Search results for "efficien"
showing 10 items of 3014 documents
Characterization of the parameters of interior permanent magnet synchronous motors for a loss model algorithm
2017
Abstract The paper provides the results of a detailed experimental study on the variations of the characteristics of an interior permanent magnet synchronous motor, when load, speed and/or magnetization conditions vary. In particular, the characterization is carried out by assessing, for several working conditions, the motor parameters that influence its efficiency. From the knowledge of the variability of these parameters, it is possible to develop a dynamic model of the motor, which accurately describes its behaviour and allows estimating the power losses for whatever speed and load. In order to validate the model, the values of the power losses obtained by using the model are compared wi…
Subject-specific odds ratios in binomial GLMMs with continuous response
2007
In a regression context, the dichotomization of a continuous outcome variable is often motivated by the need to express results in terms of the odds ratio, as a measure of association between the response and one or more risk factors. Starting from the recent work of Moser and Coombs (Odds ratios for a continuous outcome variable without dichotomizing, Statistics in Medicine, 2004, 23, 1843-1860), in this article we explore in a mixed model framework the possibility of obtaining odds ratio estimates from a regression linear model without the need of dichotomizing the response variable. It is shown that the odds ratio estimators derived from a linear mixed model outperform those from a binom…
Extended differential geometric LARS for high-dimensional GLMs with general dispersion parameter
2018
A large class of modeling and prediction problems involves outcomes that belong to an exponential family distribution. Generalized linear models (GLMs) are a standard way of dealing with such situations. Even in high-dimensional feature spaces GLMs can be extended to deal with such situations. Penalized inference approaches, such as the $$\ell _1$$ or SCAD, or extensions of least angle regression, such as dgLARS, have been proposed to deal with GLMs with high-dimensional feature spaces. Although the theory underlying these methods is in principle generic, the implementation has remained restricted to dispersion-free models, such as the Poisson and logistic regression models. The aim of this…
Phase transformation kinetics in d-dimensional grains-containing systems: diffusion-type model
1998
Abstract An analytical approach to the phase transformation in d-dimensional grains-containing complex systems is offered. It is based on considering the mechanism of surface material exchange among neighbouring grains as the so-called state-dependent diffusion process, where the diffusion function is related to the magnitude of the grain boundary. The approach proposed deals with the kinetics of that ensemble under circumstances of a volume increase of the new phase or microstructure. Probabilistic characteristics of the process are derived and analyzed. A comparison with 2D modelling of similar kind is presented for the 3D case, and some possible practical realizations of the situation un…
Robust estimation and inference for bivariate line-fitting in allometry.
2011
In allometry, bivariate techniques related to principal component analysis are often used in place of linear regression, and primary interest is in making inferences about the slope. We demonstrate that the current inferential methods are not robust to bivariate contamination, and consider four robust alternatives to the current methods -- a novel sandwich estimator approach, using robust covariance matrices derived via an influence function approach, Huber's M-estimator and the fast-and-robust bootstrap. Simulations demonstrate that Huber's M-estimators are highly efficient and robust against bivariate contamination, and when combined with the fast-and-robust bootstrap, we can make accurat…
Accounting for previous events to model and predict traffic accidents at the road segment level: A study in Valencia (Spain)
2022
Abstract Predicting the occurrence of traffic accidents is essential for establishing preventive measures and reducing the impact of traffic accidents. In particular, it is fundamental to make predictions using fine spatio-temporal units. In this paper, the daily risk of traffic accident occurrence across the road network of Valencia (Spain) is modeled through logistic regression models. The spatio-temporal dependence between the observations is accounted for through the inclusion of lagged binary covariates representing the previous occurrence of a traffic accident within a spatio-temporal window centered at each combination of day and segment of the network. A temporal distance of 28 days…
k-Step shape estimators based on spatial signs and ranks
2010
In this paper, the shape matrix estimators based on spatial sign and rank vectors are considered. The estimators considered here are slight modifications of the estimators introduced in Dümbgen (1998) and Oja and Randles (2004) and further studied for example in Sirkiä et al. (2009). The shape estimators are computed using pairwise differences of the observed data, therefore there is no need to estimate the location center of the data. When the estimator is based on signs, the use of differences also implies that the estimators have the so called independence property if the estimator, that is used as an initial estimator, has it. The influence functions and limiting distributions of the es…
A macroeconomic analysis of the public investments in European combined transport
2009
Intermodal transport has been recognized as a priority by the European Union, that has defined different budget allocations of investments to improve the shifting from road to intermodal transport, which is more sustainable. In this context, the main aim of the paper is to discuss the macroeconomic effects, in terms of economic growth, welfare and trade, of these public investments for combined transport, which aspects have been neglected in literature. A multi-country computable general equilibrium model has been used. The main results have been that the European Union benefits from these investments, but at international level, USA and Japan would lose in terms of welfare. Furthermore, th…
Tests of multinormality based on location vectors and scatter matrices
2007
Classical univariate measures of asymmetry such as Pearson’s (mean-median)/σ or (mean-mode)/σ often measure the standardized distance between two separate location parameters and have been widely used in assessing univariate normality. Similarly, measures of univariate kurtosis are often just ratios of two scale measures. The classical standardized fourth moment and the ratio of the mean deviation to the standard deviation serve as examples. In this paper we consider tests of multinormality which are based on the Mahalanobis distance between two multivariate location vector estimates or on the (matrix) distance between two scatter matrix estimates, respectively. Asymptotic theory is develop…
Fractal eigenstates in disordered systems
1990
Abstract The wave functions of the non-interacting electrons in disordered systems described by a tight-binding model with site-diagonal disorder are investigated by means of the inverse participation ratio. The wave functions are shown to be fractal objects. In three-dimensional samples, a critical fractal dimension can be defined for the mobility edge in the band centre, which yields the mobility edge trajectory in the whole energy range in good agreement with previous calculations based on the investigation of the exponentially decaying transmission coefficient.