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A comparison of minimum distance and maximum likelihood techniques for proportion estimation
| Content Provider | NASA Technical Reports Server (NTRS) |
|---|---|
| Author | Schucany, W. R. Gray, H. L. Woodward, W. A. Lindsey, H. |
| Copyright Year | 1982 |
| Description | 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. |
| File Size | 1745591 |
| Page Count | 30 |
| File Format | |
| Alternate Webpage(s) | http://archive.org/details/NASA_NTRS_Archive_19830026124 |
| Archival Resource Key | ark:/13960/t80k76j24 |
| Language | English |
| Publisher Date | 1982-11-01 |
| Access Restriction | Open |
| Subject Keyword | Earth Resources And Remote Sensing Mixtures Earth Resources Program Agristars Project Proportion Statistical Distributions Earth Resources Estimating Crop Inventories Farm Crops Maximum Likelihood Estimates Normality Ntrs Nasa Technical Reports Server (ntrs) Nasa Technical Reports Server Aerodynamics Aircraft Aerospace Engineering Aerospace Aeronautic Space Science |
| Content Type | Text |
| Resource Type | Technical Report |
