Forecasting Trending Time Series with Relative Growth Rate Models
作者:
Hans Levenbach,
BlakeE. Reuter,
期刊:
Technometrics
(Taylor Available online 1976)
卷期:
Volume 18,
issue 3
页码: 261-272
ISSN:0040-1706
年代: 1976
DOI:10.1080/00401706.1976.10489446
出版商: Taylor & Francis Group
关键词: Forecasting;Percent Changes;Trend Models;Least Squares Regression;Approximate Confidence Limits
数据来源: Taylor
摘要:
Many annual time series in socioeconomic systems are steadily increasing functions of time. This paper deals with an empirical approach to analyzing and projecting such trending time series from models of relative growth rates or percent changes. A class of relative growth rate models is defined which includes the linear. exponential, modified exponential and logistic growth curves as special eases. Parameters are estimated for the most part by linear regression techniques since the, relative growth rates for this class of models are linear in the parameters. The ternd curve for each model is obtained by integration and approximate-confidence limits can be obtained for the forecasts of future series values.
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