Asymptotic theory of least squares estimator in a nonregular nonlinear regression model
The asymptotic properties of the least squares estimator are derived for a nonregular nonlinear model via the study of weak convergence of the least squares process. This approach was adapted earlier by the author in the smooth case. The model discussed here is not amenable to analysis via the normal equations and Taylor expansions used by earlier authors.
weak convergence of the least squares process
scientific article; zbMATH DE number 3890546