On nonlinear weighted total least squares parameter estimation problem for the three-parameter Weibull density

The three-parameter Weibull density function is widely employed as a model in reliability and lifetime studies. Estimation of its parameters has been approached in the literature by various techniques, because a standard maximum likelihood estimate does not exist. In this paper we consider the nonlinear weighted total least squares fitting approach. As a main result, a theorem on the existence of the total least squares estimate is obtained, as well as its generalization in the total _lq$l_q$ norm (q?1$q?1$). Some numerical simulations to support the theoretical work are given.     

Finding maximum likelihood estimators for the three-parameter Weibull distribution

Much work has been devoted to the problem of finding maximum likelihood estimators for the three-parameter Weibull distribution. This problem has not been clearly recognized as a global optimization one and most methods from the literature occasionally fail to find a global optimum. We develop a global optimization algorithm which uses first order conditions and projection to reduce the problem to a univariate optimization one. Bounds on the resulting function and its first order derivative are obtained and used in a branch-and-bound scheme. Computational experience is reported. It is also shown that the solution method we propose can be extended to the case of right censored samples.     

Fitting the three-parameter Weibull distribution with Cross Entropy

The Weibull distribution is widely used in applications such as reliability and lifetime studies. Although this distribution has three parameters, for simplicity, literature pertaining to Weibull parameter estimation relaxes one of its parameters in order to estimate the other two. When the three-parameter Weibull distribution is of interest, the estimation procedure is complicated. For example, the likelihood function for a three-parameter Weibull distribution is hard to maximize. In this paper, a Cross Entropy (CE) method is developed in the context of maximum likelihood estimation (MLE) of a three-parameter Weibull distribution. Performing a simulation study, a comparative analysis between the newly developed method and two existing methods is conducted. The results show the proposed method has better performance in terms of accuracy, precision and run time for different parameter settings and sample sizes.     

A review of existence criteria for parameter estimation of the Michaelis–Menten regression model

In this paper we consider the least squares (LS) and total least squares (TLS) problems for a Michaelis–Menten enzyme kinetic model f(x; a, b) = ax/(b + x), a, b > 0. In various applied research such as biochemistry, pharmacology, biology and medicine there are lots of different applications of this model. We will systematize some of our results pertaining to the existence of the LS and TLS estimate, which were proved in Hadeler et al. (Math Method Appl Sci 30:1231–1241, 2007) and Jukić et al. (J Comput Appl Math 201:230–246, 2007). Finally, we suggest a choice of good initial approximation and give one numerical example.      

An approximate lower tolerance bound for the three-parameter Weibull applied to lumber property characterization

We investigate a large sample approach for obtaining tolerance bounds where the underlying population is a three-parameter Weibull distribution. Accurate tolerance bounds could play an important role in the development of lumber standards. Properties of the maximum likelihood based approach are compared with those of the standard nonparametric tolerance procedure. The asymptotic normal approximation to the tolerance bound was found to be inadequate for most of the cases considered.     

On a proper way to select population failure distribution and a stochastic optimization method in parameter estimation

It is widely accepted that the Weibull distribution plays an important role in reliability applications. The reliability of a product or a system is the probability that the product or the system will still function for a specified time period when operating under some confined conditions. Parameter estimation for the three parameter Weibull distribution has been studied by many researchers in the past. Maximum likelihood has traditionally been the main method of estimation for Weibull parameters along with other recently proposed hybrids of optimization methods. In this paper, we use a stochastic optimization method called the Markov Chain Monte Carlo (MCMC) to carry out the estimation. The method is extremely flexible and inference for any quantity of interest is easily obtained.     

On the errors-in-variables problem for time series

The usual assumption in the classical errors-in-variables problem of independent measurement errors cannot necessarily be maintained when the data are time series; errors may be strongly serially correlated, possibly containing seasonal effects and trends. When it is possible to identify frequency bands over which the signal-to-noise ratio is large, an approximate solution to the errors-in-variables problem is to omit the remaining frequencies from a time series regression. We draw attention to the danger of “leakage” from the omitted frequencies, and show that the consequent bias can be reduced by means of tapering.     

Weighted Hardy spaces in the three-parameter case

In this paper, we use the idea of the discrete Littlewood-Paley theory developed by Han and Lu to carry out the three-parameter weighted Hardy spaces theory under a rather weak condition on the product weight (w∈A_∞) and obtain the boundedness of singular integral operators on the weighted Hardy spaces.     

