A log-extended Weibull regression model

نویسندگان

  • Giovana Oliveira Silva
  • Edwin M. M. Ortega
  • Gauss M. Cordeiro
چکیده

A bathtub-shaped failure rate function is very useful in survival analysis and reliability studies. The well-known lifetime distributions do not have this property. For the first time, we propose a location-scale regression model based on the logarithm of an extended Weibull distribution which has the ability to deal with bathtub-shaped failure rate functions. We use the method of maximum likelihood to estimate the model parameters and some inferential procedures are presented.We reanalyze a real data set under the new model and the log-modifiedWeibull regressionmodel.Weperformamodel check based on martingale-type residuals and generated envelopes and the statistics AIC and BIC to select appropriate models. © 2009 Elsevier B.V. All rights reserved.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

The Log-exponentiated-Weibull Regression Models with Cure Rate: Local Influence and Residual Analysis

In this paper the log-exponentiated-Weibull regression model is modified to allow the possibility that long term survivors are present in the data. The modification leads to a log-exponentiated-Weibull regression model with cure rate, encompassing as special cases the log-exponencial regression and log-Weibull regression models with cure rate typically used to model such data. The models attemp...

متن کامل

مقایسه مدل کاکس و مدل های پارامتری در برآورد بقاء درمان مبتلایان سرطان پروستات تحت رادیوتراپی

Background and purpose: Prostate cancer is the second most common malignant cancer in men and radiotherapy is one of the treatments for this disease. The aim of this study was to determine the effect of demographic, clinical and pathology factors in survival rate of patients on radiotherapy and comparing different survival models to determine an efficient model. Materials and methods: In a his...

متن کامل

مقایسه 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 کامل

تعیین عوامل موثر بر پیش آگهی بیماران مبتلا به سرطان مری با استفاده از مدل رگرسیون لگ لجستیک

Background and Objectives: Each year almost 400,000 people are diagnosed with oesophageal cancer worldwide. Wide variation in incidence has been reported both between countries and in different ethnic groups and populations within a country. The area with the highest reported incidence for oesophageal cancer is the so-called Asian ‘oesophageal cancer belt’, which stretches from eastern Turkey t...

متن کامل

مقایسه 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...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Computational Statistics & Data Analysis

دوره 53  شماره 

صفحات  -

تاریخ انتشار 2009