Am 28.02.2024 um 09:37 schrieb Brian
Revell:
There
is an irritation in using the Forecast Function in Analysis in
that it treats Panel data as a continuum between adjacent
panel units in plotting by observation number sequence. So as
illustrated below, there are 21 annual observations in Panel 1
ending in 2021. However the forecast funtion treats this as as
a observation continuum from 1:21 to 2:01(year 2001) and plots
an irritaing line between1:21 and 2:01......and similarly
between all the adjacent 10 Panel Units. Is there anyway to
suppress this joining line, as the forecast graph plots
beautiful CI shaded areas.
The
workaround is to transfer the data to Excel -but that does not
provided a shaded 95% CI -which is clearly more elegant -only
the ability to plot the Upper and lower CI bounds as lines..
Hi Brian,
I am running the forecast function via the Estimated Model output/ /Analysis/Forecast in the GUI. My aim is not to generate forecasts beyond time period 2021 but simply to produce a prediction for actual Y values (not mean) with associated 95% CI spread. This works perfectly (see data section below). The graph however, as I said , seems to join the datapoints from adjacent panel data units i.e .it will add a line between observation 1:21 and 2:01 etc. for the dependent variable l_RSE (the number of returning adult salmon) The graph of the prediction, acutal and CI joins inserts a line joining the final value of Y (ln RSE) in 1:21 to that of 2:01 , 2:21 to 3:01 et al.. . The graph is generated by selecting 0 for the number of preforecast obsvns to graph and a tick in checkbox for show fitted values for preforecast range
l_RSE prediction std. error 95% interval1:01
1:01
1:02
1:03
1:04
1:05 7.184629
1:06 7.034388 6.894189 0.282773 6.335766 - 7.452613
1:07 6.697034 6.633725 0.282741 6.075366 - 7.192085
1:08 6.632002 6.691674 0.282374 6.134040 - 7.249307
1:09 6.411818 6.456549 0.284239 5.895231 - 7.017867
1:10 6.661855 6.971589 0.285004 6.408761 - 7.534417
1:11 6.635947 6.491402 0.283699 5.931152 - 7.051652
1:12 6.670766 6.814620 0.282740 6.256262 - 7.372978
1:13 6.526495 6.500384 0.282566 5.942371 - 7.058397 PANEL UNIT 1 -River No. 1
1:14 7.074117 7.339223 0.289105 6.768296 - 7.910149
1:15 7.193686 7.441791 0.285464 6.878053 - 8.005528
1:16 6.944087 7.205822 0.283033 6.646886 - 7.764759
1:17 6.601230 6.696775 0.283867 6.136192 - 7.257357
1:18 6.556778 6.177856 0.285445 5.614156 - 6.741556
1:19 7.309881 6.955872 0.283390 6.396231 - 7.515514
1:20 6.963190 6.860621 0.283066 6.301620 - 7.419622
1:21 6.729824 6.452257 0.284134 5.891148 - 7.013367
2:01 6.952729
2:02 5.905362
2:03 7.029088 7.102234 0.295125 6.519420 - 7.685049
2:04 7.018402 7.091428 0.286250 6.526138 - 7.656717
2:05 6.964136 6.865752 0.286381 6.300206 - 7.431299
2:06 6.498282 6.909504 0.286639 6.343447 - 7.475561
2:07 7.304516 7.068966 0.289634 6.496995 - 7.640937
2:08 6.805723 6.882406 0.288406 6.312860 - 7.451953
2:09 6.725034 6.891609 0.286613 6.325603 - 7.457614
2:10 6.887553 7.073868 0.288169 6.504789 - 7.642946Panel Unit 2 River No. 2
2:11 6.855409 6.920967 0.288442 6.351349 - 7.490584
2:12 6.927558 7.083822 0.286813 6.517421 - 7.650222
2:13 6.908755 6.889174 0.286116 6.324149 - 7.454199
2:14 7.604396 7.255976 0.287378 6.688459 - 7.823493
2:15 7.282074 7.247741 0.288574 6.677862 - 7.817620
2:16 7.522941 7.159051 0.286828 6.592620 - 7.725482
2:17 6.526495 6.772668 0.290510 6.198966 - 7.346371
2:18 6.891626 6.668582 0.288539 6.098773 - 7.238391
2:19 7.988543 7.155666 0.287025 6.588847 - 7.722484
2:20 6.556778 6.971224 0.293826 6.390974 - 7.551473
2:21 6.226537 6.513208 0.288322 5.943828 - 7.082588
3:01 5.476464
3:02 5.129899
3:03 6.016157 5.892951 0.292152 5.316006 - 6.469896
Hope that clarifies the issue.
Brian
______________________________________________________________________________
I tried to run a forecast on the grunfeld example panel dataset
shipped with gretl. I restricted the sample to leave out the last
two time periods, to save them for forecasting, and then estimated
a trivial dynamic/reduced-form fixed-effects regression with
"invest" as the dep. variable. (Let's ignore the Nickell bias
issues for this example.) No contemporaneous variables, but in the
model window under the Analysis menu the "Forecasts..." entry was
still greyed out, so I couldn't cross-check what you described.
So, it would be helpful if you could describe how exactly and
with what data you produced your forecasts.
thanks
sven
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