Fitting of Twofold Mixed Model for Two-Parameter Weibull Distribution
نویسندگان
چکیده
منابع مشابه
Fitting the Three-parameter Weibull Distribution by using Greedy Randomized Adaptive Search Procedure
The Weibull distribution is widely employed in several areas of engineering because it is an extremely flexible distribution with different shapes. Moreover, it can include characteristics of several other distributions. However, successful usage of Weibull distribution depends on estimation accuracy for three parameters of scale, shape and location. This issue shifts the attentions to the requ...
متن کاملOn nonlinear weighted least squares fitting of the three-parameter inverse Weibull distribution∗
In this paper we consider nonlinear least squares fitting of the three-parameter inverse Weibull distribution to the given data (wi, ti, yi), i = 1, . . . , n, n ≥ 3. As the main result, we show that the least squares estimate exists provided that the data satisfy just the following two natural conditions: (i) 0 < t1 < t2 < . . . < tn and (ii) 0 < y1 < y2 < . . . < yn < 1. To this end, an illus...
متن کاملLeast squares fitting the three - parameter inverse Weibull density ∗
The inverse Weibull model was developed by Erto [10]. In practice, the unknown parameters of the appropriate inverse Weibull density are not known and must be estimated from a random sample. Estimation of its parameters has been approached in the literature by various techniques, because a standard maximum likelihood estimate does not exist. To estimate the unknown parameters of the three-param...
متن کاملOn Shrinkage Estimation for the Scale Parameter of Weibull Distribution
In the present article, some shrinkage testimators for the scale parameter of a two – parameter Weibull life testing model have been suggested under the LINEX loss function assuming the shape parameter is to be known. The comparisons of the proposed testimators have been made with the improved estimator.
متن کاملMixed methods for fitting the GEV distribution
The generalised extreme-value (GEV) distribution is widely used for modelling and characterising extremes. It is a flexible 3-parameter distribution that combines three extreme-value distributions within a single framework: the Gumbel, Frechet and Weibull. Common methods used for estimating the GEV parameters are the method of maximum likelihood and the method of L-moments. This paper generalis...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Statistical and Application
سال: 2012
ISSN: 2325-2251,2325-226X
DOI: 10.12677/sa.2012.12005