103,906 research outputs found
Multipurpose small area estimation
No full textSample surveys are generally multivariate, in the sense that they measure more than oneresponse variable. In theory, each variable can then be assigned an optimal weight forestimation purposes. However, it is often a distinct practical advantage to have a singleweight that is used with all variables collected in the survey. This paper describes howsuch multipurpose sample weights can be constructed when small area estimates of thesurvey variables are required. The approach is based on the model-based direct (MBD)method of small area estimation described in Chambers and Chandra (2006). Empiricalresults reported in this paper show that MBD estimators for small areas based onmultipurpose weights perform well across a range of variables that are often of interest inbusiness surveys. Furthermore, these results show that the proposed approach is robust tomodel misspecification and also efficient for the variables ill-suited to standard methodsof small area estimation (e.g. variables that contain a significant proportion of zeros).<br/
A. T. Chambers
No full text"VX110690 Sgt A.T. Chambers 7th Fortress Coy R.A.E. Darwin May 1940 - Aug 1942".VX110690 Sergeant A. T. Chambers. 7th Fortress Company, Royal Australian Engineers, Darwin, May 1940 - August 1942.Date:199
Unchained Poem by Lee Chambers
No full textText document the poem Unchained by Lee Chambers, Jr. published in the November 1973 issue of the New Era Magazine a publication of the LDS Churchconverted from .jpg to .pdf for compatibilit
Calibrated Weighting for Small Area Estimation
No full textCalibrated weighting methods for estimation of survey population characteristics are widely used. At the same time, model-based prediction methods for estimation of small area or domain characteristics are becoming increasingly popular. This paper explores weighting methods based on the mixed models that underpin small area estimates to see whether they can deliver equivalent small area estimation performance when compared with standard prediction methods and superior population level estimation performance when compared with standard calibrated weighting methods. A simple MSE estimator for weighted small area estimation is also developed
Improved Direct Estimators for Small Areas
No full textUnbiased direct estimators for small area quantities are usually considered too variable to be of any practical use. In this paper we propose a class of model-based direct estimators for small area quantities that appears to overcome this objection, in the sense that these estimators are comparable in efficiency to the indirect model-based small area estimators (e.g. empirical best linear unbiased predictors, or EBLUPs) that are now widely used. There are many practical advantages associated with such model-based direct (MBD) estimators, arising from the fact that they are computed as weighted linear combinations of the actual sample data from the small areas of interest. Note that in this case the weights ‘borrow strength’ via a model that explicitly allows for small area effects. One particular advantage that we explore in this paper is that estimation of mean squared error (MSE) is then straightforward, using well-known methods that are in common use for population level estimates. Empirical results reported in this paper show that the MBD estimator represents a real alternative to the EBLUP, with the simple MSE estimator associated with the MBD estimator providing good coverage performance. We also report results that indicate that the MBD estimator may be more robust than the EBLUP when the small area model is incorrectly specified. Furthermore, the MBD approach is easily extended to provide multi-purpose weights that are efficient across a range of variables, including variables that are unsuitable for EBLUP, e.g. variables that contain a significant proportion of zeros
Small Area Estimation with Skewed Data
No full textIn business surveys, data typically are skewed and the standard approach for small area estimation based on linear mixed models lead to inefficient estimates. In this paper, we discuss small area estimation techniques for skewed data that are linear following a suitable transformation. In this context, implementation of the empirical best linear unbiased prediction (EBLUP) approach under transformation to a linear mixed model is complicated. However, this is not the case with the model-based direct (MBD) approach (Chambers and Chandra, 2006), which is based on weighted linear estimators. We extend the MBD approach to skewed data using sample weights derived via model calibration based on a log transform model with random area effects. Our results show this estimator is both efficient and robust with respect to the distribution of these random effects. An application to real data demonstrates the satisfactory performance of the method
Bias Adjusted Estimation for Small Areas with Outlying Values
No full textSmall area estimation techniques typically rely on regression models that use both covariates and random effects to explain between domain variation. Chambers and Tzavidis (2006) describe a novel approach to small area estimation that is based on modelling quantile-like parameters of the conditional distribution of the target variable given the covariates. This is an outlier robust approach that avoids conventional Gaussian assumptions and the problems associated with specification of random effects, allowing inter-domain differences to be characterized by the variation of area-specific M-quantile coefficients. These authors observed, however, that M-quantile estimates of small area means are biased with the magnitude of the bias being related to the presence of outliers in the data. In this paper we propose a bias adjustment to the M-quantile small area estimator of the mean that is based on representing this estimator as a functional of the small area distribution function. The method is then generalized for estimating other quantiles of the distribution function in a small area. The effect of this bias adjustment on small area estimation with random effects models in the presence of model misspecification is also examined
[Report to Chief J. E. Curry by W. E. Chambers, regarding the murder of Lee Harvey Oswald #4]
No full textReport to Chief J. E. Curry by W. E. Chambers regarding officer's assignment and the murder of Lee Harvey Oswald. Chambers describes his duties, actions, and observations as a security guard during the transfer of Oswald to the County Jail
[Report to Chief J. E. Curry by W. E. Chambers, regarding the murder of Lee Harvey Oswald #1]
No full textReport to Chief J. E. Curry by W. E. Chambers regarding officer's assignment and the murder of Lee Harvey Oswald. Chambers describes his duties, actions, and observations as a security guard during the transfer of Oswald to the County Jail
[Report to Chief J. E. Curry by W. E. Chambers, regarding the murder of Lee Harvey Oswald #2]
No full textReport to Chief J. E. Curry by W. E. Chambers regarding officer's assignment and the murder of Lee Harvey Oswald. Chambers describes his duties, actions, and observations as a security guard during the transfer of Oswald to the County Jail
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