[FLR-list] Error in a4aout at harvest + m(stock) : non-con

Havstovan FAMRI luridao at gmail.com
Wed Feb 25 14:19:26 CET 2015


thanks Ernesto

best,
Luis


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Luis Ridao Cruz
Faroe Marine Research Institute
Nóatún 1, P.O. Box 3051
FO-110 Tórshavn
Faroe Islands
Tel   : (+298) 353900
Fax: : (+298) 353901
e-mail: luisr at hav.fo
           luridao at gmail.com
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On Wed, Feb 25, 2015 at 12:17 PM, Ernesto <ernesto.jardim at jrc.ec.europa.eu>
wrote:

>  Hi,
>
> You can get the technical document from github
> https://github.com/a4a/tech-doc/blob/master/a4aAssessmentMethodology.pdf?raw=true
> .
>
> Best
>
> EJ
>
>
> On 02/25/2015 12:14 PM, Luis Ridao wrote:
>
> Hi Ernesto,
>
> Thanks for your useful response.
> There was never any intention on replicating the XSA but given the huge
> disparity
> in both the XSA and a4a outputs I was wondering why it was so.
>
> A statistical model sounds more sound than XSA but the problem with a4a is
> that there is no much documentation to see upon (or maybe it's me who can't
> find it)
>
> Your suggestion on including a year trend in the catchability of the trawl
> cpue for example sounds good. The problem is how to implement it.
>
> Thanks again,
> Luis
>
> On 02/24/2015 09:01 AM, Ernesto wrote:
>
> Hi,
>
> Sorry for the late reply.
>
> The problem is that your catch data has a large number of ages that don't
> have tunning data. The default model for a4a was not written for those
> cases. Check
>
> a4afit <- sca(gul0001, gul.indices)
> wireframe(data~year+age, data=harvest(a4afit))
>
> F in the last ages gets loose and the fit is quite poor.
>
> Once that you want to compare with XSA we can take the same kind of
> approach, which is to force the oldest ages Fs the same. In this case the
> model will fit one coefficient (times the year coefficients) for ages older
> than 18, which mean they are fit together, which I think is slightly
> different from XSA. Note that you have a large +group in some years.
>
> This can be done using the "replace" method.
>
> fmod <- ~te(replace(age, age>18, 18), year, k = c(6, 10), bs = "tp")
> a4afit <- sca(gul0001, gul.indices, fmodel=fmod)
>
> For comparison
> xsafit <- FLXSA(gul0001, gul.indices, FLXSA.control())
>
> wireframe(data~year+age|qname,
> data=as.data.frame(FLQuants(a4a=harvest(a4afit), xsa=xsafit at harvest)))
>
> Now, the one million dollars question is why you want to replicate XSA ;)
>
> Best
>
> EJ
>
> ps: Take a look at the residuals and you'll see that both fits have some
> odd residuals. In a4a you have a couple of simple options to improve this
> fit, like including a year trend in the catchability of the trawl cpue, etc.
>
> bubbles(age~year|qname, data=xsafit at index.res)
> plot(residuals(a4afit, gul0001, gul.indices))
>
> On 02/18/2015 02:35 PM, Havstovan FAMRI wrote:
>
>   Hi,
>
>  Well that solved the problem (trimming the indices object
> trim(gul.indices[[2]], age 4:12). No errors come up but stock numbers and
> F's are really spurious
> and nothing in the range of the XSA run. F are given below as a example:
>
>  > gulfit at harvest[,ac(2010:2014)]  # a4a output
> An object of class "FLQuant"
> , , unit = unique, season = all, area = unique
>
>      year
> age  2010       2011       2012       2013       2014
>   4  0.00061883 0.00054841 0.00088312 0.00104010 0.00070947
>   5  0.00194001 0.00170594 0.00221326 0.00254813 0.00223464
>   6  0.00515556 0.00454088 0.00496769 0.00561751 0.00602334
>   7  0.01007180 0.00901793 0.00900872 0.01006750 0.01202780
>   8  0.01384780 0.01273870 0.01257350 0.01389800 0.01666770
>   9  0.01448220 0.01365150 0.01385510 0.01499370 0.01669910
>   10 0.01336920 0.01269240 0.01303890 0.01351880 0.01358130
>   11 0.01248430 0.01165750 0.01145380 0.01107690 0.01019620
>   12 0.01247860 0.01127330 0.00997400 0.00880635 0.00769486
>   13 0.01285800 0.01125750 0.00874288 0.00700203 0.00595635
>   14 0.01248820 0.01082000 0.00757566 0.00557152 0.00460538
>   15 0.01064480 0.00939845 0.00633618 0.00439713 0.00344647
>   16 0.00797521 0.00732193 0.00509501 0.00344610 0.00249670
>   17 0.00569563 0.00541743 0.00403299 0.00273092 0.00182383
>   18 0.00435670 0.00416232 0.00326465 0.00224600 0.00142545
>   19 0.00388555 0.00355594 0.00278197 0.00194974 0.00124088
>   20 0.00406418 0.00340829 0.00250123 0.00177887 0.00119688
>   21 0.00465988 0.00349410 0.00231912 0.00166745 0.00122197
>
>  units:  f
> > gul_F[,ac(2010:2014)]  # XSA output
>      2010   2011   2012   2013   2014
> 4  0.0047 0.0115 0.0015 0.0066 0.0053
> 5  0.0143 0.0311 0.0100 0.0154 0.0296
> 6  0.0675 0.0787 0.0485 0.0655 0.0872
> 7  0.1257 0.1506 0.0947 0.1182 0.1404
> 8  0.1696 0.2211 0.1632 0.1897 0.2082
> 9  0.2107 0.2428 0.1669 0.2651 0.2607
> 10 0.2624 0.3209 0.2170 0.2783 0.2700
> 11 0.2686 0.3086 0.2396 0.3374 0.2840
> 12 0.3309 0.4213 0.2750 0.3371 0.2146
> 13 0.4980 0.6288 0.4110 0.4805 0.2861
> 14 0.4428 0.5557 0.4666 0.5562 0.3298
> 15 0.4462 0.5266 0.4679 0.6606 0.4605
> 16 0.3444 0.4555 0.4277 0.5946 0.4433
> 17 0.2812 0.3540 0.3561 0.5347 0.3910
> 18 0.2529 0.3157 0.3512 0.4841 0.3601
> 19 0.4566 0.2772 0.1803 0.2773 0.3215
> 20 0.2534 0.3124 0.2804 0.4170 0.4099
> 21 0.2534 0.3124 0.2804 0.4170 0.4099
>
>  best,
> Luis
>
>
>
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>
> --
> Ernesto Jardim<ernesto.jardim at jrc.ec.europa.eu> <ernesto.jardim at jrc.ec.europa.eu>
> Fisheries Scientist
> FISHREG – Scientific Support to Fisheries
> IPSC Maritime Affairs Unit
> EC Joint Research Center
> TP 051, Via Enrico Fermi 2749
> I-21027 Ispra (VA), Italy
> Office : +39 0332 785311
> Fax: +39 0332 789658https://fishreg.jrc.ec.europa.eu/
>
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> --
> Ernesto Jardim<ernesto.jardim at jrc.ec.europa.eu> <ernesto.jardim at jrc.ec.europa.eu>
> Fisheries Scientist
> FISHREG – Scientific Support to Fisheries
> IPSC Maritime Affairs Unit
> EC Joint Research Center
> TP 051, Via Enrico Fermi 2749
> I-21027 Ispra (VA), Italy
> Office : +39 0332 785311
> Fax: +39 0332 789658https://fishreg.jrc.ec.europa.eu/
>
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