نتایج جستجو برای: grenander estimator

تعداد نتایج: 30099  

2001
Yixiao Sun Peter C. B. Phillips

This paper examines the efficiency gains of GLS detrending over OLS detrending in the model yt = z′ tγ + ut, where z ′ t = (1, t, ..., t k−1) and ut ∼ I(d), −1/2 < d < 3/2. A famous theorem on trend removal by OLS regression (usually attributed to Grenander and Rosenblatt (1957) gave conditions for the asymptotic equivalence of GLS and OLS in deterministic trend estimation with I(0) errors. Whe...

Journal: :bulletin of the iranian mathematical society 2012
mohammad mohammadi mohammad salehi marzijarani

inverse sampling design is generally considered to be appropriate technique when the population is divided into two subpopulations, one of which contains only few units. in this paper, we derive the horvitz-thompson estimator for the population mean under inverse sampling designs, where subpopulation sizes are known. we then introduce an alternative unbiased estimator, corresponding to post-str...

Journal: :journal of sciences, islamic republic of iran 2011
a. karimnezhad

let be a random sample from a normal distribution with unknown mean and known variance the usual estimator of the mean, i.e., sample mean is the maximum likelihood estimator which under squared error loss function is minimax and admissible estimator. in many practical situations, is known in advance to lie in an interval, say for some in this case, the maximum likelihood estimator changes and d...

Hadi Alizadeh Noughabi, Naser Reza Arghami,

In this paper we propose an estimator of the entropy of a continuous random variable. The estimator is obtained by modifying the estimator proposed by Vasicek (1976). Consistency of estimator is proved, and comparisons are made with Vasicek’s estimator (1976), van Es’s estimator (1992), Ebrahimi et al.’s estimator (1994) and Correa’s estimator (1995). The results indicate that the proposed esti...

B. Babadi, Fatemeh Ghapani,

In this paper, we propose a new ridge-type estimator called the new mixed ridge estimator (NMRE) by unifying the sample and prior information in linear measurement error model with additional stochastic linear restrictions. The new estimator is a generalization of the mixed estimator (ME) and ridge estimator (RE). The performances of this new estimator and mixed ridge estimator (MRE) against th...

Journal: :iranian journal of science and technology (sciences) 2013
a. i. shawky

this article examines statistical inference for  where and are independent but not identically distributed pareto of the first kind (pareto (i)) random variables with same scale parameter but different shape parameters. the maximum likelihood, uniformly minimum variance unbiased and bayes estimators with gamma prior are used for this purpose. simulation studies which compare the estimators are ...

The Liu estimator has consistently been demonstrated to be an attractive shrinkage method for reducing the effects of multicollinearity. The Poisson regression model is a well-known model in applications when the response variable consists of count data. However, it is known that multicollinearity negatively affects the variance of the maximum likelihood estimator (MLE) of the Poisson regressio...

Inverse sampling design is generally considered to be appropriate technique when the population is divided into two subpopulations, one of which contains only few units. In this paper, we derive the Horvitz-Thompson estimator for the population mean under inverse sampling designs, where subpopulation sizes are known. We then introduce an alternative unbiased estimator, corresponding to post-st...

2002
ASGER HOBOLTH JOHN T. KENT IAN L. DRYDEN

Objects in the plane with no obvious landmarks can be described by either vertex transformation vectors or edge transformation vectors. In this paper we provide the relation between the two transformation vectors. Grenander & Miller (1994) use a multivariate normal distribution with a block circulant covariance matrix to model the edge transformation vector. This type of model is also feasible ...

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