Search found 5 matches

by Per
Thu Mar 09, 2017 2:16 am
Forum: Estimation
Topic: Calculate SSR for ARMA models
Replies: 0
Views: 3010

Calculate SSR for ARMA models

Hi, I would like to compare the SSR of linear models vs models on logged data. I understand I therefore need to calculate SSR manually, as EViews output the SSR for the transformed variable. I thought I would use the .fit command to do an in sample static forecast in order to get y_hat values and th...
by Per
Fri Jan 20, 2017 4:38 am
Forum: Data Manipulation
Topic: Graph confidence intervals as area bands
Replies: 2
Views: 5193

Re: Graph confidence intervals as area bands

And immediately found it after posting, mixed graph option!
by Per
Fri Jan 20, 2017 4:22 am
Forum: Data Manipulation
Topic: Graph confidence intervals as area bands
Replies: 2
Views: 5193

Graph confidence intervals as area bands

Hi, I have generated a forecast series and two series confidence intervals in Eviews (time series). Now I would like to plot a line graph for the forecast, and the confidence intervals as a shaded area in the same graph. I would like something that looks like this: http://blogs.sas.com/content/sastr...
by Per
Wed May 11, 2016 8:19 am
Forum: Estimation
Topic: Forecast errors for geometric random walk
Replies: 1
Views: 2812

Re: Forecast errors for geometric random walk

Hi again, To partly answer my own questions (if anyone else is interested), and reiterate the questions I still don't understand. 1. According to chapter 23 of the Eviews manual, forecast errors for a non-linear transformation will be a) exact in the +-2 sterror output graph generated by the forecas...
by Per
Tue May 03, 2016 2:51 am
Forum: Estimation
Topic: Forecast errors for geometric random walk
Replies: 1
Views: 2812

Forecast errors for geometric random walk

Hi! I am trying to generate confidence intervals for a k step prediction of a geometric random walk with drift. First, I estimate the drift parameter by running a least squares regression on DLOG(X) on data from 1950-2011 as per below, whereby the constant (C) in the regression is the point estimate...

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