TY - JOUR
T1 - Damped trend exponential smoothing
T2 - A modelling viewpoint
AU - Mckenzie, Edward
AU - Gardner Jr, Everette S.
PY - 2010/12
Y1 - 2010/12
N2 - Over the past twenty years, damped trend exponential smoothing has performed well in numerous empirical studies, and it is now well established as an accurate forecasting method. The original motivation for this method was intuitively appealing, but said very little about why or when it provided an optimal approach. The aim of this paper is to provide a theoretical rationale for the damped trend method based on Brown's original thinking about the form of underlying models for exponential smoothing. We develop a random coefficient state space model for which damped trend smoothing provides an optimal approach, and within which the damping parameter can be interpreted directly as a measure of the persistence of the linear trend.
AB - Over the past twenty years, damped trend exponential smoothing has performed well in numerous empirical studies, and it is now well established as an accurate forecasting method. The original motivation for this method was intuitively appealing, but said very little about why or when it provided an optimal approach. The aim of this paper is to provide a theoretical rationale for the damped trend method based on Brown's original thinking about the form of underlying models for exponential smoothing. We develop a random coefficient state space model for which damped trend smoothing provides an optimal approach, and within which the damping parameter can be interpreted directly as a measure of the persistence of the linear trend.
KW - time series
KW - state space models
KW - ARIMA models
KW - exponential smoothing
UR - http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V92-4WXBTM9-1&_user=875629&_coverDate=12%2F31%2F2010&_rdoc=1&_fmt=high&_orig=gateway&_origin=gateway&_sort=d&_docanchor=&view=c&_searchStrId=1700853985&_rerunOrigin=google&_acct=C000046979&_version=1&_urlVersion=0&_userid=875629&md5=8f9d51baf0569bddee1a072d6e564328&searchtype=a
U2 - 10.1016/j.ijforecast.2009.07.001
DO - 10.1016/j.ijforecast.2009.07.001
M3 - Article
SN - 0169-2070
VL - 26
SP - 661
EP - 665
JO - International Journal of Forecasting
JF - International Journal of Forecasting
IS - 4
ER -