Search results for "Multivariate analysis"

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…

T-patterns in the study of movement and behavioral disorders

2020

Aim of the present review is to offer an outline of the application of T-pattern analysis (TPA) in the study of neurological disorders characterized by anomalies of movement and, more in general, of behavior. TPA is a multivariate technique to detect real time patterns of behavior on the basis of statistically significant constraints among the events in sequence. TPA is particularly suitable to analyse the structure of behavior. The application of TPA to study movement and behavioral disorders is able to offer, with a high level of detail, hidden characteristics of behavior otherwise impossible to detect. For its intrinsic features, TPA is completely different not only from quantitative eva…

Multivariate approach to reveal relationships between sensory perception of cheeses and aroma profile obtained with different extraction methods

2014

A new and original statistical approach was used to compare the effectiveness of 4 different methods to analyse aroma compounds of seven different commercial semi-hard cheeses with regard to their orthonasal sensory perception. Four extraction methods were evaluated: Purge and Trap, Artificial Mouth, Solid-Phase Microextraction (SPME) and Solvent-Assisted Flavour Evaporation (SAFE). Among the headspace methods, Artificial Mouth gave the closest representation of the studied product space to the sensory perception one. The SAFE method was complementary to the dynamic headspace methods, as it was very efficient in extracting the heavy molecules but less efficient for extracting the most volat…

Non-uniform multivariate embedding to assess the information transfer in cardiovascular and cardiorespiratory variability series

2012

The complexity of the short-term cardiovascular control prompts for the introduction of multivariate (MV) nonlinear time series analysis methods to assess directional interactions reflecting the underlying regulatory mechanisms. This study introduces a new approach for the detection of nonlinear Granger causality in MV time series, based on embedding the series by a sequential, non-uniform procedure, and on estimating the information flow from one series to another by means of the corrected conditional entropy. The approach is validated on short realizations of linear stochastic and nonlinear deterministic processes, and then evaluated on heart period, systolic arterial pressure and respira…

Detecting nonlinear causal interactions between dynamical systems by non-uniform embedding of multiple time series.

2010

This study introduces a new approach for the detection of nonlinear Granger causality between dynamical systems. The approach is based on embedding the multivariate (MV) time series measured from the systems X and Y by means of a sequential, non-uniform procedure, and on using the corrected conditional entropy (CCE) as unpredictability measure. The causal coupling from X to Y is quantified as the relative decrease of CCE measured after allowing the series of X to enter the embedding procedure for the description of Y. The ability of the approach to quantify nonlinear causality is assessed on MV time series measured from simulated dynamical systems with unidirectional coupling (the Rössler-…

A multivariate statistical approach of X-ray fluorescence characterization of a large collection of reverse glass paintings

2019

We present an X-ray fluorescence spectroscopy (XRF) study combined with a multivariate approach that allow to detect compositional differences and similarities among the glass supports of a large set of reverse glass paintings belonging to the collection of the Mistretta museum. Reverse painting on glass is an old decorative technique used since the Roman time consisting in applying a cold paint layer on the reverse side of a glass support. The collection shows a large spreading of provenience and dating of the items. In consideration of the current classification solely based on stylistic criteria, we applied a multivariate analysis on the XRF measurements data set to find a more objective…