[FLR-list] Use of FLQuantPoint

[Ernesto Jardim]

Hi,

What's the outcome, iterations or hessian ? Your design seems ok for
hessian.

Best

EJ

On Mon, Oct 10, 2011 at 10:25 AM, Mark Payne <mpa at aqua.dtu.dk> wrote:

> Thanks for the comments and suggestions. I think I'm starting to see a way
> forward. It sounds like the general advice would be to base everything on
> accessor methods, and so long as everything is (somehow) accessible, then
> its fine. However, there are some limitations with, the ability of current
> classes to store  uncertainties that I need to live with (I'm not so excited
> about the idea of developing FLStock_with_uncertainties!), and therefore
> there can't be a one size fits all solution.
>
> How does this sound for a set of methods / solutions?
>
> 1. A set of standard accessor functions, that return simple (error-free)
> FLQuants in the same way as for other classes e.g
> stock.n()
> harvest()
> ssb()
> fbar()
> tsb()
> rec()
>
> 2. Having all the estimated parameters, with uncertainties, readily
> accessible through an FLPar object (?), so that any other object or method
> that wants access to them (e.g. a plot(FLSAM) method) can have at them. I
> will store the estimate and standard deviation only, so that people can go
> further with that if they like...
>
> Mark
>
>
> ________________________________________
> Fra: flr-list-bounces at r-forge.wu-wien.ac.at [
> flr-list-bounces at r-forge.wu-wien.ac.at] P&#229; vegne af Laurie [
> lauriekell at googlemail.com]
> Sendt: 10. oktober 2011 09:07
> Til: flr-list at flr-project.org
> Emne: Re: [FLR-list] Use of FLQuantPoint
>
>  Looking at all the data.frame slots, these currently store value, std and
> up.bnd & low.bnd
>
> library(FLSAM)
> data(NSH.sam)
>
>
> but it appears that a normal distribution is assumed when calculating the
> bnds, and that these are the 95th percentiles. However, depending on
> the application other percentiles might be more appropriate, but you can
> always calculate these if you know the mean & std & assumed distribution.
>
> with(ssb(   NSH.sam), (up.bnd-value)/std)
> with(logssb(NSH.sam), (up.bnd-value)/std)
> with(ssb(   NSH.sam), (value-low.bnd)/std)
> with(logssb(NSH.sam), (value-low.bnd)/std)
>
> So returning the bounds is not necessary and the bounds being returned
> might not be the correct ones. Therefore it would be better to just return
> the mean & std and
> have a method to calculate any required statistic. There is also redundancy
> as you return logssb as well as ssb (same for tsb & fbar etc).
>
> Also FLQuantPoint was designed to summarise emprical distributions, but ssb
> etc come from an assumed distribution.
>
> Also if you know wt, mat stock.n & harvest then you know ssb fbar etc. So
> agian there is redundancy.
>
> How does fbar relate to harvest, presumably each F has a std & variance and
> fbar is function of these.
>
> Laurie
>
>
>
> On 10/08/2011 01:55 PM, Mark Payne wrote:
>
> Ok, that makes sense, but I'm still a little unsure about how this should
> be implemented - as I understand it you're talking mainly about how to store
> the data, rather than pass it around. I currently have an array of accessor
> functions:
>
> ssb(sam.object)
> tsb(sam.object)
> fbar(sam.object)
> stock.n(sam.object)
> harvest(sam.object)
> rec(sam.object)
>
> What sort of objects should these return, given that these quantites now
> can all have confidence intervals associated with them?
>
> Mark
>
> ________________________________________
> Fra: flr-list-bounces at r-forge.wu-wien.ac.at<mailto:
> flr-list-bounces at r-forge.wu-wien.ac.at> [
> flr-list-bounces at r-forge.wu-wien.ac.at<mailto:
> flr-list-bounces at r-forge.wu-wien.ac.at>] P&#229; vegne af Laurie [
> lauriekell at googlemail.com<mailto:lauriekell at googlemail.com>]
> Sendt: 8. oktober 2011 12:18
> Til: flr-list at flr-project.org<mailto:flr-list at flr-project.org>
> Emne: Re: [FLR-list] Use of FLQuantPoint
>
> On 10/08/2011 11:47 AM, Mark Payne wrote:
>
>
> Hi,
>
> I am a bit confused about the intended use of FLQuantPoints. The FLSAM
> assessment model returns the confidence intervals for nearly everything that
> it calculates, including, for example, the ssb. I am trying to write an
> accessor function that will return the ssb as an FLQuantPoint object. The
> problem is that the confidence intervals for this value are asymmetric, so
> it's not sufficient just to return the mean and the variance. I was
> wondering what the intention for the uppq and lowq dimension was? Is this
> the appropriate place to store the estimated confidence bounds? Or are they
> solely for cases where you have a large distribution that you are trying to
> characteriste non-parametrically ie through median and the quartiles...
>
> Second question - is there a plural class, FLQuantPoints? I can't seem to
> find one at the moment....
>
> Mark
>
>
>
> You say ssb has an asymmetric distribution but that only matters  if it
> is from an empirical distribution, e.g. derived from an MC simulation.
> When I had a quick look at ssb, the upper & lower CIs were just +-1.96
> times the CV. I.e. if you know the distribution and parameters you can
> derive the CIs.
> Also for what percentiles do you want the CIs? this will vary on a
> case-by-case basis.
>
> FLQuantPoint was designed to summarise the 6th dim (iter) to reduce
> storage space. If you are not running MC simulations then there is no
> need for FLQuantPoint.
>
> Instead if you return the parameters and hessian as FLPar objects then
> you can design methods to calculate quantities of interest.
>
> Laurie
>
>
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