首页 | 本学科首页   官方微博 | 高级检索  
     


Time-series analysis supported by power transformations
Authors:Victor M. Guerrero
Abstract:
This paper presents some procedures aimed at helping an applied time-series analyst in the use of power transformations. Two methods are proposed for selecting a variance-stabilizing transformation and another for bias-reduction of the forecast in the original scale. Since these methods are essentially model-independent, they can be employed with practically any type of time-series model. Some comparisons are made with other methods currently available and it is shown that those proposed here are either easier to apply or are more general, with a performance similar to or better than other competing procedures.
Keywords:ARIMA models  Bias reduction  Forecasting  Taylor series approximation  Time-series models  Variance-stabilizing
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号