期刊
STOCHASTIC MODELS
卷 30, 期 3, 页码 365-389出版社
TAYLOR & FRANCIS INC
DOI: 10.1080/15326349.2014.912947
关键词
Consumption Credit; Markov Chains; Open Populations; Parameter Inference
资金
- Fundacao para a Ciencia e Tecnologia, through CMA/FCT/UNL [PEst-OE/MAT/UI0297/2011]
- Fundação para a Ciência e a Tecnologia [PEst-OE/MAT/UI0297/2011] Funding Source: FCT
In this paper, we study, by means of randomized sampling, the long-run stability of some open Markov population fed with time-dependent Poisson inputs. We show that state probabilities within transient states converge-even when the overall expected population dimension increases without bound-under general conditions on the transition matrix and input intensities. Following the convergence results, we obtain ML estimators for a particular sequence of input intensities, where the sequence of new arrivals is modeled by a sigmoidal function. These estimators allow for the forecast, by confidence intervals, of the evolution of the relative population structure in the transient states. Applying these results to the study of a consumption credit portfolio, we estimate the implicit default rate.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据