Boosted Regression Estimates of Spatial Data: Pointwise Inference
Marco d. marzio and charles c. taylor
DOI : 10.3844/jmssp.2005.257.266
Journal of Mathematics and Statistics
Volume 1, Issue 4
In this study simple nonparametric techniques have been adopted to estimate the trend surface of the Swiss rainfall data. In particular we employed the Nadaraya-Watson smoother and in addition, an adapted-by boosting-version of it. Additionally, we have explored the use of the Nadaraya-Watson estimator for the construction of pointwise confidence intervals. Overall, boosting does seem to improve the estimate as much as previous examples and the results indicate that cross-validation can be successfully used for parameter selection on real datasets. In addition, our estimators compare favorably with most of the techniques previously used on this dataset.
© 2005 Marco d. marzio and charles c. taylor. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.