In this article, we study parametric robust estimation in nonlinear regression models with regressors generated by a class of non-stationary and null recurrent Markov processes. The functions can be either integrable or asymptotically homogeneous, covering many commonly-used functional forms regression. Under regularity conditions, derive both the consistency limit distribution results for deve...

the deformation modulus of a rock mass is an important input parameter in any analysis of rock mass behavior for geotechnical projects such as dams. the determination of this parameter by in situ tests are time consuming and expensive. therefore, different researchers have proposed empirical relationships for estimating the value of rock mass deformation modulus. this work has been done by usin...

A wide variety of neural and statistical methods are available for nonlinear empirical modeling based on different modeling approaches. Selecting the best method for a given task requires deep understanding of their similarities and differences and a systematic approach to method selection. This paper presents a common framework for gaining insight into neural and statistical modeling methods. ...