A regression-type estimator is proposed for the population total of a character y , when sample-units are selected with probability proportional to some measure of size z (pps) and with replacement; and the information on yet another variate x is used. The proposed estimator is shown to be ...
So the usual regression estimator of μy takes the form: μ^yL=y¯+y¯x¯(μx−x¯)=y¯x¯μx . Note that the interpretation depends on the validity of the model M. The sampling process should not change the model. Difference estimation The difference method of estimating ...
One estimator shares the “optimal” asymptotic bias and variance of the local linear regressor. Other estimators have zero sum of residuals, a desirable property in many applications. In a survey sampling context these estimators can easily be adjusted so that they are internally bias calibrated, ...
【Real-valued Neural Autoregressive Density Estimator (RNADE)】[3] 2013年,对NADE的改进 像素值做了标准化,映射到 [-1, 1] 之间的连续值,数据变了,概率分布也要改变,很自然想到高斯分布 假设p\left(x_{t} | x_{1: t-1}\right) 服从混合高斯分布: \displaystyle p\left(x_{t} | x_{1: t-...
The most frequent method for modeling count responses in numerous investigations is the Poisson regression model. Under simple random sampling, this paper offers utilizing Poisson regression-based mean estimator and discovers its associated formula of the mean square error (MSE). The MSE of the propos...
Regression Type EstimatorSimple Random Sampling without ReplacementThis paper is an extension of Hanif, Hamad and Shahbaz estimator [1]for two-phase sampling. The aim of this paper is to develop a regression typeestimator with two auxiliary variables for two-phase sampling whenwe don't have any ...
1.We give the approximation formulas of the variance of the sample regression estimator for a population mean and its saymptotically non-biased estimator in mult-stage sampling.讨论多阶段抽样回归估计及其样本量选择问题 。 2.Some troubles emerge when we use regression estimator in such a case:in...
M estimatorOutlierSelçuk STATThe existence of a few outlier values in the sampling would prevent the information given by the majority of the sampling and all of the statistics would turn to be insignificant. Therefore it is essential to determine the outliers in the sampling. In the ...
The operation of the bootstrap in the context of nonparametric regression is considered. Bootstrap samples are taken from estimated residuals to study the distribution of a suitably recentered kernel estimator. The application of this principle to the problem of local adaptive choice of bandwidth and...
(Commun Stat Theory Methods, 2019. https ://doi.org/10.1080/03610 926.2019.16458 57) under simple random sampling. We have generalized robust-type estimators where Zaman and Bulut (2019a) and Ali et al. (2019) estimators are members of our generalized estimator. We have also extended our ...