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Locally weighted least squares kernel regression and statistical evaluation of LIDAR measurements

Holst, Ulla LU ; Hössjer, Ola LU ; Björklund, Claes; Ragnarson, Pär and Edner, Hans LU (1996) In Environmetrics 7(4). p.401-416
Abstract
The LIDAR technique is an efficient tool in monitoring the distribution of atmospheric species of importance. We study the concentration of atmospheric atomic mercury in an Italian geothermal field and discuss the possibility of using recent results from local polynomial kernel regression theory for the evaluation of the derivative of the DIAL curve. A MISE-optimal bandwidth selector, which takes account of the heteroscedasticity in the regression is suggested. Further, we estimate the integrated amount of mercury in a certain area.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
LIDAR measurements, Locally weighted least squares regression, air pollution, atmospheric atomic mercury, geothermal field
in
Environmetrics
volume
7
issue
4
pages
401 - 416
publisher
John Wiley & Sons
external identifiers
  • scopus:0029659760
ISSN
1099-095X
DOI
10.1002/(SICI)1099-095X(199607)7:4<401::AID-ENV221>3.0.CO;2-D
language
English
LU publication?
yes
id
d918ce7d-2885-42f4-b3d2-b21d246af3b7 (old id 1217043)
alternative location
http://www3.interscience.wiley.com/cgi-bin/fulltext/25021/PDFSTART
date added to LUP
2008-09-22 14:17:39
date last changed
2017-01-01 05:05:51
@article{d918ce7d-2885-42f4-b3d2-b21d246af3b7,
  abstract     = {The LIDAR technique is an efficient tool in monitoring the distribution of atmospheric species of importance. We study the concentration of atmospheric atomic mercury in an Italian geothermal field and discuss the possibility of using recent results from local polynomial kernel regression theory for the evaluation of the derivative of the DIAL curve. A MISE-optimal bandwidth selector, which takes account of the heteroscedasticity in the regression is suggested. Further, we estimate the integrated amount of mercury in a certain area.},
  author       = {Holst, Ulla and Hössjer, Ola and Björklund, Claes and Ragnarson, Pär and Edner, Hans},
  issn         = {1099-095X},
  keyword      = {LIDAR measurements,Locally weighted least squares regression,air pollution,atmospheric atomic mercury,geothermal field},
  language     = {eng},
  number       = {4},
  pages        = {401--416},
  publisher    = {John Wiley & Sons},
  series       = {Environmetrics},
  title        = {Locally weighted least squares kernel regression and statistical evaluation of LIDAR measurements},
  url          = {http://dx.doi.org/10.1002/(SICI)1099-095X(199607)7:4<401::AID-ENV221>3.0.CO;2-D},
  volume       = {7},
  year         = {1996},
}