Search results for "autocorrelation"
showing 10 items of 146 documents
Exploratory spatial data analysis of the distribution of regional per capita GDP in Europe, 1980-1995
2000
The aim of this paper is to study the dynamics of European regional per capita product over time and space. This purpose is achieved by using the recently developed methods of Exploratory Spatial Data Analysis. Using a sample of European regions over the 1980-1995 period, we find strong evidence of global and local spatial autocorrelation in per capita GDP throughout the period. The detection of clusters of high and low per capita products during the period is an indication of the persistence of spatial disparities between European regions. This analysis is finally refined by the investigation of the spatial pattern of regional growth. Key words:exploratory spatial data analysis; distributi…
Econométrie spatiale (2, Hétérogénéité spatiale)
2000
Spatial econometric methods aim at taking into account the two special characteristics of spatial data: spatial autocorrelation, which is the lack of independence between geographical observations, and spatial heterogeneity, which is related to the differentiation of variables and behaviors in space. These techniques have been mostly developed the last ten years and are more often applied in empirical studies with geographical data. The aim of this article is to present the way spatial autocorrelation and spatial heterogeneity can be incorporated in regression relationships and to present the estimation and inference procedures adapted to the models incorporating these two effects. This art…
Convergence of European regions (an approach by spatial econometrics)
2000
The aim of this paper is the analysis of spatial dependence in convergence processes applied to European regions. First, we apply the recently developed exploratory spatial data analysis (Anselin, 1996) in order to describe more precisely the geographical dynamics of European regional income growth patterns. New insights are brought to the usual cr-convergence measure, which hides geographical patterns that may fluctuate over time. Second, we test the presence of spatial autocorrelation in /^-convergence models by using spatial econometrics methods (Anselin, 1988 ; Anselin and Florax, 1995). We compare the results with and without spatial autocorrelation in order to assess the effect of geo…
Spatial autocorrelation and the selection of simultaneous autoregressive models
2007
Aim Spatial autocorrelation is a frequent phenomenon in ecological data and can affect estimates of model coefficients and inference from statistical models. Here, we test the performance of three different simultaneous autoregressive (SAR) model types (spatial error = SAR err , lagged = SAR lag and mixed = SAR mix ) and common ordinary least squares (OLS) regression when accounting for spatial autocorrelation in species distribution data using four artificial data sets with known (but different) spatial autocorrelation structures. Methods We evaluate the performance of SAR models by examining spatial patterns in model residuals (with correlograms and residual maps), by comparing model para…
Remote Photoplethysmography measurement using constrained ICA
2017
Remote Photoplethysmography (rPPG) is a technique that consists in estimating physiological parameters such as heart rate from live or recorded video sequences taken by conventional camera or even webcams. This technique is increasingly used in many application fields thanks to its simplicity and affordability. The basic idea is that the arterial blood flow shows regularity due to the heartbeat. This regularity is manifested by very small periodic variations in the color of the skin, which can be isolated and quantified by signal and image processing methods. In this context, Independent Component Analysis (ICA) is largely used to separate the signal due to arterial flow from signals from o…
The resemblance of an autocorrelation function to a power spectrum density for a spike train of an auditory model
2013
In this work we develop an analytical approach for calculation of the all-order interspike interval density (AOISID), show its connection with the autocorrelation function, and try to explain the discovered resemblance of AOISID to the power spectrum of the same spike train.
Inverse Scattering Solutions with Applications to Electromagnetic Signal Processing
2009
When a signal is recorded that has been physically generated by some scattering process (the interaction of electromagnetic, acoustic or elastic waves with inhomogeneous materials, for example), the ‘standard model’ for the signal (i.e. information content convolved with a characteristic Impulse Response Function) is usually based on a single scattering approximation. An additive noise term is introduced into the model to take into account a range of non-deterministic factors including multiple scattering that, along with electronic noise and other background noise sources, is assumed to be relatively weak. Thus, the standard model is based on a ‘weak field condition’ and the inverse scatte…
Model reduction techniques for the computation of extended Markov parameterizations for generalized Langevin equations
2021
Abstract The generalized Langevin equation is a model for the motion of coarse-grained particles where dissipative forces are represented by a memory term. The numerical realization of such a model requires the implementation of a stochastic delay-differential equation and the estimation of a corresponding memory kernel. Here we develop a new approach for computing a data-driven Markov model for the motion of the particles, given equidistant samples of their velocity autocorrelation function. Our method bypasses the determination of the underlying memory kernel by representing it via up to about twenty auxiliary variables. The algorithm is based on a sophisticated variant of the Prony metho…
Smart load prediction analysis for distributed power network of Holiday Cabins in Norwegian rural area
2020
Abstract The Norwegian rural distributed power network is mainly designed for Holiday Cabins with limited electrical loading capacity. Load prediction analysis, within such type of network, is necessary for effective operation and to manage the increasing demand of new appliances (e. g. electric vehicles and heat pumps). In this paper, load prediction of a distributed power network (i.e. a typical Norwegian rural area power network of 125 cottages with 478 kW peak demand) is carried out using regression analysis techniques for establishing autocorrelations and correlations among weather parameters and occurrence time in the period of 2014–2018. In this study, the regression analysis for loa…
An improved method for estimating the frequency correlation function
2012
For time-invariant frequency-selective channels, the transfer function is a superposition of waves having different propagation delays and path gains. In order to estimate the frequency correlation function (FCF) of such channels, the frequency averaging technique can be utilized. The obtained FCF can be expressed as a sum of auto-terms (ATs) and cross-terms (CTs). The ATs are caused by the autocorrelation of individual path components. The CTs are due to the cross-correlation of different path components. These CTs have no physical meaning and leads to an estimation error. We propose a new estimation method aiming to improve the estimation accuracy of the FCF of a band-limited transfer fun…