{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

info abt final exam

# info abt final exam - characteristic equation are real and...

This preview shows page 1. Sign up to view the full content.

STA 4005B Final Examination (Total Marks 100) [55% of the Overall marks] Close-book and close-notes Approved calculators are allowed. Topics may include: 1. Given a time series { Z t } , calculate E ( Z t ) , V ar ( Z t ) , γ t,s , γ k , ρ t,s , ρ k . 2. Stationary - Weakly Stationary (Stationary)/ Strictly stationary. 3. Models of regression type (a) No need to memorize the formulas of ˆ β 0 , ˆ β 1 , V ar ( ˆ β 0 ), V ar ( ˆ β 1 ). (b) No question on cosine trend model. 4. AR(p), MA(q), ARMA(p,q), AR characteristic polynomial/equation, MA char- acteristic polynomial/equation, Yule Walker equations, the conditions of sta- tionarity and invertibility, representation forms of Z t = ψ ( B ) a t , a t = π ( B ) Z t , the general form of ρ k for an AR(2) model for the case where the roots of the
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: characteristic equation are real and distinct. 5. Identifying a speciﬁed ARIMA(p,d,q) model, To write Z t in terms of W t , Con-stant term in ARIMA model, Eﬀect of a nonzero mean for W t on Z t . 6. Overall strategy - Box Jenkins Approach, pacf φ kk , over diﬀerencing. 7. Method of moments, (conditional) least square estimation method, maximum likelihood estimation method (for AR(1) only). 8. Portmanteau test, Parameter redundancy. 9. MMSE error prediction, MMSE forecast, forecast error, prediction interval, up-dating. 10. Multiplicative seasonal ARIMA( p,d,q ) × ( P,D,Q ) s model....
View Full Document

{[ snackBarMessage ]}