کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1149359 | 957875 | 2011 | 19 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Quasi- and pseudo-maximum likelihood estimators for discretely observed continuous-time Markov branching processes
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
ریاضیات کاربردی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Quasi- and pseudo-maximum likelihood estimators for discretely observed continuous-time Markov branching processes Quasi- and pseudo-maximum likelihood estimators for discretely observed continuous-time Markov branching processes](/preview/png/1149359.png)
چکیده انگلیسی
This article deals with quasi- and pseudo-likelihood estimation for a class of continuous-time multi-type Markov branching processes observed at discrete points in time. “Conventional” and conditional estimation are discussed for both approaches. We compare their properties and identify situations where they lead to asymptotically equivalent estimators. Both approaches possess robustness properties, and coincide with maximum likelihood estimation in some cases. Quasi-likelihood functions involving only linear combinations of the data may be unable to estimate all model parameters. Remedial measures exist, including the resort either to non-linear functions of the data or to conditioning the moments on appropriate sigma-algebras. The method of pseudo-likelihood may also resolve this issue. We investigate the properties of these approaches in three examples: the pure birth process, the linear birth-and-death process, and a two-type process that generalizes the previous two examples. Simulations studies are conducted to evaluate performance in finite samples.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Statistical Planning and Inference - Volume 141, Issue 7, July 2011, Pages 2209-2227
Journal: Journal of Statistical Planning and Inference - Volume 141, Issue 7, July 2011, Pages 2209-2227
نویسندگان
Rui Chen, Ollivier Hyrien,