grotag_boot {fishboot} | R Documentation |
Bootstrapped tag-and-recapture growth analysis
Description
This function performs bootstrapped fitting of the von Bertalanffy growth
function (VBGF) with estimated growth parameters (L_{inf}
, K
and
t_0
) from tag-and-recapture data, based on the function
grotag, that estimates VBGF parameters according to
Francis (1988). The output is an object containing the parameters
L_{inf}
and K
, as well as the growth performance index
Phi’
(named PhiL
).
This function resamples the input.data
data by rows (i.e.,
by recapture date) several times (nresamp
times, default:
nresamp = 200
). Then, a VBGF curve is fitted to each resampled data set.
The output (a list
of class lfqBoot
) will store results (e.g.,
VGBGF function parameters K and Linf) in a data.frame
accessible
through $bootRaw
. The $bootRaw
table also includes the growth
performance index Phi', seasonal parameters u and w
(sensu Francis, 1988), which are equal to C (sensu Pauly and Gaschütz,
1979) and and ts (sensu Mildenberger et al., 2017). The
$bootRaw
table also includes seed values and system time.
Usage
grotag_boot(
L1 = NULL,
L2 = NULL,
T1 = NULL,
T2 = NULL,
alpha = NULL,
beta = NULL,
design = list(nu = 0, m = 0, p = 0, sea = 0),
stvalue = list(sigma = 0.9, nu = 0.4, m = -1, p = 0.1, u = 0.4, w = 0.4),
upper = list(sigma = 5, nu = 1, m = 2, p = 1, u = 1, w = 1),
lower = list(sigma = 0, nu = 0, m = -2, p = 0, u = 0, w = 0),
gestimate = TRUE,
st.ga = NULL,
st.gb = NULL,
st.galow = NULL,
st.gaup = NULL,
st.gblow = NULL,
st.gbup = NULL,
control = list(maxit = 10000),
input.data = NULL,
seed = NULL,
nresamp = 200,
na_action = c("nothing", "narm", "force"),
time_lim = 5 * 60
)
Arguments
L1 , L2 , T1 , T2 |
Name of the columns to be extracted from |
alpha |
|
beta |
|
design |
Model 1 of Francis is the default settings of 0 for |
stvalue |
Starting values of sigma(s) and depending on the |
upper , lower |
Upper and lower limits of the model parameters' ( |
gestimate |
|
st.ga , st.gb |
If |
st.galow , st.gaup |
If |
st.gblow , st.gbup |
If |
control |
Additional controls passed to the optimization function optim. |
input.data |
A growth increment object of the class |
seed |
seed value for random number reproducibility (if it |
nresamp |
|
na_action |
|
time_lim |
If |
Details
There are 2 ways to specify the main input arguments (related to the size and
timing of the mark-recapture): (1) in the classical way, i.e. by defining
L1
, L2
, T1
and T2
as numeric
vectors as
indicated in the grotag documentation or (2) through a
data.frame
indicated in the input.data
argument. In the latter
case, the arguments L1
, L2
, T1
and T2
must be
1-length character
vectors and they will serve to indicate the column
names of the corresponding variables. If only one value is specified for
input.data
and any of the other arguments is NULL, a default name
equal to the variable name will be assigned (e.g. L1 <- “L1”
).
na_action = "force"
should be used carefully, as it is not always due
to bootstrap data selection factors, but also to an inadequate selection of
the estimation parameters that the NA
values are obtained. Also, the
search time may depend on the size of the input set, if you have many
thousands of individuals or if (in addition) the value of nresamp
is
high, it is possible that the function will take a long time before obtaining
complete results. time_lim
avoids falling into an infinite loop by
limiting the time used by this process to 5 minutes, but this value is
referential and may be insufficient due to the factors mentioned above.
Value
A data.frame
of fitted VBGF parameters (columns) by resampling
(rows). It includes a column (seed
) with seed values set prior to each
resampling call.
References
Efron, B., & Tibshirani, R., 1986. Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy. Statistical Science, 54-75.
Francis, R.I.C.C., 1988. Maximum likelihood estimation of growth and growth variability from tagging data. New Zealand Journal of Marine and Freshwater Research, 22, p.42-51.
Pauly, D., 1981. The relationship between gill surface area and growth performance in fish: a generalization of von Bertalanffy's theory of growth. Meeresforsch. 28:205-211.
Schwamborn, R., Mildenberger, T. K., & Taylor, M. H., 2019. Assessing sources of uncertainty in length-based estimates of body growth in populations of fishes and macroinvertebrates with bootstrapped ELEFAN. Ecological Modelling, 393, 37-51.
Schwamborn, R. & Schwamborn, D. F. M. C. Growth and mortality of the endangered land crab Cardisoma guanhumi assessed through tagging with PITs and novel bootstrapped methods. Pan-American Journal of Aquatic Sciences, 16(1): 57-78.
von Bertalanffy, L., 1938. A quantitative theory of organic growth. Human Biology 10, 181-213.
Examples
# Load example DB from fishmethods package
data(bonito, package = "fishmethods")
## Run the example cited on ?grotag
# fishmethods::grotag(L1 = bonito$L1,
# L2 = bonito$L2,
# T1 = bonito$T1,
# T2 = bonito$T2,
# alpha = 35, beta = 55,
# design = list(nu = 1, m = 1,p = 1, sea = 1),
# stvalue = list(sigma = 0.9, nu = 0.4, m = -1, p = 0.2, u = 0.4, w = 0.4),
# upper = list(sigma = 5, nu = 1, m = 2, p = 0.5, u = 1, w = 1),
# lower = list(sigma = 0, nu = 0, m = -2, p = 0.0, u = 0, w = 0),
# control = list(maxit = 1e4))
# Run the example using grotag_boot
res <- grotag_boot(L1 = bonito$L1,
L2 = bonito$L2,
T1 = bonito$T1,
T2 = bonito$T2,
alpha = 35, beta = 55,
design = list(nu = 1, m = 1,p = 1, sea = 1),
stvalue = list(sigma = 0.9, nu = 0.4, m = -1, p = 0.2, u = 0.4, w = 0.4),
upper = list(sigma = 5, nu = 1, m = 2, p = 0.5, u = 1, w = 1),
lower = list(sigma = 0, nu = 0, m = -2, p = 0.0, u = 0, w = 0),
control = list(maxit = 1e4), seed = 18,
nresamp = 3, na_action = "nothing")
res