In a recent study posted to the medRxiv* preprint server, an interdisciplinary team of researchers from the United States (US) assessed predictions of the laboratory-confirmed coronavirus disease 2019 ...
The distributed lag model (DLM), used most prominently in air pollution studies, finds application wherever the effect of a covariate is delayed and distributed through time. We specify modified ...
A methodology is introduced for identifying dynamic regression or distributed lag models relating two time series. First, specification of a bivariate time-series model is discussed, and its ...
Although recent articles have stressed the importance of testing for unit roots and cointegration in time-series analysis, practitioners have been left without a straightforward procedure to implement ...
This example shows the use of the %PDL macro for polynomial distributed lag models. Simulated data is generated so that Y is a linear function of six lags of X, with the lag coefficients following a ...
The Dynamic Regressor option allows you to specify a complex time series model of the way that a predictor variable influences the series that you are forecasting. When you specify a predictor ...
This study found interesting, complex and important interactive effects among meteorological factors and ambient air pollutants on influenza incidences in Huaian, China.
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