首页> 外文会议>IASTED International Conference on Modelling,Simulation and Optimization >LONG MEMORY IN PRODUCER PRICES OF SOUTH AFRICA'S TRADING PARTNERS: ARFIMA MODEL
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LONG MEMORY IN PRODUCER PRICES OF SOUTH AFRICA'S TRADING PARTNERS: ARFIMA MODEL

机译:南非贸易伙伴的生产者价格漫长记忆:Arfima Model

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The fractionally integrated autoregressive moving average model, denoted by ARFIMA can be used for the analysis of a univariate time series y{sub}t with long memory. The long run behavior of a time series can be modelled in a flexible way with the ARFIMA model. Models of long-memory processes include fractional Brownian noise[1] and the ARFIMA process introduced by [2] and [3]. Long memory entails that shocks or innovations to a time series do not have a persistent or a short-run transitory effect, but that they last for a long time. The producer prices of 10 trading partner countries of South Africa are modelled as fractionally integrated processes. The countries included are USA, UK, Japan, Korea, Canada, Singapore, Sweden, Israel, South Africa, Switzerland and Euro. Three parametric estimation procedures are used in the present study; one, due to [4] is the Exact Maximum Likelihood (EML) estimator, and the others are the nonlinear least squares (NLS) estimator by [5] and the Modified Profile Likelihood (MPL). These procedures are implemented using the ARFIMA package for the Ox program [6].
机译:由Arfima表示的分馏集成的自回归移动平均模型可用于分析单变量时间序列Y {Sub} T,具有长存储器。时间序列的长期行为可以用arfima模型以灵活的方式进行建模。长内存过程的模型包括分数褐色噪声[1]和[2]和[3]引入的arfima过程。长记忆需要对时间序列的冲击或创新没有持久或短期暂时效应,但它们持续很长时间。南非10个贸易伙伴国家的生产者价格被建模为分数综合的流程。包括的国家是美国,英国,日本,韩国,加拿大,新加坡,瑞典,以色列,南非,瑞士和欧元。本研究中使用了三个参数估计程序;一个,由于[4],由于精确的最大可能性(EML)估计器,并且其他是通过[5]的非线性最小二乘(NLS)估计器和修改的简档可能性(MPL)。使用氧气编程的arfima包来实现这些程序[6]。

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