کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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1144587 | 957422 | 2015 | 7 صفحه PDF | دانلود رایگان |
We are concerned with the stochastic process for which the likelihood of the data, although it does exist, is possibly unknown to us. In order to estimate parameter, we are led to appropriate estimating functions (EF, for short) including the (quasi) maximum likelihood score. A formal definition of the general non-ergodic estimating function is made in this paper. This can be viewed as a generalization of the non-ergodic maximum likelihood score (due to Basawa and Koul (1979), and Basawa and Scott (1983)) toward the theory of EFs. In addition, some characterizations on the non-ergodic EFs are made. It is interesting to note non-standard cases where non-stationary process may yield an ergodic EF while stationary process can produce a non-ergodic EF. Various examples are presented to illustrate the main results.
Journal: Journal of the Korean Statistical Society - Volume 44, Issue 4, December 2015, Pages 661–667