10. We have observed 110 anual values of the CPI, z,. Complete the spaces in order to explain the rational behind the following steps. Hand written plz (a) Firstly, we took logs and obtaines w₁ = log(z,), in order to obtain a series which is in (b) Then, we took the first differences x₁ = (1-B)w, trying to obtain a process. (c) Then, we subtracted the sample mean = 0.7 to these x,, in order to obtain a process with (d) Finally, we adjusted an AR(2) to the series (x,-0.7), which is equivalent to assume that w, is an ARIMA(_,_,__). (e) In order to verify whether the residuals are Ljung-Box test. 15 we performed the (f) We have obtained Q = n(n+2)Σ (109−k)¯¹² = 11.243<23.362 = x².05(13), where n = (g) This means we haven't rejected Ho: P₁ = P2 = ... = P15=. (h) That means we concluded that the model AR(2) is for the residuals. for the data (x,-0.7).
10. We have observed 110 anual values of the CPI, z,. Complete the spaces in order to explain the rational behind the following steps. Hand written plz (a) Firstly, we took logs and obtaines w₁ = log(z,), in order to obtain a series which is in (b) Then, we took the first differences x₁ = (1-B)w, trying to obtain a process. (c) Then, we subtracted the sample mean = 0.7 to these x,, in order to obtain a process with (d) Finally, we adjusted an AR(2) to the series (x,-0.7), which is equivalent to assume that w, is an ARIMA(_,_,__). (e) In order to verify whether the residuals are Ljung-Box test. 15 we performed the (f) We have obtained Q = n(n+2)Σ (109−k)¯¹² = 11.243<23.362 = x².05(13), where n = (g) This means we haven't rejected Ho: P₁ = P2 = ... = P15=. (h) That means we concluded that the model AR(2) is for the residuals. for the data (x,-0.7).
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Transcribed Image Text:10. We have observed 110 anual values of the CPI, z₁. Complete the spaces in order to explain
the rational behind the following steps. Hand written plz
(a) Firstly, we took logs and obtaines w₁ = log(z,), in order to obtain a series which is
in
(b) Then, we took the first differences x, = (1-B)w, trying to obtain a
process.
(c) Then, we subtracted the sample mean x = 0.7 to these x,, in order to obtain a process
with
(d) Finally, we adjusted an AR (2) to the series (x,-0.7), which is equivalent to assume that
w, is an ARIMA(__,_,_).
(e) In order to verify whether the residuals are
we performed the
Ljung-Box test.
15
(f) We have obtained Q = n(n+2) Σ(109—k)-¹p² = 11.243 < 23.362=X2.05(13), where
n =
(g) This means we haven't rejected Ho: P₁= P2 = = 1
. = P15 =
for the residuals.
J
(h) That means we concluded that the model AR (2) is
for the data (x,-0.7).
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