共查询到20条相似文献,搜索用时 0 毫秒
1.
The class of nature exponential families generated by stable distributions has been introduced in different contexts by several authors. Tweedie (1984) and Jorgensen (1987) studied this class in the context of generalized liner models and exponential dispersion models. Bar-Lev and Enis (1986) introduced this class in the context of the property of reproducibility in natural exponential families and Hougaard (1986) found the distributions in this class to be natural candidates for applications as survival distributions in life tables for heterogeneous populations. In this note, we consider such a class in the context of minimum variance unbiased estimation. For each family in this class, we obtain an explicit expression for the uniformly minimum variance unbiased estimator for the r-th cumlant, the density function, and the reliability function. 相似文献
2.
Kam-Wah Tsui 《Revue canadienne de statistique》1979,7(2):193-200
Let X1, …, Xp be independent random variables, all having the same distribution up to a possibly varying unspecified parameter, where each of the p distributions belongs to the family of one parameter discrete exponential distributions. The problem is to estimate the unknown parameters simultaneously. Hudson (1978) shows that the minimum variance unbiased estimator (MVUE) of the parameters is inadmissible under squared error loss, and estimators better than the MVUE are proposed. Essentially, these estimators shrink the MVUE towards the origin. In this paper, we indicate that estimators shifting the MVUE towards a point different from the origin or a point determined by the observations can be obtained. 相似文献
3.
Ashish Kumar 《统计学通讯:理论与方法》2013,42(5):549-556
We give a simple theorem which easily enables us to get the minimum variance unbiased estimators of manv useful parametric functions of the parmecer in a left cruncated power series distribution. The theorem can be used in both cases:when the truncation is know and (ii) when truncation point is unknown. 相似文献
4.
Wangxue Chen Yi Tian Minyu Xie 《Journal of Statistical Computation and Simulation》2018,88(17):3399-3414
The minimum variance unbiased estimators (MVUEs) of the parameters for various distributions are extensively studied under ranked set sampling (RSS). However, the results in existing literatures are only locally MVUEs, i.e. the MVUE in a class of some unbiased estimators is obtained. In this paper, the global MVUE of the parameter in a truncated parameter family is obtained, that is to say, it is the MVUE in the class of all unbiased estimators. Firstly we find the optimal RSS according to the character of a truncated parameter family, i.e. arrange RSS based on complete and sufficient statistics of independent and identically distributed samples. Then under this RSS, the global MVUE of the parameter in a truncated parameter family is found. Numerical simulations for some usual distributions in this family fully support the result from the above two-step optimizations. A real data set is used for illustration. 相似文献
5.
The uniformly minimum variance unbiased estimator (UMVUE) of the variance of the inverse Gaussian distribution is shown to be inadmissible in terms of the mean squared error, and a dominating estimator is given. A dominating estimator to the maximum likelihood estimator (MLE) of the variance and estimators dominating the MLE's and the UMVUE's of other parameters are also given. 相似文献
6.
In this paper we study certain properties of estimable and UMUV-estimable functions in a subfamily of the one-parameter exponential family of distributions for which there exists a sufficient and complete statistic following a Gamma distribution. These results are applied to the problem of estimation in the transformed chi-square family. 相似文献
7.
The present paper explores the structure of linear exponential families for which the sample variance is a uniformly minimum variance unbiased estimator. 相似文献
8.
K.K. Ferentinos 《统计学通讯:理论与方法》2013,42(3):847-856
In this paper we construct uniformly minimum variance unbiased estimators for U-estimable functions when the underlying family of distributions involves two unknown truncation parameters and the sample is doubly Type II censored. Previous relevant results for the complete sample case are obtained as special cases of our results. 相似文献
9.
Malay Ghosh James V. Zidek Tapabrata Maiti Rick White 《Revue canadienne de statistique》2004,32(2):139-157
The authors propose a weighted likelihood concept for the estimation of parameters in natural exponential families with quadratic variance. They apply the results to both simulated and real data. 相似文献
10.
S. Sengupta 《统计学通讯:理论与方法》2018,47(20):5077-5082
We consider the problem of estimation of a finite population variance related to a sensitive character under a randomized response model and prove (i) the admissibility of an estimator for a given sampling design in a class of quadratic unbiased estimators and (ii) the admissibility of a sampling strategy in a class of comparable quadratic unbiased strategies. 相似文献
11.
