Search found 5 matches
- 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...
- 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!
- 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...
- 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...
- 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...
