The First Order Autoregressive Model with Coefficient Contains Non-Negative Random Elements: Simulation and Esimation  

作　　者：Pham Van Khanh 

机构地区：[1]Military Technical Academy, Hanoi, Vietnam

出　　处：《Open Journal of Statistics》2012年第5期498-503,共6页统计学期刊（英文）

摘　　要：This paper considered an autoregressive time series where the slope contains random components with non-negative values. The authors determine the stationary condition of the series to estimate its parameters by the quasi-maximum likelihood method. The authors also simulates and estimates the coefficients of the simulation chain. In this paper, we consider modeling and forecasting gold chain on the free market in Hanoi, Vietnam.This paper considered an autoregressive time series where the slope contains random components with non-negative values. The authors determine the stationary condition of the series to estimate its parameters by the quasi-maximum likelihood method. The authors also simulates and estimates the coefficients of the simulation chain. In this paper, we consider modeling and forecasting gold chain on the free market in Hanoi, Vietnam.

关 键 词：Random COEFFICIENT AUTOREGRESSIVE Model Quasi-Maximum LIKELIHOOD CONSISTENCY 

分 类 号：O1[理学—数学]