Issue with PredictivePosteriorPlot.TSPNDE when bad.u2 is not null #28
Comments
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Thanks Kate...I'll have a look in the next bit but can't guarantee a solution before Xmas...Thanks for delving deep into the code. Carl |
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This was caused by an error in how the discrepancy statistic was computed for the non-diagnonal case. If u2 is missing, then the u2- E[u2 | model parameters] is also missing and so the sum of the statistic over all time periods is also missing. This caused the error as noted. This is now fixed. The diagonal case routines already had the fix done. Carl Schwarz |
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Thanks Kale...I think I've pushed a fix to GitHub, so if you could download
the latest version from GitHub and try it out that would be helpful.
I went through all of the routines and standardized how to deal with bad
data.
n1 and m2. Set to 0. JAGS can now deal properly with a binomial/multinomial
with n=0 and x=0 regardless of the value of the probability.
u2 set to missing. Don't set u2 to 0 because this then is treated as 0
captured which is not correct.
So if you are stratifying by week and for some reason have no releases in
week 2, set n1[2] to 0 and of course m2[2,...] = 0 as well in the data.
If u2 is also missing in week2, set it to missing (not to zero).
In theory, it is possible to have n1 >0 and m2 = missing (e.g. you released
fish but didn't check for marks). I think setting n1=xxx and m2=NA should
also work (don't use the bad.m2 argument). I don't remember how extensively
we have tested this case...
Carl.
…On Mon, Dec 14, 2020 at 5:49 PM Kale Bentley ***@***.***> wrote:
Hi Carl,
I work for the Washington Department of Fish and Wildlife and a group of
us have been using your BTSPAS package (version "2014.0901") for
approximately the past five years.
I recently tried to use the non-diagonal function (
*TimeStratPetersenNonDiagError_fit*) in the most up-to-date version of
BTSPAS (version "2020.9.1") and I am having an issue when I specify maidens
(u2) as NA for any period (i.e., bad.u2 is not null). Specifically, the
JAGS model will run/finish and outputs will start to be generated but
eventually, an error will occur saying "Error in if (sum(temp) > 0 ) [
missing value where TRUE/FALSE needed }.
To debug this issue, I opened the non-diagonal vignette and reproduced the
error with the demo dataset (Conne River 1987 Atlantic Salmon Smolts).
Again, the model runs and produces all output files unless "bad.u2" is not
null. It doesn't matter what u2 period(s) is/are specified as bad (NA) but
I arbitrarily chose jday 135 to reproduce the error/issue.
To isolate the issue, I "loaded" all necessary functions and ran the
*TimeStratPetersenNonDiagError_fit* function line-by-line. It appear that
the issue is occurring in the *PredictivePosteriorPlot.TSPNDE* function
and specifically on line 23 (if(sum(temp)>0){cat(sum(temp), " infinite
discrepancy measures set to NA\n")}). By adding a ", na.rm = TRUE inside
the sum() argument, the error goes away and the plotting function works.
However, this doesn't solve the actual problem. The issue appears to be
with the calculation of "discrep" in the *PredictivePosterior.TSPNDE*
function and specifically NA are generated for "d2.u2.o" and thus also
"d2.o" (which is d2.m2.o + d2.u2.o).
This same issue (model runs but script ultimately fails during the
Predictive Posterior part of the code) if recaptures are specified as NA.
Here the error occurs in the *dmultinom* function on line 82 and/or line
95 of the *PredictivePosterior.TSPNDE* function. I noticed in the updated
version of the model, recaptures are no longer specified as NA if
bad/missing but rather 0 (same with marks -- left at zero instead of
switching to 1). Once I noticed this change in the non-diagonal "fit"
function, I changed my data summarization code so bad/missing recaptures
were left as 0 as opposed to NA and this issue seems to have gone away.
Let me know if there is any other information I can provide. Unless the
issue is fixed (or figure out what I'm doing wrong), we won't be able to
use the updated BTSPAS package as almost every trapping location
experienced outages due to COVID-related shutdowns in the spring of 2020.
I appreciate your help. Take care.
