alkIndivAge | R Documentation |
Use either the semi- or completely-random methods from Isermann and Knight (2005) to assign ages to individual fish in the unaged sample according to the information in an age-length key supplied by the user.
alkIndivAge(
key,
formula,
data,
type = c("SR", "CR"),
breaks = NULL,
seed = NULL
)
key |
A numeric matrix that contains the age-length key. The format of this matrix is important. See details. |
formula |
A formula of the form |
data |
A data.frame that minimally contains the length measurements and possibly contains a variable that will receive the age assignments as given in |
type |
A string that indicates whether to use the semi-random ( |
breaks |
A numeric vector of lower values that define the length intervals. See details. |
seed |
A single numeric that is given to |
The age-length key in key
must have length intervals as rows and ages as columns. The row names of key
(i.e., rownames(key)
) must contain the minimum values of each length interval (e.g., if an interval is 100-109, then the corresponding row name must be 100). The column names of key
(i.e., colnames(key)
) must contain the age values (e.g., the columns can NOT be named with “age.1”, for example).
The length intervals in the rows of key
must contain all of the length intervals present in the unaged sample to which the age-length key is to be applied (i.e., sent in the length
portion of the formula
). If this constraint is not met, then the function will stop with an error message.
If breaks=NULL
, then the length intervals for the unaged sample will be determined with a starting interval at the minimum value of the row names in key
and a width of the length intervals as determined by the minimum difference in adjacent row names of key
. If length intervals of differing widths were used when constructing key
, then those breaks should be supplied to breaks=
. Use of breaks=
may be useful when “uneven” length interval widths were used because the lengths in the unaged sample are not fully represented in the aged sample. See the examples.
Assigned ages will be stored in the column identified on the left-hand-side of formula
(if the formula has both a left- and right-hand-side). If this variable is missing in formula
, then the new column will be labeled with age
.
The original data.frame in data
with assigned ages added to the column supplied in formula
or in an additional column labeled as age
. See details.
The type="SR"
method worked perfectly on a small example. The type="SR"
method provides results that reasonably approximate the results from alkAgeDist
and alkMeanVar
, which suggests that the age assessments are reasonable.
5-Age-Length Key.
Derek H. Ogle, DerekOgle51@gmail.com. This is largely an R version of the SAS code provided by Isermann and Knight (2005).
Ogle, D.H. 2016. Introductory Fisheries Analyses with R. Chapman & Hall/CRC, Boca Raton, FL.
Isermann, D.A. and C.T. Knight. 2005. A computer program for age-length keys incorporating age assignment to individual fish. North American Journal of Fisheries Management, 25:1153-1160. [Was (is?) from http://www.tandfonline.com/doi/abs/10.1577/M04-130.1.]
See alkAgeDist
and alkMeanVar
for alternative methods to derived age distributions and mean (and SD) values for each age. See alkPlot
for methods to visualize age-length keys.
## First Example -- Even breaks for length categories
WR1 <- WR79
# add length categories (width=5)
WR1$LCat <- lencat(WR1$len,w=5)
# isolate aged and unaged samples
WR1.age <- subset(WR1, !is.na(age))
WR1.len <- subset(WR1, is.na(age))
# note no ages in unaged sample
head(WR1.len)
# create age-length key
raw <- xtabs(~LCat+age,data=WR1.age)
( WR1.key <- prop.table(raw, margin=1) )
# apply the age-length key
WR1.len <- alkIndivAge(WR1.key,age~len,data=WR1.len)
# now there are ages
head(WR1.len)
# combine orig age & new ages
WR1.comb <- rbind(WR1.age, WR1.len)
# mean length-at-age
Summarize(len~age,data=WR1.comb,digits=2)
# age frequency distribution
( af <- xtabs(~age,data=WR1.comb) )
# proportional age distribution
( ap <- prop.table(af) )
## Second Example -- length sample does not have an age variable
WR2 <- WR79
# isolate age and unaged samples
WR2.age <- subset(WR2, !is.na(age))
WR2.len <- subset(WR2, is.na(age))
# remove age variable (for demo only)
WR2.len <- WR2.len[,-3]
# add length categories to aged sample
WR2.age$LCat <- lencat(WR2.age$len,w=5)
# create age-length key
raw <- xtabs(~LCat+age,data=WR2.age)
( WR2.key <- prop.table(raw, margin=1) )
# apply the age-length key
WR2.len <- alkIndivAge(WR2.key,~len,data=WR2.len)
# add length cat to length sample
WR2.len$LCat <- lencat(WR2.len$len,w=5)
head(WR2.len)
# combine orig age & new ages
WR2.comb <- rbind(WR2.age, WR2.len)
Summarize(len~age,data=WR2.comb,digits=2)
## Third Example -- Uneven breaks for length categories
WR3 <- WR79
# set up uneven breaks
brks <- c(seq(35,100,5),110,130)
WR3$LCat <- lencat(WR3$len,breaks=brks)
WR3.age <- subset(WR3, !is.na(age))
WR3.len <- subset(WR3, is.na(age))
head(WR3.len)
raw <- xtabs(~LCat+age,data=WR3.age)
( WR3.key <- prop.table(raw, margin=1) )
WR3.len <- alkIndivAge(WR3.key,age~len,data=WR3.len,breaks=brks)
head(WR3.len)
WR3.comb <- rbind(WR3.age, WR3.len)
Summarize(len~age,data=WR3.comb,digits=2)
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