ANALISIS CRITICAL ROOT VALUE PADA DATA NONSTASIONER
ABSTRACT: A stationery process
can be done t-test, on the contrary at non stationery process t-test cannot be
done again because critical value of this process isn’t t-distribution. At this
research, we will do simulation of time series AR(1) data in four non
stationery models and doing unit root test to know critical value at ttest of
non stationery process. From the research is yielded that distribution of
critical point for t-test of non stationery process comes near to normal with
restating simulation of random walk process which ever greater. Result of
acquirement of this critical point has come near to result of Dickey-Fuller
Test. From this research has been obtained critical point for third case which
has not available at tables result of Dickey-Fuller Test.
Penulis: Abdul Aziz
Kode Jurnal: jpmatematikadd110139
