Search results for "regressive models"

Spectral decomposition of cerebrovascular and cardiovascular interactions in patients prone to postural syncope and healthy controls.

2022

We present a framework for the linear parametric analysis of pairwise interactions in bivariate time series in the time and frequency domains, which allows the evaluation of total, causal and instantaneous interactions and connects time- and frequency-domain measures. The framework is applied to physiological time series to investigate the cerebrovascular regulation from the variability of mean cerebral blood flow velocity (CBFV) and mean arterial pressure (MAP), and the cardiovascular regulation from the variability of heart period (HP) and systolic arterial pressure (SAP). We analyze time series acquired at rest and during the early and late phase of head-up tilt in subjects developing or…

The effectiveness of the autoregressive models in forecasting the agricultural prices in Poland

2010

The forecast of agricultural prices is one of the most important factors in making decision on production farms. The appropriate forecast allows for limiting the risk connected with one’s economic activity. In this study autoregressive models have been used, which helped to determine the price forecast for agricultural products in the purchasing centers in the second half of 2010. To determine the quality of forecast the average ex-post errors of the past forecasts have been used. The achieved results show that autoregressive models are an effective tool in forecasting the agricultural prices in Poland.

Mathematical modeling and parameters estimation of a car crash using data-based regressive model approach

2011

Author's version of an article in the journal: Applied Mathematical Modelling. Also available from the publisher at: http://dx.doi.org/10.1016/j.apm.2011.04.024 n this paper we present the application of regressive models to simulation of car-to-pole impacts. Three models were investigated: RARMAX, ARMAX and AR. Their suitability to estimate physical system parameters as well as to reproduce car kinematics was examined. It was found out that they not only estimate the one quantity which was used for their creation (car acceleration) but also describe the car's acceleration, velocity and crush. A virtual experiment was performed to obtain another set of data for use in further research. An A…

A framework for assessing frequency domain causality in physiological time series with instantaneous effects.

2013

We present an approach for the quantification of directional relations in multiple time series exhibiting significant zero-lag interactions. To overcome the limitations of the traditional multivariate autoregressive (MVAR) modelling of multiple series, we introduce an extended MVAR (eMVAR) framework allowing either exclusive consideration of time-lagged effects according to the classic notion of Granger causality, or consideration of combined instantaneous and lagged effects according to an extended causality definition. The spectral representation of the eMVAR model is exploited to derive novel frequency domain causality measures that generalize to the case of instantaneous effects the kno…

Stochastic analysis of motorcycle dynamics

2011

Off-road and racing motorcycles require a particular setup of the suspensions to improve the comfort and the safety of the rider, maintaining a continuous contact between the road and the motorcycle (by means of the tires). Further, because of the ground roughness, in the case of offroad motorcycle, suspensions usually experience extreme and erratic excursions (suspension stroke) in performing their function. In this regard, the adoption of nonlinear devices can, perhaps, limit both the acceleration experienced by the sprung mass and the excursions of the suspensions. This leads to the consideration of asymmetric nonlinearly-behaving suspensions. This option, however, induces the difficulty…

On the interpretability and computational reliability of frequency-domain Granger causality

2017

This Correspondence article is a comment which directly relates to the paper “A study of problems encountered in Granger causality analysis from a neuroscience perspective” (Stokes and Purdon, 2017). We agree that interpretation issues of Granger causality (GC) in neuroscience exist, partially due to the historically unfortunate use of the name “causality”, as described in previous literature. On the other hand, we think that Stokes and Purdon use a formulation of GC which is outdated (albeit still used) and do not fully account for the potential of the different frequency-domain versions of GC; in doing so, their paper dismisses GC measures based on a suboptimal use of them. Furthermore, s…

Multivariate autoregressive model with instantaneous effects to improve brain connectivity estimation

2009

Comparative Economic Cycles

2008

The income cycles that have been experienced by six OECD countries over the past 24 years are analysed. The amplitude of the cycles relative to the level of aggregate income varies amongst the countries, as does the degree of the damping that affects the cycles. The study aims to reveal both of these characteristics. It also seeks to determine whether there exists a clear relationship between the degree of damping and the length of the cycles. In order to estimate the parameters of the cycles, the data have been subjected to the processes of detrending, anti-alias filtering and subsampling.

Recursion at the crossroads of sequence modeling, random trees, stochastic algorithms and martingales

2013

This monograph synthesizes several studies spanning from dynamical systems in the statistical analysis of sequences, to analysis of algorithms in random trees and discrete stochastic processes. These works find applications in various fields ranging from biological sequences to linear regression models, branching processes, through functional statistics and estimates of risk indicators for insurances. All the established results use, in one way or another, the recursive property of the structure under study, by highlighting invariants such as martingales, which are at the heart of this monograph, as tools as well as objects of study.

Multiscale Information Decomposition: Exact Computation for Multivariate Gaussian Processes

2017

Exploiting the theory of state space models, we derive the exact expressions of the information transfer, as well as redundant and synergistic transfer, for coupled Gaussian processes observed at multiple temporal scales. All of the terms, constituting the frameworks known as interaction information decomposition and partial information decomposition, can thus be analytically obtained for different time scales from the parameters of the VAR model that fits the processes. We report the application of the proposed methodology firstly to benchmark Gaussian systems, showing that this class of systems may generate patterns of information decomposition characterized by prevalently redundant or sy…