Non-Gaussian seasonal adjustment: X-12-ARIMA versus robust structural models
Article Abstract:
The X-12-ARIMA is a non-parametric seasonal adjustment method designed to handle additive outliers and level shifts. On the other hand, the MING is a mixture based non-Gaussian seasonal adjustment procedure based on time series models. Using 29 macroeconomic time series from the Bureau of Census, the two methods are compared with each other. Results indicate that use of the former leads to smoother and more flexible seasonal factors. However, the MING is more stable in predicting seasonal factors than the X-12-ARIMA.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 1996
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A flexible model of technological diffusion incorporating economic factors with an application to the spread of colour television onwership in the UK
Article Abstract:
An epidemic type model of technological diffusion which integrates economic factors is discussed. The proposed model permits a freer interaction of exogenous and endogenous factors in the diffusion process when compared with other existing models of the same type. The model is used in determining the pattern of diffusion of color television ownership in the UK. Results show the dominance of exogenous factors in the diffusion process.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 1992
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The role of prices in models of innovation diffusion
Article Abstract:
Tests of the integration of price into innovation diffusion models show that price affects the rate of adoption for a market that is launching a new product or service. However, such an inclusion does not quantify the model's 'fitness' or its predictive validity. One possible application of these results is to model the rate of adoption as a function of price in markets featuring inexpensive durable goods.
Publication Name: Journal of Forecasting
Subject: Mathematics
ISSN: 0277-6693
Year: 1998
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