unable to save a bundle out of a bundle via GUI
by Pindar
Hi,
while working with felogit.gfn I noticed that it is not possible to save
an already stored bundle out of a bundle via GUI
<hansl>
bundle bA = null
bundle bB = null
bA["newB"] = bB
bundle newB = bA["newB"] # works in script but not via GUI
<hansl>
I'm using gretl x64 on Windows 8.1.
Cheers
Leon
12 years, 12 months
ADF test
by antonio.puca＠enel.com
Hello Gretl community,
I have a request...My time series is based on daily data but I need monitor mean reverting tendency (using ADF test coefficient) for each monthly subset. My output would be an ADF test on monthly group of my daily time series.
Thanks a lot
12 years, 12 months
DOLS
by Claudio Shikida (敷田治誠 クラウジオ)
Hi
Just one question: is there any script for gretl that calculate DOLS (Stock
& Watson 1993)?
Thank you
Claudio
Obrigado / Thanks for your time and attention.
Claudio D. Shikida
http://www.cdshikida.net and http://works.bepress.com/claudio_shikida/
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12 years, 12 months
Poisson with Offset
by Pindar
Hi,
I'd like to replicate the coefficients obtained by 'poisson ; offset'
with MLE statements.
Here is an example that shows the differences.
Btw, is there a more efficient way of coding the MLE e.g. in case of 20
regressors?
Cheers
Leon
<hansl>
open rac3d.gdt --quiet
list X = SEX INCOME
# Poisson regression
poisson DVISITS 0 X
# Initial OLS to get starting values for the coefficients
ols DVISITS 0 X --quiet
list xList = $xlist
matrix b = zeros(1,nelem(xList))
mle loglik = DVISITS*Xb - exp(Xb)
series Xb = lincomb(xList,b)
deriv b = {DVISITS - exp(Xb), \
SEX*(DVISITS - exp(Xb)), \
INCOME*(DVISITS - exp(Xb))}
end mle --hessian
# Poisson regression with Offset
poisson DVISITS 0 X ; AGE
series DVISITS_off = DVISITS/AGE #*try*
mle loglik = DVISITS_off*Xb - exp(Xb)
series Xb = lincomb(xList,b)
deriv b = {DVISITS_off - exp(Xb), \
SEX*(DVISITS_off - exp(Xb)), \
INCOME*(DVISITS_off - exp(Xb))}
end mle --hessian
<hansl>
12 years, 12 months
mols() and openmp support
by Artur T.
Hi I just saw that the mols() function now supports
parallelization. Just out of curiosity: How high is
the efficiency gain to to be expected?
Cheers,
Artur
13 years
data standardization
by antonio.puca＠enel.com
Hello Gretl communuty,
i'm writing for an easy question (I hope). I need to standardize a daily time series based on a monthlly mean and standard deviation (not global mean and standard deviation, this is the main problem). I've tried with matrix but I'm not able to convert a matrix, which is made with an aggregate function (based on monthly mean and stddev), in a variable in my TS with almost 300 obs.
13 years
Structural break tests
by Julien Chevallier
Greetings everyone,
it is perhaps a bit late to ask, but I would like to run some structural
break tests in Gretl with my class (in computer lab).
Is there any way to run Bai-Perron or Zivot Andrews? I'd like to go further
than Chow test
Thanks a lot
Julien,
University Paris 8
13 years
confirm 347f524a4442c508a98e82c988136a617471d39b
by antonio.puca＠enel.com
Antonio Puca
Enel Trade SpA
Energy Management Business Area - Origination
Viale Regina Margherita 125 - 00198 Roma - Italia
Tel: +39 06 8305 9333
Email: Antonio.Puca(a)enel.com<mailto:antonio.puca@enel.com>
[cid:image001.png@01CC4223.F4030930]
13 years
summary command within variation
by Pindar
Hi there,
I noticed that the summary command does show the within and between
variation for a series but not for lists.
Hence, I wanted to calculate the variation components with a UDF.
On page 33 of this presentation
http://fmwww.bc.edu/repec/msug2010/mex10sug_trivedi.pdf
the stata output for the series mdu of the data set 'mus18data.dta'
(http://fmwww.bc.edu/ec-p/data/mus/) is shown.
The only difference to the gretl output is the calculated within variation:
STATA 2.5759
gretl 3.0627
When trying to calculate it myself I came up with totally different
outcomes.
How is it correct? Is there 'a' correct method?
Cheers
Leon
<hansl>
summary mdu
series x_bar_i= pmean(mdu)
series x_bar = mean(mdu)
## between variation
eval sd(pmean(mdu)) # OK
eval sqrt(sum(((x_bar_i-x_bar)^2))/5908/5) # OK, Baltagi (2003) p.76f
*## within variation*
eval mean(psd(mdu)) # *wrong*
eval sqrt(sum((mdu-x_bar_i)^2)/5908/5) # *wrong*, Baltagi (2003) p.76
<hansl>
13 years
