Online surveillance of multivariate small area disease data: a Bayesian approach

2011 ◽  
Vol 4 (0) ◽  
Author(s):  
Ana Corberán ◽  
Andrew B Lawson
Keyword(s):  
2006 ◽  
Vol 15 (5) ◽  
pp. 499-516 ◽  
Author(s):  
Ravi Maheswaran ◽  
Robert P Haining ◽  
Tim Pearson ◽  
Jane Law ◽  
Paul Brindley ◽  
...  

2020 ◽  
Vol 18 (1) ◽  
pp. 2-22
Author(s):  
Kusman Sadik ◽  
Rahma Anisa ◽  
Euis Aqmaliyah

The most commonly used method of small area estimation (SAE) is the empirical best linear unbiased prediction method based on a linear mixed model. However, it is not appropriate in the case of the zero-inflated target variable with a mixture of zeros and continuously distributed positive values. Therefore, various model-based SAE methods for zero-inflated data are developed, such as the Frequentist approach and the Bayesian approach. Both approaches are compared with the survey regression (SR) method which ignores the presence of zero-inflation in the data. The results show that the two SAE approaches for zero-inflated data are capable to yield more accurate area mean estimates than the SR method.


Author(s):  
R. H. Geiss

The theory and practical limitations of micro area scanning transmission electron diffraction (MASTED) will be presented. It has been demonstrated that MASTED patterns of metallic thin films from areas as small as 30 Åin diameter may be obtained with the standard STEM unit available for the Philips 301 TEM. The key to the successful application of MASTED to very small area diffraction is the proper use of the electron optics of the STEM unit. First the objective lens current must be adjusted such that the image of the C2 aperture is quasi-stationary under the action of the rocking beam (obtained with 40-80-160 SEM settings of the P301). Second, the sample must be elevated to coincide with the C2 aperture image and its image also be quasi-stationary. This sample height adjustment must be entirely mechanical after the objective lens current has been fixed in the first step.


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