Search results for "Parametric"

Information Dynamics Analysis: A new approach based on Sparse Identification of Linear Parametric Models*

2020

The framework of information dynamics allows to quantify different aspects of the statistical structure of multivariate processes reflecting the temporal dynamics of a complex network. The information transfer from one process to another can be quantified through Transfer Entropy, and under the assumption of joint Gaussian variables it is strictly related to the concept of Granger Causality (GC). According to the most recent developments in the field, the computation of GC entails representing the processes through a Vector Autoregressive (VAR) model and a state space (SS) model typically identified by means of the Ordinary Least Squares (OLS). In this work, we propose a new identification …

On the internal multivariate quality control of analytical laboratories. A case study: the quality of drinking water

2001

Abstract Multivariate statistical process control (MSPC) tools, based on principal component analysis (PCA), partial least squares (PLS) regression and other regression models, are used in the present study for automatic detection of possible errors in the methods used for routine multiparametric analysis in order to design an internal Multivariate Analytical Quality Control (iMAQC) program. Such tools could notice possible failures in the analytical methods without resorting to any external reference since they use their own analytical results as a source for the diagnosis of the method's quality. Pseudo-univariate control charts provide an attractive alternative to traditional univariate …

Measuring Connectivity in Linear Multivariate Processes: Definitions, Interpretation, and Practical Analysis

2011

This tutorial paper introduces a common framework for the evaluation of widely used frequency-domain measures of coupling (coherence, partial coherence) and causality (directed coherence, partial directed coherence) from the parametric representation of linear multivariate (MV) processes. After providing a comprehensive time-domain definition of the various forms of connectivity observed in MV processes, we particularize them to MV autoregressive (MVAR) processes and derive the corresponding frequency-domain measures. Then, we discuss the theoretical interpretation of these MVAR-based connectivity measures, showing that each of them reflects a specific time-domain connectivity definition an…

Multivariate and Multiscale Complexity of Long-Range Correlated Cardiovascular and Respiratory Variability Series

2020

Assessing the dynamical complexity of biological time series represents an important topic with potential applications ranging from the characterization of physiological states and pathological conditions to the calculation of diagnostic parameters. In particular, cardiovascular time series exhibit a variability produced by different physiological control mechanisms coupled with each other, which take into account several variables and operate across multiple time scales that result in the coexistence of short term dynamics and long-range correlations. The most widely employed technique to evaluate the dynamical complexity of a time series at different time scales, the so-called multiscale …

Extended causal modeling to assess Partial Directed Coherence in multiple time series with significant instantaneous interactions.

2010

The Partial Directed Coherence (PDC) and its generalized formulation (gPDC) are popular tools for investigating, in the frequency domain, the concept of Granger causality among multivariate (MV) time series. PDC and gPDC are formalized in terms of the coefficients of an MV autoregressive (MVAR) model which describes only the lagged effects among the time series and forsakes instantaneous effects. However, instantaneous effects are known to affect linear parametric modeling, and are likely to occur in experimental time series. In this study, we investigate the impact on the assessment of frequency domain causality of excluding instantaneous effects from the model underlying PDC evaluation. M…

Rank scores tests of multivariate independence

2004

New rank scores test statistics are proposed for testing whether two random vectors are independent. The tests are asymptotically distribution-free for elliptically symmetric marginal distributions. Recently, Gieser and Randles (1997), Taskinen, Kankainen and Oja (2003) and Taskinen, Oja and Randles (2005) introduced and discussed different multivariate extensions of the quadrant test, Kendall's tau and Spearman's rho statistics. In this paper, standardized multivariate spatial signs and the (univariate) ranks of the Mahalanobis-type distances of the observations from the origin are combined to construct ranks cores tests of independence. The limiting distributions of the test statistics ar…

Non-Parametric Rank Statistics for Spectral Power and Coherence

2019

AbstractDespite advances in multivariate spectral analysis of neural signals, the statistical inference of measures such as spectral power and coherence in practical and real-life scenarios remains a challenge. The non-normal distribution of the neural signals and presence of artefactual components make it difficult to use the parametric methods for robust estimation of measures or to infer the presence of specific spectral components above the chance level. Furthermore, the bias of the coherence measures and their complex statistical distributions are impediments in robust statistical comparisons between 2 different levels of coherence. Non-parametric methods based on the median of auto-/c…

Vector Autoregressive Fractionally Integrated Models to Assess Multiscale Complexity in Cardiovascular and Respiratory Time Series

2020

Cardiovascular variability is the result of the activity of several physiological control mechanisms, which involve different variables and operate across multiple time scales encompassing short term dynamics and long range correlations. This study presents a new approach to assess the multiscale complexity of multivariate time series, based on linear parametric models incorporating autoregressive coefficients and fractional integration. The approach extends to the multivariate case recent works introducing a linear parametric representation of multiscale entropy, and is exploited to assess the complexity of cardiovascular and respiratory time series in healthy subjects studied during postu…

F55. An Image-Based Meta-Analysis of Successful and Failed Stopping in Attention Deficit/Hyperactivity Disorder Using Statistical Parametric Maps

2019

Automated parametric neutronics analysis of the Helium Cooled Pebble Bed breeder blanket with Be 12 Ti

2017

The Helium Cooled Pebble Bed (HCPB) breeder blanket is being developed as part of the European Fusion Programme. Part of the programme is to investigate blanket designs relevant for future demonstration fusion power plants. This paper presents neutronics analyses of the HCPB with an alternative neutron multiplier, Be12Ti which is incorporated into the design, replacing the current Be multiplier. A parameter study was performed for a range of geometries to identify the optimal heights of the lithium ceramic and neutron multiplier pebble beds. Automated creation of CAD models followed by conversion to constructive solid geometry (CSG) and unstructured mesh (UM) geometry allows the models to b…