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The Effect of the First Observation in Regression Models with First‐Order Autoregressive Disturbances
Author(s) -
Poirier Dale J.
Publication year - 1978
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.2307/2346228
Subject(s) - autoregressive model , regression , star model , econometrics , order (exchange) , regression analysis , statistics , setar , mathematics , autoregressive integrated moving average , time series , economics , finance
Summary Based on well‐known updating formulae used in Kalman filtering and recursive residual estimation, this study presents simple formulae for determining the effect of including the first observation in regression models with first‐order autoregressive disturbances. These formulae describe the changes in coefficient estimates, variance estimates and covariance estimates in terms of similar quantities involving the first observation.