Note on the strong consistency of the least squares estimator in nonlinear regression
- 1 January 1989
- journal article
- research article
- Published by Taylor & Francis in Statistics
- Vol. 20 (2), 199-210
- https://doi.org/10.1080/02331888908802161
Abstract
We consider a nonlinear regression model under standard assumptions on the error distribution, We prove an almost sure convergence of weighted sums with an interesting uniformity, and under very general conditions on the parameter space and the regression function we prove the a.s, boundedness and the strong consistency of the least squares estimator, Here we generalize results of Jennrich (1969) to unbounded parameter spacesKeywords
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