نتایج جستجو برای: parametric models
تعداد نتایج: 957187 فیلتر نتایج به سال:
In discrete undirected graphical models, the conditional independence of the node labels Y is specified by the graph structure. We study the case where there is another input random vector X (e.g. observed features) such that the distribution P (Y | X) is determined by functions of X that characterize the (higher-order) interactions among the Y ’s. The main contribution is to learn the graph st...
A Bayesian semi-parametric estimation of the binary response model using Markov Chain Monte Carlo algorithms is proposed. The performances of the parametric and semi-parametric models are presented. The mean squared errors, receiver operating characteristic curve, and the marginal effect are used as the model selection criteria. Simulated data and Monte Carlo experiments show that unless the bi...
Nowadays risk management is as vital as gaining the maximum return. Therefore, researches in risk management area and its different models are very useful for the investors. Using a local (fmincon function) and a global optimization (simulated annealing) algorithms based on three risk management models namely Markowitz, Value at Risk (VaR) and Conditional Value at Risk (CVaR), this research see...
Thin plate and spherical splines are nonparametric methods suitable for spatial data analysis. Thin plate splines acquire efficient practical and high precision solutions in spatial interpolations. Two components in the model fitting is considered: spatial deviations of data and the model roughness. On the other hand, in parametric regression, the relationship between explanatory and response v...
Recently, quantile regression (QR) models are often applied for longitudinal data analysis. When the distribution of responses seems to be skew and asymmetric due to outliers and heavy-tails, QR models may work suitably. In this paper, a semi-parametric quantile regression model is developed for analysing continuous longitudinal responses. The error term's distribution is assumed to be Asymmetr...
In most genomic prediction studies only additive effects will be used in models for estimating genomic breeding values (GEBV). However, dominance genetic effects are an important source of variation for complex traits, considering them into account may improve the accuracy of GEBV. In the present study, performed applying simulated data, the effect of different heritability values (0.1...
Software reliability is an important factor for quantitatively characterizing software quality and estimating the duration of software testing period. Traditional parametric software reliability growth models (SRGMs) such as nonhomogeneous Poisson process (NHPP) models have been successfully utilized in practical software reliability engineering. However, no single such parametric model can obt...
This study examines the technical efficiency of the electricity generation companies in a deregulated electricity market. Two approaches are used – parametric and non-parametric. Parametric models show that there exist high levels of efficiency among the generation firms; the lowest score is 99.83%, after accounting for noise. While non-parametric models do not give efficiency scores as high as...
This paper introduces basic elements of systems engineering that are useful in managing the product lifecycle, as expressed in an extension to the Unified Modeling Language. It presents models of product requirements for capturing stakeholder needs, system structure for defining the static relations of its elements, behaviour for the transformation of inputs to outputs, parametrics for constrai...
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