Deconvolution by Simulation
Given samples (x₁,...,$x_{m}$) and (z₁,...,$z_{n}$) which we believe are independent realizations of random variables X and Z respectively, where we further believe that Z = X + Y with Y independent of X, the problem is to estimate the distribution of Y. We present a new method for doing this, invol...
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| Veröffentlicht in: | Lecture notes-monograph series 2007-01, Vol.54, p.1-11 |
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| container_title | Lecture notes-monograph series |
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| creator | Mallows, Colin |
| description | Given samples (x₁,...,$x_{m}$) and (z₁,...,$z_{n}$) which we believe are independent realizations of random variables X and Z respectively, where we further believe that Z = X + Y with Y independent of X, the problem is to estimate the distribution of Y. We present a new method for doing this, involving simulation. Experiments suggest that the method provides useful estimates. |
| doi_str_mv | 10.1214/074921707000000021 |
| format | Article |
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| fulltext | fulltext |
| identifier | ISSN: 0749-2170 |
| ispartof | Lecture notes-monograph series, 2007-01, Vol.54, p.1-11 |
| issn | 0749-2170 |
| language | eng |
| recordid | cdi_jstor_primary_20461455 |
| source | JSTOR Mathematics & Statistics; JSTOR Archive Collection A-Z Listing; Project Euclid Open Access; Project Euclid Complete |
| subjects | Estimation methods Gaussian distributions Hyperlinks Mathematical functions Mathematical vectors Outliers Random variables Random walk Statistics |
| title | Deconvolution by Simulation |
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