| タイトル | A comparison of minimum distance and maximum likelihood techniques for proportion estimation |
| 本文（外部サイト） | http://hdl.handle.net/2060/19830026124 |
| 著者（英） | Woodward, W. A.; Gray, H. L.; Schucany, W. R.; Lindsey, H. |
| 著者所属（英） | Southern Methodist Univ. |
| 発行日 | 1982-11-01 |
| 言語 | eng |
| 内容記述 | The estimation of mixing proportions P sub 1, P sub 2,...P sub m in the mixture density f(x) = the sum of the series P sub i F sub i(X) with i = 1 to M is often encountered in agricultural remote sensing problems in which case the p sub i's usually represent crop proportions. In these remote sensing applications, component densities f sub i(x) have typically been assumed to be normally distributed, and parameter estimation has been accomplished using maximum likelihood (ML) techniques. Minimum distance (MD) estimation is examined as an alternative to ML where, in this investigation, both procedures are based upon normal components. Results indicate that ML techniques are superior to MD when component distributions actually are normal, while MD estimation provides better estimates than ML under symmetric departures from normality. When component distributions are not symmetric, however, it is seen that neither of these normal based techniques provides satisfactory results. |
| NASA分類 | EARTH RESOURCES AND REMOTE SENSING |
| レポートNO | 83N34395
SR-62-04376
E83-10402
NASA-CR-171678
NAS 1.26:171678 |
| 権利 | No Copyright |
| URI | https://repository.exst.jaxa.jp/dspace/handle/a-is/161562 |
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