On Thu, 7 Jan 2016, Jan Tille wrote:
Dear list members,
I am trying to estimate several quantile regressions, each with a
constant and a single regressor, on a rolling basis (497 steps). The
quantile vector is set to q={0.1, 0.25, 0.5, 0.75, 0.90) yielding 5
quantile regressions per step and individual (1317). Using a simple
weighting scheme, where the weights sum to 1, the estimated conditional
quantiles ("y-hats") are aggregated so that this yield one estimate per
step.
Overall, I have 16 regressors and at the end, I intend to obtain one
matrix for each regressor. At the end of the day, this should amount to
497 (steps) * 1317(indiviuals) * 16(regressors) * 5(quantiles) =
5,236,392,0 quantile regressions.
[...]
The only piece of advice I have for you at this stage, is: try reducing
the size of your problem by cutting down the number of individuals and/or
the number of steps, if possible. If the problem persists even with a much
smaller combination, then the problem is most likely with gretl and
we'll be able to diagnose what the problem is. If the problem goes away,
perhaps the data you dropped contain some oddness. By some trial and
error you should be able to isolate the offending observations and, again,
we should be able to trace the cause(s) of your problem.
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Riccardo (Jack) Lucchetti
Dipartimento di Scienze Economiche e Sociali (DiSES)
Università Politecnica delle Marche
(formerly known as Università di Ancona)
r.lucchetti(a)univpm.it
http://www2.econ.univpm.it/servizi/hpp/lucchetti
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