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On 10/18/2011 03:38 PM, Laurie wrote:
<blockquote cite="mid:4E9D8146.1090706@gmail.com" type="cite">
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On 10/18/2011 03:07 PM, <a moz-do-not-send="true"
class="moz-txt-link-abbreviated"
href="mailto:ernesto.jardim@jrc.ec.europa.eu">ernesto.jardim@jrc.ec.europa.eu</a>
wrote:
<blockquote cite="mid:4E9D7A13.3020303@jrc.ec.europa.eu"
type="cite">
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On 10/18/2011 02:34 PM, Laurie wrote:
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On 10/18/2011 01:34 PM, <a moz-do-not-send="true"
class="moz-txt-link-abbreviated"
href="mailto:ernesto.jardim@jrc.ec.europa.eu">ernesto.jardim@jrc.ec.europa.eu</a>
wrote:
<blockquote cite="mid:4E9D6431.9030109@jrc.ec.europa.eu"
type="cite">
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On 10/18/2011 01:22 PM, Laurie wrote:
<blockquote cite="mid:4E9D615F.7030402@gmail.com"
type="cite">
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On 10/18/2011 01:10 PM, Ernesto Jardim wrote:
<blockquote
cite="mid:CAC03QWCxARV-RbXfZJNwS8gMLVsgYkRPDrH86LDUkPuyhCmRzg@mail.gmail.com"
type="cite"><br>
<br>
<div class="gmail_quote">On Tue, Oct 18, 2011 at 1:03
PM, Laurie <span dir="ltr"><<a
moz-do-not-send="true"
href="mailto:lauriekell@googlemail.com">lauriekell@googlemail.com</a>></span>
wrote:<br>
<blockquote class="gmail_quote" style="margin: 0pt 0pt
0pt 0.8ex; border-left: 1px solid rgb(204, 204,
204); padding-left: 1ex;">
<div text="#000000" bgcolor="#ffffff">
<div>
<div class="h5"> On 10/18/2011 12:50 PM, <a
moz-do-not-send="true"
href="mailto:ernesto.jardim@jrc.ec.europa.eu"
target="_blank">ernesto.jardim@jrc.ec.europa.eu</a>
wrote:
<blockquote type="cite"> On 10/18/2011 12:02
PM, Laurie wrote:
<blockquote type="cite"> On 10/18/2011 11:41
AM, <a moz-do-not-send="true"
href="mailto:ernesto.jardim@jrc.ec.europa.eu"
target="_blank">ernesto.jardim@jrc.ec.europa.eu</a>
wrote:
<blockquote type="cite">On 10/18/2011
11:26 AM, Laurie wrote: <br>
<blockquote type="cite">I am working on
tagging models, where tags are
released for a number of years and
then recaptured in subsequent years.
This allows M & Z to be estimated
along a cohort. <br>
<br>
The data are in the form of number of
fish tagged and recovered each year of
a cohort. This means that you can´t
use FLCohort which has age &
cohort as dims 1&2. <br>
<br>
However, if you use the 1st dim for
cohort then you can model this with an
FLQuant, i.e. <br>
<br>
library(plyr) <br>
<br>
setGeneric("I",
function(object,...) <br>
standardGeneric("I")) <br>
setGeneric('O',
function(object, ...) <br>
standardGeneric("O")) <br>
<br>
setMethod('I',
signature(object='FLQuant'), <br>
function(object,...){ <br>
dmns <-dimnames(object) <br>
dmns[[1]]
<-ac((dims(object)$minyear-dims(object)$max):(dims(object)$maxyear-
dims(object)$min)) <br>
names(dmns)[1]<-"quant" <br>
flc <-FLQuant(NA,dimnames=dmns)
<br>
<br>
t. <-as.data.frame(object) <br>
t.$cohort <-t.$year-t.$age <br>
flc[]
<-daply(t.,c("cohort","year","unit","season","area","iter"),function(x)
sum(x$data)) <br>
<br>
return(flc)}) <br>
<br>
setMethod('O',
signature(object='FLQuant'), <br>
function(object,...){ <br>
dmns <-dimnames(object) <br>
dmns[[1]]
<-ac((dims(object)$maxyear-dims(object)$max):(dims(object)$minyear-dims(object)$min))<br>
names(dmns)[1]<-"age" <br>
flc <-FLQuant(NA,dimnames=dmns)
<br>
<br>
t. <-as.data.frame(object) <br>
t.$age <-t.$year-t.$quant <br>
t. <-t.[!<a
moz-do-not-send="true"
href="http://is.na" target="_blank">is.na</a>(t.$data),]
<br>
flc[]
<-daply(t.,c("age","year","unit","season","area","iter"),function(x)
sum(x$data)) <br>
<br>
return(flc)}) <br>
<br>
data(ple4) <br>
<br>
m1=I(m(ple4)) <br>
m2=O(m1) <br>
<br>
It is probably best to derive a new
class for this object just to break
VPAs etc. But what to call it? Also
how does it relate to FLCohort. <br>
Laurie <br>
</blockquote>
<br>
You may change the age in FLCohort <br>
<br>
library(FLCore) <br>
data(ple4) <br>
flc <- FLCohort(catch.n(ple4)) <br>
quant(flc) <- "year" <br>
<br>
why not using year in the first
dimension ? it should work out of the
box. <br>
<br>
EJ <br>
<br>
<br>
</blockquote>
But you don´t get what you want.<br>
<br>
<span style="border-collapse: separate;
