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421.
Many researchers have used time series models to construct population forecasts and prediction intervals at the national level,
but few have evaluated the accuracy of their forecasts or the out-of-sample validity of their prediction intervals. Fewer
still have developed models for subnational areas. In this study, we develop and evaluate six ARIMA time series models for
states in the United States. Using annual population estimates from 1900 to 2000 and a variety of launch years, base periods,
and forecast horizons, we construct population forecasts for four states chosen to reflect a range of population size and
growth rate characteristics. We compare these forecasts with population counts for the corresponding years and find precision,
bias, and the width of prediction intervals to vary by state, launch year, model specification, base period, and forecast
horizon. Furthermore, we find that prediction intervals based on some ARIMA models provide relatively accurate forecasts of
the distribution of future population counts but prediction intervals based on other models do not. We conclude that there
is some basis for optimism regarding the possibility that ARIMA models might be able to produce realistic prediction intervals
to accompany population forecasts, but a great deal of work remains to be done before we can draw any firm conclusions. 相似文献
422.
The method of Gupta (1956, 1965) was developed to select a subset from k normal populations that contains the best populations with given probability. This paper shows a duality between the general goal of selecting a subset for the best population and many-one tests. A population should be regarded as ‘candidate’ for the best population and thus retained in the subset if the samples from the other populations are not significantly better. Based on this ‘idea’ a general selection procedure is proposed using many-one tests for the comparison of each population against the remaining ones. 相似文献
423.
Pendl Manfred Hussain Raja Imran Moser Dietmar Frank Thomas Drapela Thomas 《Urban Ecosystems》2022,25(2):477-486
Urban Ecosystems - Although urbanization is increasing worldwide, private gardens may help mitigate the impact of urbanization on butterfly diversity. We investigated how local and landscape... 相似文献