Kale
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Great! Thanks for looking into this issue and fixing it at record speed. I will test out the updated version of the package in the next couple of days and report back any issues. Kale |
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I finally had some time to explore the BTSPAS functions after you made several updates last week. The change you made to the discrepancy statistic calculation for the non-diagonal now allows for missing maiden data (i.e., u2 = NA), which is great. Upon re-running my various juvenile data sets, I came across a couple of other issues that I wanted to bring to your attention:
Thanks again for helping fix the previous issue with "bad" u2 data! I was able to run all of my 2020 abundance estimates using the updated BTSPAS package I downloaded off of GitHub. Happy Holidays! Kale |
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Hi @cschwarz-stat-sfu-ca, |
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Hi Kale. sorry, I've been working 24/7 on a number of contracts that are
due at the end of the Cdn fiscal year (31 March)... I haven't forgotten
about it... Is this a critical issue, i.e. stopping you from proceeding?
Carl.
…On Fri, Jan 29, 2021 at 11:58 AM Kale Bentley ***@***.***> wrote:
Hi @cschwarz-stat-sfu-ca <https://github.com/cschwarz-stat-sfu-ca>,
I wanted to check back in and see if you have had any time to read through
the update I sent you on this issue #25
<#25> back in late
December. If nothing else, I was wondering if you may consider updating how
u2copy is calculated using my suggestion. If it would be helpful, I could
submit a pull request.
Hope you are doing well. Thanks for your time and help.
Kale
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Hi @cschwarz-stat-sfu-ca, |
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Hi @cschwarz-stat-sfu-ca, |
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Hi Kale.. thanks for the nudge...
I think I've patched BTSPAS to fix the problems you identified..
Upon re-running my various juvenile data sets, I came across a couple of
other issues that I wanted to bring to your attention:
1.
As I mentioned before, manually amending individual periods of marks and
recaptures in a dataset as "bad" by setting marks to 1 and recaptures as NA
still seems to cause an issue with the non-diagonal Posterior Predictive
function. This isn't an issue now that I know to leave marks and recaptures
as 0, 0 but figured I'd highlight this nonetheless.
This has been patched. Try the attached script.
1.
The way u2copy is specified, the value can go negative. Interestingly,
and I don't totally understand why, but it appears as though the diagonal
model will run just fine with a negative u2copy value but the non-diagonal
model will not. I ran into this issue with one of my data sets where I was
trying to interpolate missed catch at the end of the run by adding several
periods of NAs for u2 (similar to your vignette here
<https://cran.r-project.org/web/packages/BTSPAS/vignettes/f-Interpolating-run-earlier-and-later.html>).
The error I got said, "Error in node epsilon[XX] Node inconsistent with
parents" and the model would not run. I tried to duplicate the error with
your demo data sets but couldn't. However, I may have figured out a
potential solution to the perhaps rare issue. Your code creates a copy of
u2 using the following code:
- u2copy <- exp(spline(x = 1:length(u2), y = log(u2+1), xout =
1:length(u2))$y)-1
- u2copy <- round(u2copy)
If the spline generates a value less than roughly -0.7, the above code
will result in a u2copy of -1, which again, seems to cause an issue with
the non-diagonal model. I suggest changing the u2copy code to:
- u2copy <- ceiling(exp(spline(x = 1:length(u2), y = log(u2+1), xout =
1:length(u2))$y))-1
This has been patched. I set the v2copy
u2copy <- pmax(0, round(u2copy))
So you should not get negative values of u2copy anymore.
1. The last issue I ran into may be related to the second item listed
above but, unfortunately, I haven't totally figured this one out. In short,
when I go to add "extra" NAs at the end of the run, I sometimes get an
error. For example, in one case, I added five NA u2 periods at the end of
the dataset and the model ran five. I then added a sixth NA u2 period and
the following error:
[image: image]
<https://user-images.githubusercontent.com/40397762/103031927-aa5f4e80-4513-11eb-8828-b0b431303500.png>
This error seems to be occurring somewhere in the "_fit" function after
the runs and all of the plots have been generated. I tried to comb through
the remaining code/functions but couldn't locate the exact location of the
error (I don't see the function "grouped.data" being used). Anyhow, this
isn't a huge deal but again figured I'd mention it if it potentially made
any sense to you.