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<pre style="font-family: Monospace; font-size: 10pt ! important; outline-style: none; border-style: none; white-space: pre-wrap ! important; margin: 0px; line-height: 1.3;"><span style="color: blue;">I(m(ple4))[1:10,1:10]
</span>An object of class "FLQuant"
, , unit = unique, season = all, area = unique
year
quant 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966
1947 0.1 NA NA NA NA NA NA NA NA NA
<a moz-do-not-send="true" href="tel:1948%200.1%20%200.1" value="+35319480101" target="_blank">1948 0.1 0.1</a> NA NA NA NA NA NA NA NA
<a moz-do-not-send="true" href="tel:1949%200.1%20%200.1" value="+35319490101" target="_blank">1949 0.1 0.1</a> 0.1 NA NA NA NA NA NA NA
1950 0.1 0.1 0.1 0.1 NA NA NA NA NA NA
1951 <a moz-do-not-send="true" href="tel:0.1%20%200.1%20%200.1%20%200.1%20%200.1" value="+353101010101" target="_blank">0.1 0.1 0.1 0.1 0.1</a> NA NA NA NA NA
1952 0.1 0.1 0.1 0.1 0.1 0.1 NA NA NA NA
1953 0.1 0.1 0.1 0.1 0.1 0.1 0.1 NA NA NA
1954 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 NA NA
1955 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 NA
1956 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1
units: NA
<span style="white-space: pre-wrap; color: blue;">> </span><span style="color: blue;">FLCohort(m(ple4))[1:10,1:10]
</span>An object of class "FLCohort"
, , unit = unique, season = all, area = unique
cohort
age 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956
1 NA NA NA NA NA NA NA NA NA 0.1
2 NA NA NA NA NA NA NA NA 0.1 0.1
3 NA NA NA NA NA NA NA 0.1 0.1 0.1
4 NA NA NA NA NA NA 0.1 0.1 0.1 0.1
5 NA NA NA NA NA <a moz-do-not-send="true" href="tel:0.1%20%200.1%20%200.1%20%200.1%20%200.1" value="+353101010101" target="_blank">0.1 0.1 0.1 0.1 0.1</a>
6 NA NA NA NA 0.1 <a moz-do-not-send="true" href="tel:0.1%20%200.1%20%200.1%20%200.1%20%200.1" value="+353101010101" target="_blank">0.1 0.1 0.1 0.1 0.1</a>
7 NA NA NA 0.1 0.1 0.1 0.1 0.1 0.1 0.1
8 NA NA 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1
9 NA 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1
laurie</pre>
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</span></span></blockquote>
<br>
Lost me. What do you want ?<br>
<br>
EJ<br>
<br>
<br>
<br>
</blockquote>
</div>
</div>
There are three ways to represent the 1st two dims
in an FLQuant.<br>
<br>
i) age & year<br>
ii) age & cohort<br>
iii) cohort & year<br>
<br>
(i) is FLQuant and (ii) is FLCohort; However we do
not have (iii) which is what I need for my tagging
model.<br>
<br>
I have created an "FLCohortYear" from an FLQuant
by adding I() & O() as coercion methods and
validity that only allows 1st dim to be called
cohort.<br>
But then we have two FLCohort objects which might
conflict. <br>
<font color="#888888"> <br>
Laurie <br>
<br>
<br>
</font></div>
</blockquote>
<div><br>
But you can use FLQuant and change the first
dimension. You may need a method to convert i) or
ii) into it but shouldn't create any conflicts. If
you really need a new data structure and the problem
only affects tag data, call it FLTag and extend
FLQuant.<br>
<br>
Best<br>
EJ<br>
<br>
</div>
</div>
</blockquote>
I would have called in FLCohort but some body got there
1st!<br>
<br>
Having 2 versions of FLCohorts with different properties
does raise an issue though.<br>
<br>
Laurie</blockquote>
<br>
Yes, sure ! But you get what you need computing
year=cohort+age, so I don't see the need for a new one.<br>
<br>
Best<br>
<br>
EJ<br>
</blockquote>
<br>
Same argument applies to FLQuant! However, the maths is easier
in my case using sweep & plyr if dims are year &
cohort<br>
<br>
Laurie<br>
</blockquote>
<br>
Fine, but we're not changing FLCohort so that you may use plyr.
In that case you should create a new class like you're
suggesting and use it.<br>
<br>
Best<br>
<br>
EJ<br>
</blockquote>
<br>
I first looked at FLCohort in order to see if it could be modified
to allow the two cases to be included (i.e. age-cohort &
year-cohort), but found doing the aperms a bit tricky, hence the
daply solution.<br>
<br>
I will create an FLYrCls for now.<br>
<br>
Laurie<br>
</blockquote>
<br>
<br>
Yes, with 6 dimensions aperm can get a bit trick very fast.<br>
<br>
Best<br>
<br>
EJ<br>
<br>
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