Small-area estimation under a log-transformed area-level model
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Title |
Small-area estimation under a log-transformed area-level model
Not Available |
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Creator |
Hukum Chandra
Kaustav Aditya Sushil Kumar |
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Subject |
Small area
log scale back-transformation bias correction |
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Description |
Not Available
Area-level models are often used for small-area estimation when auxiliary data are available only as area aggregates. A popular area-level model used for small-area estimation is the Fay–Herriot model. In many small-area applications, the Fay– Herriot model is often fitted on a logarithm (log) scale and model parameters are estimated under this model. This is followed by back-transformation to obtain the estimates for small-area quantities in the original scale. However, back-transformation leads to biased estimates of small-area quantities. This article develops a bias-corrected predictor for small-area quantities under a log-transformed Fay–Herriot model. The empirical results-based simulation studies show that the bias-corrected small-area predictor has both smaller bias and better efficiency as compared to the existing small-area predictors. Not Available |
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Date |
2018-10-26T09:43:22Z
2018-10-26T09:43:22Z 2018-01-04 |
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Type |
Research Paper
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Identifier |
Not Available
Not Available https://doi.org/10.1080/15598608.2017.1415174 http://krishi.icar.gov.in/jspui/handle/123456789/8252 |
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Language |
English
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Relation |
Not Available;
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Publisher |
Not Available
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