[Home ] [Archive]    
:: Volume 10, Issue 1 (9-2013) ::
JSRI 2013, 10(1): 41-62 Back to browse issues page
Analysis of Record Data from the Scaled Logistic Distribution
A. Asgharzadeh *1, M. Abdi, R. Valiollahi
1- , a.asgharzadeh@umz.ac.ir
Abstract:   (3440 Views)

In this paper, we consider the estimation of the unknown parameter of the scaled logistic distribution on the basis of record values. The maximum likelihood method does not provide an explicit estimator for the scale parameter. In this article, we present a simple method of deriving an explicit estimator by approximating the likelihood function. Bayes estimator is obtained using importance sampling. Asymptotic confidence intervals, bootstrap confidence interval and credible interval are also proposed. Monte Carlo simulations are performed to compare the different proposed methods. Analysis of one real data set is also given for illustrative purposes.

Keywords: Bayes estimation, maximum likelihood estimation, Monte Carlo simulation, record values, importance sampling
Full-Text [PDF 228 kb]   (1295 Downloads)    
Type of Study: Research | Subject: General
Received: 2015/12/21 | Accepted: 2015/12/21 | Published: 2015/12/21
Send email to the article author

Add your comments about this article
Your username or Email:


XML   Persian Abstract   Print

Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Asgharzadeh A, Abdi M, valiollahi R. Analysis of Record Data from the Scaled Logistic Distribution . JSRI. 2013; 10 (1) :41-62
URL: http://jsri.srtc.ac.ir/article-1-54-en.html

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 10, Issue 1 (9-2013) Back to browse issues page
مجله‌ی پژوهش‌های آماری ایران Journal of Statistical Research of Iran JSRI
Persian site map - English site map - Created in 0.04 seconds with 29 queries by YEKTAWEB 4447