File:Plaia 2006 - Single imputation method.pdf

From Earth Science Information Partners (ESIP)
Revision as of 19:28, January 31, 2015 by DataRonin (talk | contribs) (Missing data represent a general problem in many scientific fields above all in environmental research. Several methods have been proposed in literature for handling missing data and the choice of an appropriate method depends, among others, on the mis...)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
The printable version is no longer supported and may have rendering errors. Please update your browser bookmarks and please use the default browser print function instead.

Plaia_2006_-_Single_imputation_method.pdf(file size: 413 KB, MIME type: application/pdf)

Missing data represent a general problem in many scientific fields above all in environmental research. Several methods have been proposed in literature for handling missing data and the choice of an appropriate method depends, among others, on the missing data pattern and on the missing-data mechanism. One approach to the problem is to impute them to yield a complete data set. The goal of this paper is to propose a new single imputation method and to compare its performance to other single and multiple imputation methods known in literature. Considering a data set of PM10 concentration measured every 2 h by eight monitoring stations distributed over the metropolitan area of Palermo, Sicily, during 2003, simulated incomplete data have been generated, and the performance of the imputation methods have been compared on the correlation coefficient ðrÞ, the index of agreement (d), the root mean square deviation (RMSD) and the mean absolute deviation (MAD). All the performance indicators agree to evaluate the proposed method as the best among the ones compared, independently on the gap length and on the number of stations with missing data.

File history

Click on a date/time to view the file as it appeared at that time.

Date/TimeDimensionsUserComment
current19:28, January 31, 2015 (413 KB)DataRonin (talk | contribs)Missing data represent a general problem in many scientific fields above all in environmental research. Several methods have been proposed in literature for handling missing data and the choice of an appropriate method depends, among others, on the mis...

The following page uses this file: