Estimation of a parametric function associated with the lognormal distribution
نویسندگان
چکیده
Estimation of the mean of the lognormal distribution has received much attention in the literature beginning with Finney (1941). The problem is of significant practical importance because of the ubiquitous use of log-transformation. In this paper we consider estimation of a parametric function associated with the lognormal distribution of which the mean, median and moments are special cases. We generalize various estimators from the literature for the mean to this parametric function and propose a new simple estimator. We present the estimators in a unified framework and use this framework to derive asymptotic expressions for their biases and mean square errors (MSEs). Next we make asymptotic and small sample comparisons via simulations between them in terms of their MSEs. Our proposed estimator outperforms many of the previously proposed estimators. A numerical example is given to illustrate the various estimators.
منابع مشابه
Supplementary material for estimation of a parametric function associated with the lognormal distribution 1
Supplementary material for estimation of a parametric function associated with the lognormal distribution Jiangtao Gou and Ajit C. Tamhane Department of Statistics, Northwestern University, Evanston, IL 60208, USA Department of Mathematics and Statistics, Hunter College, New York, NY 10065, USA Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL 6...
متن کاملAN OPTIMUM APPROACH TOWARDS SEISMIC FRAGILITY FUNCTION OF STRUCTURES THROUGH METAHEURISTIC HARMONY SEARCH ALGORITHM
Vulnerability assessment of structures encounter many uncertainties like seismic excitations intensity and response of structures. The most common approach adopted to deal with these uncertainties is vulnerability assessment through fragility functions. Fragility functions exhibit the probability of exceeding a state namely performance-level as a function of seismic intensity. A common approach...
متن کاملParametric Estimation in a Recurrent Competing Risks Model
A resource-efficient approach to making inferences about the distributional properties of the failure times in a competing risks setting is presented. Efficiency is gained by observing recurrences of the compet- ing risks over a random monitoring period. The resulting model is called the recurrent competing risks model (RCRM) and is coupled with two repair strategies whenever the system fails. ...
متن کاملAdmissible Estimators of ?r in the Gamma Distribution with Truncated Parameter Space
In this paper, we consider admissible estimation of the parameter ?r in the gamma distribution with truncated parameter space under entropy loss function. We obtain the classes of admissible estimators. The result can be applied to estimation of parameters in the normal, lognormal, pareto, generalized gamma, generalized Laplace and other distributions.
متن کاملdistribution(exponential) exponential survival distribution distribution(gompertz) Gompertz survival distribution distribution(loglogistic) loglogistic survival distribution distribution(llogistic) synonym for distribution(loglogistic) distribution(weibull) Weibull survival distribution distribution(lognormal) lognormal survival distribution distribution(lnormal) synonym for distribution(lognormal) distribution(ggamma) generalized gamma survival distribution
Description streg performs maximum likelihood estimation for parametric regression survival-time models. streg can be used with singleor multiple-record or singleor multiple-failure st data. Survival models currently supported are exponential, Weibull, Gompertz, lognormal, loglogistic, and generalized gamma. Parametric frailty models and shared-frailty models are also fit using streg. Also see ...
متن کامل