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Parametric Estimation (parametric + estimation)

Distribution by Scientific Domains
Mathematics and Statistics75%

Selected Abstracts

Nonparametric and Parametric Estimation for a Linear Germination-Growth Model

BIOMETRICS, Issue 3 2000
S. N. Chiu
Summary. Seeds are planted on the interval [0, L] at various locations. Each seed has a location x and a potential germination time t, [0, ,), and it is assumed that the collection of such (x, t) pairs forms a Poisson process in [0, L] × [0, ,) with intensity measure dxd,(t). From each seed that germinates, an inhibiting region grows bidirectionally at rate 2v. These regions inhibit germination of any seed in the region with a later potential germination time. Thus, seeds only germinate in the uninhibited part of [0, L]. We want to estimate , on the basis of one or more realizations of the process, the data being the locations and germination times of the germinated seeds. We derive the maximum likelihood estimator of v and a nonparametric estimator of , and describe methods of obtaining parametric estimates from it, illustrating these with reference to gamma densities. Simulation results are described and the methods applied to some neurobiological data. An Appendix outlines the S-PLUS code used. [source]

Parametric estimation for the location parameter for symmetric distributions using moving extremes ranked set sampling with application to trees data

ENVIRONMETRICS, Issue 7 2003
Mohammad Fraiwan Al-Saleh
Abstract A modification of ranked set sampling (RSS) called moving extremes ranked set sampling (MERSS) is considered parametrically, for the location parameter of symmetric distributions. A maximum likelihood estimator (MLE) and a modified MLE are considered and their properties are studied. Their efficiency with respect to the corresponding estimators based on simple random sampling (SRS) are compared for the case of normal distribution. The method is studied under both perfect and imperfect ranking (with error in ranking). It appears that these estimators can be real competitors to the MLE using (SRS). The procedure is illustrated using tree data. Copyright © 2003 John Wiley & Sons, Ltd. [source]

Empirical implications of response acquiescence in discrete-choice contingent valuation

HEALTH ECONOMICS, Issue 10 2006
Raymond Y. T. Yeung
Abstract The use of discrete-choice contingent valuation (CV) to elicit individuals' preference, expressed as maximum willingness-to-pay (WTP), although primarily developed in environmental economics, has been popular in the economic evaluation of health and healthcare. However, a concern with this method is the potential for ,over-estimating' WTP values due to the presence of response acquiescence, or ,yea-saying' bias. Based on a CV survey conducted to estimate physicians' valuation of clinic computerization, the extent of such bias was estimated from a within-sample open-ended valuation question following the respondents' discrete choice response. Analysis of this data suggests that not only was response acquiescence an issue, but also that the parametric estimation of mean and median WTP, the most common approach to estimating WTP from discrete-choice data, would potentially magnify such bias (to various degrees depending on the distributional assumptions applied). The possible extent of CV design versus analysis in discrete-choice methods therefore warrants further exploration. Copyright © 2006 John Wiley & Sons, Ltd. [source]

Parameter Estimation for Partially Complete Time and Type of Failure Data

BIOMETRICAL JOURNAL, Issue 2 2004
Debasis Kundu
Abstract The theory of competing risks has been developed to asses a specific risk in presence of other risk factors. In this paper we consider the parametric estimation of different failure modes under partially complete time and type of failure data using latent failure times and cause specific hazard functions models. Uniformly minimum variance unbiased estimators and maximum likelihood estimators are obtained when latent failure times and cause specific hazard functions are exponentially distributed. We also consider the case when they follow Weibull distributions. One data set is used to illustrate the proposed techniques. (© 2004 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source]