N.S. Kambo 《统计学通讯:理论与方法》2013,42(12):1129-1132
In this note explicit expressions are given for the maximum likelihood estimators of the parameters of the two-parameter exponential distribution, when a doubly censored sample is available. 相似文献
12.
M. A. Beg 《统计学通讯:理论与方法》2013,42(7):687-691
In this note a relationship in the treatment of the lower and upper truncations considered in Beg (1980) is pointed out and the minimum variance unbiased estimator of P = Pr{Y<X) for the (upper) truncated exponential distribution is obtained. 相似文献
13.
We obtain a new technique to calculate the value of the minimum variance unbiased estimator (MVUE) of the probability function (p.f.) of the R distribution. This technique is based on an investigation of the ratios of r numbers. A recurrence relation for the MVUE of the p.f. of the R distribution is derived. It is interesting that the derived relation does not depend on the r numbers but depends on the ratios of the r numbers. The new method is efficient, convenient and accurate. 相似文献
14.
The paper considers the problem of bounded risk point estimation for a linear function of location parameters of two negative exponential distributions, including the difference in a special case, when two scale parameters are unknown. Purely sequential procedures are proposed and second order expansions of the average sample sizes and risk are given. Furthermore some simulation results are provided. 相似文献
15.
16.
Exponential dispersion models, which are linear exponential families with a dispersion parameter, are the prototype response
distributions for generalized linear models. The Tweedie family comprises those exponential dispersion models with power mean-variance
relationships. The normal, Poisson, gamma and inverse Gaussian distributions belong to theTweedie family. Apart from these
special cases, Tweedie distributions do not have density functions which can be written in closed form. Instead, the densities
can be represented as infinite summations derived from series expansions. This article describes how the series expansions
can be summed in an numerically efficient fashion. The usefulness of the approach is demonstrated, but full machine accuracy
is shown not to be obtainable using the series expansion method for all parameter values. Derivatives of the density with
respect to the dispersion parameter are also derived to facilitate maximum likelihood estimation. The methods are demonstrated
on two data examples and compared with with Box-Cox transformations and extended quasi-likelihoood. 相似文献
17.
In this paper, we consider the distribution of the number of "1"-runs of length k in a sequence of {0,1}-valued random variables of length n by using a new (unified) counting scheme called l-overlapping counting. Here, k and n are positive integers with k ≦ and l is an integer less than k. We obtain the prohabi!ity generating function of the distribution of the number of eoverlapping "in-runs of iength k in the sequence, even when the underiying sequence is a dependent sequence such as a highcr order Markov chaic. 相似文献
18.
《Journal of Statistical Computation and Simulation》2012,82(2):73-82
Variance estimation under systematic sampling with probability proportional to size is known to be a difficult problem. We attempt to tackle this problem by the bootstrap resampling method. It is shown that the usual way to bootstrap fails to give satisfactory variance estimates. As a remedy, we propose a double bootstrap method which is based on certain working models and involves two levels of resampling. Unlike existing methods which deal exclusively with the Horvitz–Thompson estimator, the double bootstrap method can be used to estimate the variance of any statistic. We illustrate this within the context of both mean and median estimation. Empirical results based on five natural populations are encouraging. 相似文献
19.
Kōsei Iwase 《统计学通讯:理论与方法》2013,42(12):3559-3566
The uniformly minimum variance unbiased estimator of the cumulative hazard function in the Pareto distribution of the first kind is derived. The variance of the estimator is also obtained in an analytic form, and for some cases its values are compared numerically with mean square errors of the maximum likelihood estimator. 相似文献
20.
Saralees Nadarajah K. Jayakumar Miroslav M. Ristić 《Journal of Statistical Computation and Simulation》2013,83(8):1389-1404
We introduce a new family of distributions by adding a parameter to the Marshall–Olkin family of distributions. Some properties of the new family of distributions are derived. A particular case of the family, a three-parameter generalization of the exponential distribution, is given special attention. The shape properties, moments, distributions of the order statistics, entropies and estimation procedures are derived. An application to a real data set is discussed. 相似文献