Search results for "Parametric statistics"
showing 10 items of 354 documents
A data analysis approach to evaluate the impact of the capacity utilization on the energy consumption of wastewater treatment plants
2019
Abstract The reduction of energy consumption in Waste Water Treatment Plants (WWTPs) is a challenge for the scientific community and for the public authorities. A source of excessive energy cost is the mismatching between operational and design inflow (i.e. capacity utilization): this issue is very relevant above all in areas with high demographic seasonality. Consequently, it is really important to have operational decision criteria to evaluate the impact of a low capacity utilization on energy consumption. In order to provide the scientific community and the plant managers with an adequate criterion, we propose a user-friendly methodology to identify critical conditions of capacity utiliz…
A Sample Selection Model for Unit and Item Nonresponse in Cross-Sectional Surveys
2007
We consider a general sample selection model where unit and item nonresponse simultaneously affect a regression relationship of interest, and both types of nonresponse are potentially correlated. We estimate both parametric and semiparametric specifications of the model. The parametric specification assumes that the errors in the latent regression equations follow a trivariate Gaussian distribution. The semiparametric specification avoids distributional assumptions about the underlying regression errors. In our empirical application, we estimate Engel curves for consumption expenditure using data from the first wave of SHARE (Survey on Health, Aging and Retirement in Europe).
Adaptive backstepping based consensus tracking of uncertain nonlinear systems with event-triggered communication
2021
Abstract This paper investigates the consensus tracking problem for a class of uncertain high-order nonlinear systems with parametric uncertainties and event-triggered communication. Under a directed communication condition, a totally distributed adaptive backstepping based control scheme is presented. Specifically, a decentralized triggering condition is adopted in this paper such that continuous monitoring of neighboring states, as required in some existing results, can be avoided. Besides, to handle the non-differentiability problem of virtual controllers, which arises from the utilization of neighboring states collected only at the triggering instants, the virtual controllers in each re…
Segmentation algorithm for non-stationary compound Poisson processes
2010
We introduce an algorithm for the segmentation of a class of regime switching processes. The segmentation algorithm is a non parametric statistical method able to identify the regimes (patches) of a time series. The process is composed of consecutive patches of variable length. In each patch the process is described by a stationary compound Poisson process, i.e. a Poisson process where each count is associated with a fluctuating signal. The parameters of the process are different in each patch and therefore the time series is non-stationary. Our method is a generalization of the algorithm introduced by Bernaola-Galván, et al. [Phys. Rev. Lett. 87, 168105 (2001)]. We show that the new algori…
Experimental approach for testing the uncoupling between cardiovascular variability series
2002
In cardiovascular variability analysis, the significance of the coupling between two series is commonly assessed by defining a zero level on the magnitude-squared coherence (MSC). Although the use of the conventional value of 0.5 does not consider the dependence of MSC estimates on the analysis parameters, a theoretical threshold Tt is available only for the weighted covariance (WC) estimator. In this study, an experimental threshold for zero coherence Te was derived by a statistical test from the sampling distribution of MSC estimated on completely uncoupled time series. MSC was estimated by the WC method (Parzen window, spectral bandwidth B = 0.015, 0.02, 0.025, 0.03 Hz) and by the parame…
A comparison of local parametric C0 Bézier interpolants for triangular meshes
2011
Parametric curved shape surface schemes interpolating vertices and normals of a given triangular mesh with arbitrary topology are widely used in computer graphics for gaming and real-time rendering due to their ability to effectively represent any surface of arbitrary genus. In this context, continuous curved shape surface schemes using only the information related to the triangle corresponding to the patch under construction, emerged as attractive solutions responding to the requirements of resource-limited hardware environments. In this paper we provide a unifying comparison of the local parametric C^0 curved shape schemes we are aware of, based on a reformulation of their original constr…
Nonparametric statistics for DOA estimation in the presence of multipath
2002
This paper is concerned with array signal processing in nonGaussian noise and in the presence of multipath. Robust and fully nonparametric high resolution algorithms for direction of arrival (DOA) estimation are presented. The algorithms are based on multivariate spatial sign and rank concepts. Spatial smoothing of the multivariate rank and sign based covariance matrices is employed as a preprocessing step in order to deal with coherent sources. The performance of the algorithms is studied using simulations. The results show that almost optimal performance is obtained in wide variety of different noise conditions.
Support Vector Machines Framework for Linear Signal Processing
2005
This paper presents a support vector machines (SVM) framework to deal with linear signal processing (LSP) problems. The approach relies on three basic steps for model building: (1) identifying the suitable base of the Hilbert signal space in the model, (2) using a robust cost function, and (3) minimizing a constrained, regularized functional by means of the method of Lagrange multipliers. Recently, autoregressive moving average (ARMA) system identification and non-parametric spectral analysis have been formulated under this framework. The generalized, yet simple, formulation of SVM LSP problems is particularized here for three different issues: parametric spectral estimation, stability of I…
Robust subspace DOA estimation for wireless communications
2002
This paper is concerned with array signal processing in non-Gaussian noise typical in urban and indoor radio channels. Robust and fully nonparametric high resolution algorithms for direction of arrival (DOA) estimation are presented. The algorithms are based on multivariate spatial sign and rank concepts. The performance of the algorithms is studied using simulations. The results show that almost optimal performance is obtained in wide variety of noise conditions.