Search results for "Parametric statistics"
showing 10 items of 354 documents
A reanalysis of the center for epidemiological studies depression scale (CES-D) using non-parametric item response theory
2020
Abstract The “Center for Epidemiological Studies Depression Scale” (CES-D; Radloff, 1977 ) is a questionnaire used world-wide to measure depressive symptoms. Although the original four-factor-structure has been widely accepted and replicated, some studies point to other factor-structures like a one- and two-factor-structure. The goal of the current study was to evaluate the factor structure of the CES-D (one-, two- and four-factor-structure), which was found using classical test theory (CTT), with two non-parametric item-response-theory-models (Mokken-Scaling; Monotone-homogeneity-model; MHM and Double-monotonicity-model; DMM). To this end, a representative German sample was analyzed (N = 2…
Stochastic linearization of MDOF systems under parametric excitations
1992
Abstract The stochastic linearization approach is examined for non-linear systems subjected to parametric type excitations. It is shown that, for these systems too, stochastic linearization and Gaussian closure are two equivalent approaches if the former is applied to the coefficients of the Ito differential rule. A critical review of other stochastic linearization approaches is also presented and discussed by means of simple examples.
Non-linear oscillators under parametric and external poisson pulses
1994
The extended Ito calculus for non-normal excitations is applied in order to study the response behaviour of some non-linear oscillators subjected to Poisson pulses. The results obtained show that the non-normality of the input can strongly affect the response, so that, in general, it can not be neglected.
Contribution to modeling the viscosity Arrhenius-type equation for some solvents by statistical correlations analysis
2014
Abstract Estimation and knowledge of transport properties of fluids are essential for heat and mass flow. Viscosity is one of the important properties which are affected by temperature and pressure. In the present work, based on the use of econometric and statistical techniques for parametric and non-parametric regression analysis and statistical correlation tests, we propose an equation modeling the relationship between the two parameters of viscosity Arrhenius-type equation, such as the Arrhenius energy ( E a ) or the pre-exponential factor ( A s ). In addition, we introduce a third interesting parameter called Arrhenius temperature ( T A ), to enrich the discussion. Empirical validation …
A Review of Kernel Methods in Remote Sensing Data Analysis
2011
Kernel methods have proven effective in the analysis of images of the Earth acquired by airborne and satellite sensors. Kernel methods provide a consistent and well-founded theoretical framework for developing nonlinear techniques and have useful properties when dealing with low number of (potentially high dimensional) training samples, the presence of heterogenous multimodalities, and different noise sources in the data. These properties are particularly appropriate for remote sensing data analysis. In fact, kernel methods have improved results of parametric linear methods and neural networks in applications such as natural resource control, detection and monitoring of anthropic infrastruc…
An Application of Hybrid Models in Credit Scoring
2000
The predictive capability of parametric and non-parametric models in solving problems related to financial classification has been widely proved in empirical research carried out in the financial field, particulary in problems like bond rating, bankruptcy prediction and credit scoring. However, recently, it has been shown that a combination of different models generally reduces the prediction error, so that the best alternative to consider may not be a specific model but a combination of them. In this paper, we study hybrid systems based on the aggregation of individual (parametric and nonparametric) models. Our hybrids are built by using both parametric and non parametric models as the sys…
Parametric and nonparametric A-Laplace problems: Existence of solutions and asymptotic analysis
2021
We give sufficient conditions for the existence of weak solutions to quasilinear elliptic Dirichlet problem driven by the A-Laplace operator in a bounded domain Ω. The techniques, based on a variant of the symmetric mountain pass theorem, exploit variational methods. We also provide information about the asymptotic behavior of the solutions as a suitable parameter goes to 0 + . In this case, we point out the existence of a blow-up phenomenon. The analysis developed in this paper extends and complements various qualitative and asymptotic properties for some cases described by homogeneous differential operators.
Analysis of the authors’ rights collection frontier using PCA-MDEA: an application to the Valencia region
2002
The aim of this paper is to estimate the authors’ rights collection frontier within the collection zones into which the Valencia Region (Spain) has been divided. To be more exact, a nonparametric frontier technique (Modified Data Envelopment Analysis, MDEA) and the Principal Components Analysis (PCA) are jointly employed to map out an initial approach to the potential authors’ rights collection within this region (as divided into collection zones). The analysis has been carried out both jointly and by majority sectors (performing, musical, and audio-visual arts). Publicaciones Econcult: Área de Investigación en Economía de la Cultura y Turismo. Universitat de València
Finding Prediction Limits for a Future Number of Failures in the Prescribed Time Interval under Parametric Uncertainty
2012
Computing prediction intervals is an important part of the forecasting process intended to indicate the likely uncertainty in point forecasts. Prediction intervals for future order statistics are widely used for reliability problems and other related problems. In this paper, we present an accurate procedure, called ‘within-sample prediction of order statistics', to obtain prediction limits for the number of failures that will be observed in a future inspection of a sample of units, based only on the results of the first in-service inspection of the same sample. The failure-time of such units is modeled with a two-parameter Weibull distribution indexed by scale and shape parameters β and δ, …
Low-complexity AoA and AoD Estimation in the Transformed Spatial Domain for Millimeter Wave MIMO Channels
2021
High-accuracy angle of arrival (AoA) and angle of departure (AoD) estimation is critical for cell search, stable communications and positioning in millimeter wave (mmWave) cellular systems. Moreover, the design of low-complexity AoA/AoD estimation algorithms is also of major importance in the deployment of practical systems to enable a fast and resource-efficient computation of beamforming weights. Parametric mmWave channel estimation allows to describe the channel matrix as a combination of direction-dependent signal paths, exploiting the sparse characteristics of mmWave channels. In this context, a fast Transformed Spatial Domain Channel Estimation (TSDCE) algorithm was recently proposed …