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National statistical institutes generally apply design-based techniques like the generalized regression estimator to compile official statistics.
For model-assisted estimation, the variance estimator of the so-called generalized regression estimator is [60].
The generalized regression estimator and the Horvitz Thompson estimator are mentioned.
Comparisons with the generalized regression estimator and Horvitz Thompson estimators are also performed.
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Calibration techniques in survey sampling, such as generalized regression estimation (GREG), were formalized in the 1990s to produce efficient estimators of linear combinations of study variables, such as totals or means.
Regarding the criteria for exploiting information from remote sensing at the estimation level in forest inventories, many recent papers make use of the generalized regression (GREG) estimator (e.g. Opsomer et al. 2007; Mandallaz et al. 2013; McRoberts et al. 2014).
Also, when the MDP prior baseline distribution is specified as a product of independent probability measures, this WLS solution provides a new type of generalized ridge regression estimator.
The proposed algorithm is fairly compared with the optimal GCC methods, a generalized linear regression estimator, and an AMDF method in noisy and reverberant environment.
In this paper, we first discuss the origin, developments and various thoughts by several researchers on the generalized linear regression estimator (GREG) due to Deville and Särndal [Deville, J.C., Särndal, C.E., 1992. Calibration estimators in survey sampling. J. Amer. Statist. Assoc. 87, 376 382].
A limited simulation study shows that the minimum model mean squared error regression estimator performs well compared to the generalized least squares regression estimator, even when the working model is inappropriate.
Similarly, the functions of the segments are estimated using the Nadaraya-Watson regression estimator.
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