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Approximate Method of Estimation of Exponential Trend Parameters for Forecasting Process Purposes

机译:用于预测过程目的的指数趋势参数估计的近似方法

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The paper discusses the issue of estimation of exponential trend parameters in terms of its application in the forecast process. Due to the character of a random element, three models were considered: additive, multiplicative, and mixed. For estimating trend parameters, a log transformation method, least squares method, and approximate methods were applied. As a result of computer simulations, high sensitivity of the log transformation method with regard to the assumed random element model was noticed. This method yields the smallest value of ex post error for the multiplicative model but is burdened with a large error for the additive model, where the estimated parameter B takes large values (B > 0.24). In the paper, a new approximate method of estimation of exponential trend parameters is proposed. The method is compared with approximate formulas presented in the paper by Purczyński (2008).
机译:本文讨论了指数趋势参数估计在预测过程中的应用问题。由于随机元素的特性,考虑了三个模型:加性,乘法和混合模型。为了估计趋势参数,应用了对数变换方法,最小二乘法和近似方法。作为计算机仿真的结果,注意到对数变换方法相对于假定的随机元素模型的高灵敏度。对于乘法模型,此方法产生事后误差的最小值,但对于加法模型,则产生较大误差,其中估计参数B取大值(B> 0.24)。提出了一种新的指数趋势参数估计的近似方法。该方法与Purczyński(2008)在论文中提出的近似公式进行了比较。

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