Name
Abstract | ||
|---|---|---|
A parameter estimation problem for ellipsoid fitting in the presence of measurement errors is considered. The ordinary least squares estimator is inconsistent, and due to the nonlinearity of the model, the orthogonal regression estimator is inconsistent as well, i.e., these estimators do not converge to the true value of the parameters, as the sample size tends to infinity. A consistent estimator is proposed, based on a proper correction of the ordinary least squares estimator. The correction is explicitly given in terms of the true value of the noise variance. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1007/s00211-004-0526-9 | Numerische Mathematik |
Keywords | Field | DocType |
sample size,parameter estimation problem,consistent estimator,orthogonal regression estimator,measurement error,noise variance,squares estimator,proper correction,true value,ellipsoid fitting,parameter estimation,ordinary least square,least square | Minimum-variance unbiased estimator,Mathematical optimization,Newey–West estimator,Mathematical analysis,Generalized least squares,Bias of an estimator,Non-linear least squares,Total least squares,Linear least squares,Mathematics,Consistent estimator | Journal |
Volume | Issue | ISSN |
98 | 1 | 0029-599X |
Citations | PageRank | References |
22 | 2.88 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ivan Markovsky | 1 | 61 | 7.81 |
| A. Kukush | 2 | 60 | 8.24 |
| S. Van Huffel | 3 | 260 | 32.75 |