Regression analysis of autocorrelated poisson-distribution) data |
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Authors: | Lap-Ming Wun |
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Institution: | Division of Cancer Prevention and Control , National Cancer Institute , 9000 Rockville Pike, EPS/313, Bethesda, Maryland, 20892 |
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Abstract: | A regression model assuming Poisson-dia distributed data. with autocorrelated errors falls into the class of regression models that; have the error structure which is both heteroscedastic and autocorrelated. In general, this class of regression models are not estimable. However, due to the properties of the Poisson distribution that the variance is equal to the mean, this regression model on Poisson-distributed data with autocorrelated. errors is estimable. In this note the special structure of the covarlance matrix of the model with the first order auto-correlated error Is derived utilizing this property, A method based on the least squares method of Frome, Kutner, and Beauchamp (1973), supplemented by steps for handling autocorrelation in studies of time series analysis, nonlinear regression, and econometrics is presented for obtaining generalized least squares estimates for the parameters of the model. |
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Keywords: | Autocorrelation generalized least squares heteroscedasticity Poisson distribution repeated measurement |
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