes, using a geoscientific standard approach of vibracoring, analyses of sedimentary, geochemical and microfaunal palaeoenvironmental parameters and radiocarbon dating. In a next step, Direct Push (DP)‐based Cone Penetration Testing (CPT) and the Hydraulic Profiling Tool (HPT) wer…

Statistical Multivariate Techniques for the Stock Location Assignment Problem

1998

In previous papers we proposed to apply multivariate statistical methodologies, like Multidimensional Scaling (MDS) and Seriation to the stock location assignment problem of a warehouse, often solved by considering the Cube per Order Index (COI). In this paper we compare the results by MDS, Seriation, a COI based method and the Maximum Path criterion, considering the data of a whole year of a Sicilian supermarket chain warehouse. The comparison is based on the simulated times to satisfy a sample of real orders.

Application of multivariate statistics to the problems of upper palaeolithic and mesolithic samples

1987

Multivariate statistics (discriminant function analysis and principal component analysis) have been applied to a broad sample of Upper Paleolithic and mesolithic skulls. In addition to some methodological problems concerning the evaluation of missing data by principal component analysis, we discussed the possibility of misclassifications (14%).

Multivariate Survey Analysis

2004

Global, regional, and national burden of mortality associated with non-optimal ambient temperatures from 2000 to 2019: a three-stage modelling study

2021

Background: Exposure to cold or hot temperatures is associated with premature deaths. We aimed to evaluate the global, regional, and national mortality burden associated with non-optimal ambient temperatures. Methods: In this modelling study, we collected time-series data on mortality and ambient temperatures from 750 locations in 43 countries and five meta-predictors at a grid size of 0·5° × 0·5° across the globe. A three-stage analysis strategy was used. First, the temperature–mortality association was fitted for each location by use of a time-series regression. Second, a multivariate meta-regression model was built between location-specific estimates and meta-predictors. Finally, the gri…

Computation of the Multivariate Oja Median

2003

The multivariate Oja median (Oja, 1983) is an affine equivariant multivariate location estimate with high efficiency. This estimate has a bounded influence function but zero breakdown. The computation of the estimate appears to be highly intensive. We consider different, exact and stochastic, algorithms for the calculation of the value of the estimate. In the stochastic algorithms, the gradient of the objective function, the rank function, is estimated by sampling observation. hyperplanes. The estimated rank function with its estimated accuracy then yields a confidence region for the true sample Oja median, and the confidence region shrinks to the sample median with the increasing number of…

MuTE: a MATLAB toolbox to compare established and novel estimators of the multivariate transfer entropy.

2014

A challenge for physiologists and neuroscientists is to map information transfer between components of the systems that they study at different scales, in order to derive important knowledge on structure and function from the analysis of the recorded dynamics. The components of physiological networks often interact in a nonlinear way and through mechanisms which are in general not completely known. It is then safer that the method of choice for analyzing these interactions does not rely on any model or assumption on the nature of the data and their interactions. Transfer entropy has emerged as a powerful tool to quantify directed dynamical interactions. In this paper we compare different ap…