Search results for "multivariate statistic"

Multivariate Exploratory Comparative Analysis of LaLiga Teams: Principal Component Analysis

2021

The use of principal component analysis (PCA) provides information about the main characteristics of teams, based on a set of indicators, instead of displaying individualized information for each of these indicators. In this work we have considered reducing an extensive data matrix to improve interpretation, using PCA. Subsequently, with new components and with multiple linear regression, we have carried out a comparative analysis between the best and bottom teams of LaLiga. The sample consisted of the matches corresponding to the 2015/16, 2016/17 and 2017/18 seasons. The results showed that the best teams were characterized and differentiated from bottom teams in the realization of a great…

Different Representation Procedures Originated from Multivariate Temporal Pattern Analysis of the Behavioral Response to Pain in Wistar Rats Tested i…

2019

Temporal pattern analysis is an advanced multivariate technique able to investigate the structure of behavior by unveiling the existence of statistically significant constraints among the interval length separating events in sequence. If on the one hand, such an approach allows investigating the behavioral response to pain in its most intimate and inner features, on the other hand, due to the meaning of the studies on pain, it is of relevant importance that the results utilize intuitive and easily comprehensible ways of representation. The aim of this paper is to show various procedures useful to represent the results originating from the multivariate T-pattern analysis of the behavioral re…

2018

A comprehensive monitoring of fitness, fatigue, and performance is crucial for understanding an athlete's individual responses to training to optimize the scheduling of training and recovery strategies. Resting and exercise-related heart rate measures have received growing interest in recent decades and are considered potentially useful within multivariate response monitoring, as they provide non-invasive and time-efficient insights into the status of the autonomic nervous system (ANS) and aerobic fitness. In team sports, the practical implementation of athlete monitoring systems poses a particular challenge due to the complex and multidimensional structure of game demands and player and te…

On Mardia’s Tests of Multinormality

2004

Classical multivariate analysis is based on the assumption that the data come from a multivariate normal distribution. The tests of multinormality have therefore received very much attention. Several tests for assessing multinormality, among them Mardia’s popular multivariate skewness and kurtosis statistics, are based on standardized third and fourth moments. In Mardia’s construction of the affine invariant test statistics, the data vectors are first standardized using the sample mean vector and the sample covariance matrix. In this paper we investigate whether, in the test construction, it is advantageous to replace the regular sample mean vector and sample covariance matrix by their affi…

Contribution to the taxonomy of the family Campulidae Odhner, 1926 (Digenea) by means of a morphometric multivariate analysis

1996

Digeneans of the family Campulidae occur exclusively in marine mammals, particularly in cetaceans. Their taxonomy is confused, being based on adult morphology only. We used a multivariate discriminant analysis of morphometric data to provide new evidence on the taxonomy of the Campulidae. Measurements of 217 specimens from 21 species of all seven genera of the family were taken. The percentage of specimens correctly assigned into their own species was 96.3%. The first three discriminant functions accounted for most of the variation between the species, which were grouped together in suprageneric groups along the first and the second function. The ordination pattern observed conforms partly …

A discrete mathematical model for addictive buying: Predicting the affected population evolution

2011

This paper deals with the construction of a discrete mathematical model for addictive buying. Firstly, identifications of consumers buying behavior are performed by using multivariate statistical techniques based on real data bases and sociological approaches. Then the population is divided into appropriate groups according to the level of overbuying and a discrete compartmental model is constructed. The future short term addicted population is computed assuming several future economic scenarios. © 2010 Elsevier Ltd.

Association between odontoma size, age and gender: Multivariate analysis of retrospective data

2019

Background The variety of characteristics related to odontoma research, including an unexplored one such as size, merits a multivariate approach that allows the adequate drawing of inferences with pertinent conclusions. The objective of this study is to establish the possible association between some characteristics related to the odontoma, tumor size among them. Material and methods The sociodemographic characteristics of 60 patients were evaluated. Diagnosis, size, location, type of treatment performed, and prognosis were determined. These data were analyzed descriptively and through multivariate models. Results Thirty-four compound and 26 complex odontomas in 32 men and 28 women were obs…

Directed coherence analysis in patients with severe autonomic dysfunction

2014

Many different approaches have been applied to analyse the coupling between cardiovascular signals. This study evaluated the use of directed coherence, based on multivariate autoregressive modelling, for analysis of cardiovascular signals in patients with transthyretin amyloidosis, a rare disease where severe autonomic dysfunction is common. © 2014 IEEE.

Background Correction and Multivariate Curve Resolution of Online Liquid Chromatography with Infrared Spectrometric Detection

2011

J.K. acknowledges the “V Segles” grant provided by the University of Valencia to carry out this study. Authors acknowledge the financial support of Ministerio de Educación y Ciencia (Projects AGL2007-64567 and CTQ2008-05719/BQU) and Conselleria d'Educació de la Generalitat Valenciana (Project PROMETEO 2010-055).

Algorithms for the inference of causality in dynamic processes: Application to cardiovascular and cerebrovascular variability

2015

This study faces the problem of causal inference in multivariate dynamic processes, with specific regard to the detection of instantaneous and time-lagged directed interactions. We point out the limitations of the traditional Granger causality analysis, showing that it leads to false detection of causality when instantaneous and time-lagged effects coexist in the process structure. Then, we propose an improved algorithm for causal inference that combines the Granger framework with the approach proposed by Pearl for the study of causality among multiple random variables. This new approach is compared with the traditional one in theoretical and simulated examples of interacting processes, sho…