Sorry, but I was unable to re-create this problem. Do you have sample file
where this happens?
The grouped.data() function is used in the RunTiming routine. I suspect
that some estimates of U are NA which upsets the function, but can't be
sure and can't generate a case where this happens - sorry.
You can access the revised BTSPAS at the GitHub site. The version number is
2021.11.1 (the target date for uploading to CRAN).
I'm making some other (minor) cosmetic changes so will push the BTSPAS to
CRAN later this month.
Please let me know if you run into any other problems.
Thanks for your continuing interest in BTSPAS
…On Tue, Sep 21, 2021 at 3:13 PM Kale Bentley ***@***.***> wrote:
Hi @cschwarz-stat-sfu-ca <https://github.com/cschwarz-stat-sfu-ca>,
I wanted to quickly check in again to see if you may have time to revisit
the follow-up "issue" I submitted on Dec. 23, 2020. Our juvenile monitoring
teams are starting to analyze the data collected this year and it would be
helpful, if nothing else, to update how u2copy is calculated (using my
suggestion) so that the initial values cannot be negative, which leads to
the model not initiating.
Thanks so much.
Kale
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Excellent. I will give the latest version of BTSPAS a try in the very near future. As for the last issue I highlighted re: adding extra NAs to a dataset. In case I wasn't clear, the I am trying to implement is effectively what you showcase in your vignette "Interpolating run early and late". Enough time has passed since I ran into the problem that I don't exactly recall how I was specifying maidens, marks, and recaps in the "fake data". Nonetheless, I'll revisit and respond if I can duplicate the issue. Thank you so much, Carl! Kale |
Hi Carl,
I work for the Washington Department of Fish and Wildlife and a group of us have been using your BTSPAS package (version "2014.0901") for approximately the past five years.
I recently tried to use the non-diagonal function (TimeStratPetersenNonDiagError_fit) in the most up-to-date version of BTSPAS (version "2020.9.1") and I am having an issue when I specify maidens (u2) as NA for any period (i.e., bad.u2 is not null). Specifically, the JAGS model will run/finish and outputs will start to be generated but eventually, an error will occur saying "Error in if (sum(temp) > 0 ) [ missing value where TRUE/FALSE needed }.
To debug this issue, I opened the non-diagonal vignette and reproduced the error with the demo dataset (Conne River 1987 Atlantic Salmon Smolts). Again, the model runs and produces all output files unless "bad.u2" is not null. It doesn't matter what u2 period(s) is/are specified as bad (NA) but I arbitrarily chose jday 135 to reproduce the error/issue.
To isolate the issue, I "loaded" all necessary functions and ran the TimeStratPetersenNonDiagError_fit function line-by-line. It appear that the issue is occurring in the PredictivePosteriorPlot.TSPNDE function and specifically on line 23 (if(sum(temp)>0){cat(sum(temp), " infinite discrepancy measures set to NA\n")}). By adding a ", na.rm = TRUE inside the sum() argument, the error goes away and the plotting function works. However, this doesn't solve the actual problem. The issue appears to be with the calculation of "discrep" in the PredictivePosterior.TSPNDE function and specifically NA are generated for "d2.u2.o" and thus also "d2.o" (which is d2.m2.o + d2.u2.o).
This same issue (model runs but script ultimately fails during the Predictive Posterior part of the code) if recaptures are specified as NA. Here the error occurs in the dmultinom function on line 82 and/or line 95 of the PredictivePosterior.TSPNDE function. I noticed in the updated version of the model, recaptures are no longer specified as NA if bad/missing but rather 0 (same with marks -- left at zero instead of switching to 1). Once I noticed this change in the non-diagonal "fit" function, I changed my data summarization code so bad/missing recaptures were left as 0 as opposed to NA and this issue seems to have gone away.
Let me know if there is any other information I can provide. Unless the issue is fixed (or figure out what I'm doing wrong), we won't be able to use the updated BTSPAS package as almost every trapping location experienced outages due to COVID-related shutdowns in the spring of 2020.
I appreciate your help. Take care.
Kale
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