Nathan Paxton schrieb:
>
> I don't need to use gretl to do the actual MI, but I wonder if there's
> any facility in gretl for doing analysis on separate MI-generated
> datasets and then combining the results according to the Rubin rules.
> That is, can gretl be told easily to run a procedure m ti
Ok, I've pretty much figured this out. My problem was that I didn't restrict
the sample to those in the relevant group before estimating the model. When I
do that I get the results I expected.
Sorry to bother you...
PS
From: gretl-users-bounces(a)lists.wfu.edu
El vie, 05-03-2010 a las 10:18 +0100, Jaroslaw Gramacki escribió:
> Suppose we have a Time series Data in gretl generated as a simple TS:
>
> z_t = p * z_{t-1} + u_t; -1 < p < 1
> x_t = a + b * t + z_t;
>
> Two scenarios:
>
> 1. We build an OLS model (no lags, static model)
> 2. We build Time s
Allin Cottrell schrieb:
> On Thu, 4 Mar 2010, Artur T. wrote:
>
>
>> for the same file and session as yesterday I just wanted to do some
>> further work. Gretl does not calculate estimations for a restricted VECM
>> and gives this error after the restriction block:
>> "Matrices not conformable f
Suppose we have a Time series Data in gretl generated as a simple TS:
z_t = p * z_{t-1} + u_t; -1 < p < 1
x_t = a + b * t + z_t;
Two scenarios:
1. We build an OLS model (no lags, static model)
2. We build Time series (say Cochrane-Orcutt) model (no lags, static model)
In scenario 1: If we mak
Suppose we have a Time series Data in gretl generated as a simple TS:
z_t = p * z_{t-1} + u_t; -1 < p < 1
x_t = a + b * t + z_t;
Two scenarios:
1. We build an OLS model (no lags, static model)
2. We build Time series (say Cochrane-Orcutt) model (no lags, static model)
In scenario 1: If we mak
Hi all,
I've recently discovered gretl, having been a fairly elementary user of
R and Stata for a few years.
I do work with multiple imputation datasets, and I generate them in R,
using the Amelia package. But the sorts of tests I want to run aren't easily
done using an
Folks,
I've just noticed some very strange behavior when I try to generate studentized
bootstrap confidence intervals in a model with only a constant (this is problem
5.6 in Davidson/MacKinnon's ETM). The model is earnings data regressed on a
dummy variable for a particular income group, so it'
