Locally weighted least squares kernel regression and statistical evaluation of LIDAR measurements
Research output: Contribution to journal › Article
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.
|Research areas and keywords||
Subject classification (UKÄ) – MANDATORY
|Publication status||Published - 1996|