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Analysis of low count time series data by poisson autoregression
Author(s) -
Freeland R. K.,
McCabe B. P. M.
Publication year - 2004
Publication title -
journal of time series analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.576
H-Index - 54
eISSN - 1467-9892
pISSN - 0143-9782
DOI - 10.1111/j.1467-9892.2004.01885.x
Subject(s) - mathematics , autoregressive model , count data , poisson distribution , statistics , series (stratigraphy) , econometrics , data set , overdispersion , poisson regression , information criteria , goodness of fit , fisher information , time series , model selection , paleontology , population , demography , sociology , biology
. This study provides new methods of assessing the adequacy of the Poisson autoregressive time‐series model for count data. New expressions are given for the score function and the information matrix and these lead to the construction of new types of residuals for this model. However, these residuals often need to be supplemented by formal statistical procedures and an overall test of the model adequacy is given via the information matrix equality that holds for correctly specified models. The techniques are applied to a monthly count data set of claimants for wage loss benefit, in order to estimate the the expected duration of claimants in the system.