Sometime ago there was a discussion on this list about the feasibility of
running gretl on Android. I have been looking at some of the recent
developments on the Google play store. In particular the app GNURoot
provides a method to install and run Linux applications on an Android
device without needing to root the device. One then installs a Linux
rootfs. I installed the Debian Wheezy rootfs app from the play store. Using
this I have installed R, emacs, ess and gretl using standard apt-get. The R
inferior process works with emacs. As regards gretl gretlcli works as
expected but gretl_x11 can not start the display.
This was done on a Kobo Arc running Android 4.1.1. The author of these
apps has a good version of Octave and various octave packages available on
the play store. There is also a version of Maxima for Octave available.
Proof of what can be done? Personally I will not be selling my laptop or
desktop and moving to Android in the short run.
John C Frain
3 Aranleigh Park
Created forecast variance decomposition graph, style = stacked bars.
Edited title. When I pressed "Apply", the stacked bars styles
disappeared (became crosses, stars and boxes that mark the points that
wold have been used in a line graph).
I am facing a problem with estimating panel regression with Random Effects.
I did not find any way how to persuade Gretl to compute R-Squared.
Could you give me advice? Thank you very much for replies.
Mobil.: +420 728 431 027
[image: ICON] <http://cz.linkedin.com/in/ondrejdvoulety/>
273 79 TUŘANY U SLANÉHO
Dear Gretl Community,
I would like to know if the following "strategies" could improve my scripts
in terms of the execution time:
(1) Write/open gdt files is faster than csv files?
(2) Using Gretl's home directory (located at my hard drive) is faster than
use a network drive?
(3) Specify the object type could reduce the execution time? (e.g. "scalar
x = 2" instead of "x = 2")
(4) Short variables/lists names could reduce the execution time?
(5) Matrices are longer than series (I'm talking about computer memory
Dear all, I am trying to ML estimate a model from http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1884237 and the following code, with Rng being the variable of interest,
RANGE = Rng
scalar rng = 0.1
scalar err = 0.2
scalar gamma = 1
mle ll = 0.5*ln(theta) - theta*lambda + RANGE *(ln(RANGE)-1) - lngamma(RANGE+1) + theta*RANGE( 1 + ln(lambda/RANGE))
series lambda = mean(RANGE)
series lambda = c + rng*RANGE(-1) + err*lambda(-1)
params gamma c rng err
end mle --robust
returns "lag order: argument 2 should be scalar, is series. Data types not conformable for operation". As far as I undestand, the problem is the first element of LL, but have no clue how to correct it. Any hint is much appreciated.