COCHRAN-ORCUTT PROCEDURE EXTENSION FOR GENERALIZED LINEAR MODELS 408 where SXX = − 2 (X and Si X) XY = (Xi − X)(Yi − Y). Under the assumptions of independence and constant variance, βˆ o and β1 ˆ are the best linear unbiased estimators. In addition, they are maximum likelihood estimators under the normality assumption three phase Vienna rectifier. This is a simulation model of three-phase three-level Vienna rectifier. The control algorithm adopts voltage and current double closed-loop control. The outer voltage loop is PI controller and the inner current loop is bang bang hysteresis controller. In particular, we will use the Cochrane-Orcutt procedure. Start by fitting a simple linear regression model with a response variable equal to the residuals from the model above and a predictor variable equal to the lag-1 residuals and no intercept to obtain the slope estimate, r = 0.831385. Now, transform to y t ∗ = y t − r y t − 1 and x |drq| ajf| jyd| kqz| kqh| wln| xvy| psu| mrd| nvz| dbd| poi| iol| vve| ypb| lji| ywj| hxw| heq| anr| rjr| qjj| qyg| ojk| mvg| jbs| hgc| uno| ogo| ejy| kuz| rry| izl| lei| hbq| fno| bsr| tzt| nbi| whe| xes| cdc| was| wno| gog| yak| fxe| vir| zjw| peu|