STATIONARY OF AUTOREGRESSIVE MODEL THROUGH CHARACTERISTIC EQUATION AND UNIT ROOT TEST
Autoregressive model (AR) is one of the applications from the stochastic process. This model is aimed to predict the future value using the previous observations. Time series stationary can be described from the model that is dened in the dif- ference equation. On the other hand, the time series...
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id-itb.:341532019-02-04T15:58:43ZSTATIONARY OF AUTOREGRESSIVE MODEL THROUGH CHARACTERISTIC EQUATION AND UNIT ROOT TEST Herlambang, Wahyu Matematika Indonesia Final Project Time series, Stationary, Dierence equation, Characteristic equation, eigenvalues, Maximum likelihood estimation, Bias parameter, Unit root. INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/34153 Autoregressive model (AR) is one of the applications from the stochastic process. This model is aimed to predict the future value using the previous observations. Time series stationary can be described from the model that is dened in the dif- ference equation. On the other hand, the time series stationary can be seen from the rst two-moment that is time invariant. The AR model is being used in this nal paper are AR(1) and AR(2). There are some parameters in the models must be estimated to give the representative result between the model and the sample data. The parameter estimation can be achieved through the maximum likelihood estimation. the autoregressive time series stationary is usually tested by unit root test which is aimed to test the eigenvalues of the characteristic equation from the autoregressive model through their parameters. text |
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Matematika Herlambang, Wahyu STATIONARY OF AUTOREGRESSIVE MODEL THROUGH CHARACTERISTIC EQUATION AND UNIT ROOT TEST |
| description |
Autoregressive model (AR) is one of the applications from the stochastic process.
This model is aimed to predict the future value using the previous observations.
Time series stationary can be described from the model that is dened in the dif-
ference equation. On the other hand, the time series stationary can be seen from
the rst two-moment that is time invariant. The AR model is being used in this
nal paper are AR(1) and AR(2). There are some parameters in the models must
be estimated to give the representative result between the model and the sample
data. The parameter estimation can be achieved through the maximum likelihood
estimation. the autoregressive time series stationary is usually tested by unit root
test which is aimed to test the eigenvalues of the characteristic equation from the
autoregressive model through their parameters. |
| format |
Final Project |
| author |
Herlambang, Wahyu |
| author_facet |
Herlambang, Wahyu |
| author_sort |
Herlambang, Wahyu |
| title |
STATIONARY OF AUTOREGRESSIVE MODEL THROUGH CHARACTERISTIC EQUATION AND UNIT ROOT TEST |
| title_short |
STATIONARY OF AUTOREGRESSIVE MODEL THROUGH CHARACTERISTIC EQUATION AND UNIT ROOT TEST |
| title_full |
STATIONARY OF AUTOREGRESSIVE MODEL THROUGH CHARACTERISTIC EQUATION AND UNIT ROOT TEST |
| title_fullStr |
STATIONARY OF AUTOREGRESSIVE MODEL THROUGH CHARACTERISTIC EQUATION AND UNIT ROOT TEST |
| title_full_unstemmed |
STATIONARY OF AUTOREGRESSIVE MODEL THROUGH CHARACTERISTIC EQUATION AND UNIT ROOT TEST |
| title_sort |
stationary of autoregressive model through characteristic equation and unit root test |
| url |
https://digilib.itb.ac.id/gdl/view/34153 |
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1823637506668625920 |