On transmission problem for viscoelastic wave equation with a localized a nonlinear dissipation

In this article, we consider the global existence and decay rates of solutions for the transmission problem of Kirchhoff type wave equations consisting of two physically different types of materials, one component being a Kirchhoff type wave equation with time dependent localized dissipation which is effective only on a neighborhood of certain part of boundary, while the other being a Kirchhoff type viscoelastic wave equation with nonlinear memory.     

Improved maximum-likelihood estimation for the common shape parameter of several Weibull populations

The biasness problem of the maximum-likelihood estimate (MLE) of the common shape parameter of several Weibull populations is examined in detail. A modified MLE (MMLE) approach is proposed. In the case of complete and Type II censored data, the bias of the MLE can be substantial. This is noticeable even when the sample size is large. Such a bias increases rapidly as the degree of censorship increases and as more populations are involved. The proposed MMLE, however, is nearly unbiased and much more efficient than the MLE, irrespective of the degree of censorship, the sample sizes, and the number of populations involved. Copyright © 2007 John Wiley & Sons, Ltd.     

Robust weighted orthogonal regression in the errors-in-variables model

This paper focuses on robust estimation in the structural errors-in-variables (EV) model. A new class of robust estimators, called weighted orthogonal regression estimators, is introduced. Robust estimators of the parameters of the EV model are simply derived from robust estimators of multivariate location and scatter such as the M-estimators, the S-estimators and the MCD estimator. The influence functions of the proposed estimators are calculated and shown to be bounded. Moreover, we derive the asymptotic distributions of the estimators and illustrate the results on simulated examples and on a real-data set.     

On an initial boundary value problem in nonlinear 3D-magnetoelasticity

We prove existence and uniqueness of a weak solution to an initial boundary value problem, related to the Maxwell and Lamé systems nonlinearly coupled through the so-called magnetoelastic effect. Uniqueness is proved under additional assumptions on the smoothness of the solution.     

On the general problem of mean estimation

Mean estimation for a random function is considered in its most general context, including both the case of infinite dimensional mean and exact estimation. The existence theorem for the best linear unbiased estimates is established. The general definition of the pseudobest estimate is given; necessary and sufficient conditions for the efficiency of the pseudobest estimates are obtained. As an application the problem of the periodic trend estimation is considered.     

Comparison of certain value-at-risk estimation methods for the two-parameter Weibull loss distribution

The Weibull distribution is one of the most important distributions that is utilized as a probability model for loss amounts in connection with actuarial and financial risk management problems. This paper considers the Weibull distribution and its quantiles in the context of estimation of a risk measure called Value-at-Risk (VaR). VaR is simply the maximum loss in a specified period with a pre-assigned probability level. We attempt to present certain estimation methods for VaR as a quantile of a distribution and compare these methods with respect to their deficiency (Def) values. Along this line, the results of some Monte Carlo simulations, that we have conducted for detailed investigations on the efficiency of the estimators as compared to MLE, are provided.     

On asymptotics of t-type regression estimation in multiple linear model

We consider a robust estimator (t-type regression estimator) of multiple linear regression model by maximizing marginal likelihood of a scaled t-type error t-distribution. The marginal likelihood can also be applied to the de-correlated response when the within-subject correlation can be consistently estimated from an initial estimate of the model based on the independent working assumption. This paper shows that such a t-type estimator is consistent.     

Initial-boundary value problem for the nonlinear string-beam system

This paper deals with a nonlinear string-beam system describing the torsional-vertical oscillations of a suspension bridge. We consider the initial-boundary value problem and study the existence and uniqueness question. We assume time independent right hand sides, but allow quite general nonlinear terms. Using the Faedo-Galerkin method we prove the existence of a unique solution on an arbitrary large time interval.     

威布尔分布的Bayes可靠性分析

本文针对两参数的威布尔分布的元件，采用Ｂａｙｅｓ方法对其可靠性进行分析，文中分别对两种假设情况进行了讨论，第一种情况是形状参数为离散取值，尺度参数为连续取值的情况，第二种情况假设形状参数的先验分布为均匀分布，尺度参数的先验分布为逆伽玛分布，推出了对应的可靠性估计和置信下限估计，并给出了计算算法，最后用实例对算法进行了验证。     

WEIBULL分布步进应力加速寿命试验损伤失效率模型参数的近似极大似然估计和逆矩估计

Bhattacharyya和Soejoeti(1980)对步进应力加速寿命试验提出损伤失效率模型(TFR模型)．本针对TFR模型，对两参数Weibull分布，在步进应力加速试验下给出了参数的近似极大似然估计和逆矩估计，并通过Montr-Carlo模拟考察了估计的精度，比较了各估计的优劣。