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<span class="Apple-style-span" style="border-collapse: separate;
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font-size: medium;"><span class="Apple-style-span"
style="font-family: Monospace; font-size: 13px; line-height:
17px; text-indent: -28px;">Looking at all the data.frame slots,
these currently store value, std and up.bnd & low.bnd<br>
<br>
library(FLSAM)<br>
data(NSH.sam)<br>
<br>
</span></span><br>
but it appears that a normal distribution is assumed when
calculating the bnds, and that these are the 95th percentiles.
However, depending on<br>
the application other percentiles might be more appropriate, but you
can always calculate these if you know the mean & std &
assumed distribution.<br>
<br>
<span class="Apple-style-span" style="border-collapse: separate;
color: rgb(0, 0, 0); font-family: Arial; font-style: normal;
font-variant: normal; font-weight: normal; letter-spacing: normal;
line-height: normal; orphans: 2; text-indent: 0px; text-transform:
none; white-space: normal; widows: 2; word-spacing: 0px;
font-size: medium;"><span class="Apple-style-span"
style="font-family: Monospace; font-size: 13px; line-height:
17px; text-indent: -28px;">with(ssb( NSH.sam),
(up.bnd-value)/std)<br>
</span></span><span class="Apple-style-span"
style="border-collapse: separate; color: rgb(0, 0, 0);
font-family: Arial; font-style: normal; font-variant: normal;
font-weight: normal; letter-spacing: normal; line-height: normal;
orphans: 2; text-indent: 0px; text-transform: none; white-space:
normal; widows: 2; word-spacing: 0px; font-size: medium;"><span
class="Apple-style-span" style="font-family: Monospace;
font-size: 13px; line-height: 17px; text-indent: -28px;">with(logssb(NSH.sam),
(up.bnd-value)/std)<br>
</span></span><span class="Apple-style-span"
style="border-collapse: separate; color: rgb(0, 0, 0);
font-family: Arial; font-style: normal; font-variant: normal;
font-weight: normal; letter-spacing: normal; line-height: normal;
orphans: 2; text-indent: 0px; text-transform: none; white-space:
normal; widows: 2; word-spacing: 0px; font-size: medium;"><span
class="Apple-style-span" style="font-family: Monospace;
font-size: 13px; line-height: 17px; text-indent: -28px;">with(ssb(
NSH.sam), (value-low.bnd)/std)<br>
</span></span><span class="Apple-style-span"
style="border-collapse: separate; color: rgb(0, 0, 0);
font-family: Arial; font-style: normal; font-variant: normal;
font-weight: normal; letter-spacing: normal; line-height: normal;
orphans: 2; text-indent: 0px; text-transform: none; white-space:
normal; widows: 2; word-spacing: 0px; font-size: medium;"><span
class="Apple-style-span" style="font-family: Monospace;
font-size: 13px; line-height: 17px; text-indent: -28px;">with(logssb(NSH.sam),
(value-low.bnd)/std) <br>
</span></span><br>
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<br>
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).<br>
<br>
Also FLQuantPoint was designed to summarise emprical distributions,
but ssb etc come from an assumed distribution.<br>
<br>
Also if you know wt, mat stock.n & harvest then you know ssb
fbar etc. So agian there is redundancy. <br>
<br>
How does fbar relate to harvest, presumably each F has a std &
variance and fbar is function of these.<br>
<br>
Laurie <br>
<br>
<br>
<br>
On 10/08/2011 01:55 PM, Mark Payne wrote:
<blockquote
cite="mid:AAD1945C8FDCF0488D845356BF31DB72065CF4CF@WINEXCHANGE5.win.dtu.dk"
type="cite">
<pre wrap="">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: <a class="moz-txt-link-abbreviated" href="mailto:flr-list-bounces@r-forge.wu-wien.ac.at">flr-list-bounces@r-forge.wu-wien.ac.at</a> [<a class="moz-txt-link-abbreviated" href="mailto:flr-list-bounces@r-forge.wu-wien.ac.at">flr-list-bounces@r-forge.wu-wien.ac.at</a>] P&#229; vegne af Laurie [<a class="moz-txt-link-abbreviated" href="mailto:lauriekell@googlemail.com">lauriekell@googlemail.com</a>]
Sendt: 8. oktober 2011 12:18
Til: <a class="moz-txt-link-abbreviated" href="mailto:flr-list@flr-project.org">flr-list@flr-project.org</a>
Emne: Re: [FLR-list] Use of FLQuantPoint
On 10/08/2011 11:47 AM, Mark Payne wrote:
</pre>
<blockquote type="cite">
<pre wrap="">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
</pre>
</blockquote>
<pre wrap="">
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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