Polynomial regression under a mixture of classical and Berkson errors with unknown moments of the latter error
MS student Oleksandr Liubimov (Taras Shevchenko National University of Kyiv and EPFL, Lausanne, Switzerland)
Abstract: Previously we gave consistent estimators for model parameters given the first 2d moments of Berkson error, where d is the power of the polynomial. Now we weaken this assumption and construct new estimators for the model parameters. In particular we estimate consistently the regression coefficients without information on moments of Berkson error.
probabilitystatistics theorydata analysis, statistics and probability
Audience: researchers in the topic
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Asymptotic Methods in Statistics
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| Organizers: | Alexander Kukush*, Rostislav Mayboroda |
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