Parametric Models
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منابع مشابه
Evaluation Approaches of Value at Risk for Tehran Stock Exchange
The purpose of this study is estimation of daily Value at Risk (VaR) for total index of Tehran Stock Exchange using parametric, nonparametric and semi-parametric approaches. Conditional and unconditional coverage backtesting are used for evaluating the accuracy of calculated VaR and also to compare the performance of mentioned approaches. In most cases, based on backtesting statistics Results, ...
متن کاملمقایسه مدل شبکه عصبی مصنوعی و رگرسیون پارامتری در پیش‌بینی بقای بیماران مبتلا به سرطان معده
Background & Objective: Using parametric models is common approach in survival analysis. In the recent years, artificial neural network (ANN) models have increasingly used in survival prediction. The aim of this study was to predict of survival rate of patients with gastric cancer by using a parametric regression and ANN models and compare these methods. Methods: We used the data of 436 gast...
متن کاملThe Negative Binomial Distribution Efficiency in Finite Mixture of Semi-parametric Generalized Linear Models
Introduction Selection the appropriate statistical model for the response variable is one of the most important problem in the finite mixture of generalized linear models. One of the distributions which it has a problem in a finite mixture of semi-parametric generalized statistical models, is the Poisson distribution. In this paper, to overcome over dispersion and computational burden, finite ...
متن کاملEvaluation of Survival Analysis Models for Predicting Factors Infuencing the Time of Brucellosis Diagnosis
Background:Brucellosis or Malta fever is one of the most common zoonotic diseases in the world. In addition to causing human suffering and dire economic impact on animals, due to the high prevalence of Brucellosis in the western regions of Isfahan province, this study aimed to analyze effective factors in the time of Brucellosis diagnosis using parametric and semi-parametric mo...
متن کاملIntroducing of Dirichlet process prior in the Nonparametric Bayesian models frame work
Statistical models are utilized to learn about the mechanism that the data are generating from it. Often it is assumed that the random variables y_i,i=1,…,n ,are samples from the probability distribution F which is belong to a parametric distributions class. However, in practice, a parametric model may be inappropriate to describe the data. In this settings, the parametric assumption could be r...
متن کاملمقایسه رگرسیون کاکس و مدل های پارامتریک در تحلیل بقای بیماران مبتلا به سرطان معده
Background & Objectives: Although Cox regression is commonly used to detect relationships between patient survival and demographic/clinical variables, there are situations where parametric models can yield more accurate results. The objective of this study was to compare two survival regression methods, namely Cox regression and parametric models, in patients with gastric carcinoma registered a...
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