Nothing
VBGF
function with argument na.rm = TRUE
(default is
FALSE
)(L1 - L2) /
(sd1 + sd2)/2
)sqrt(-dL/b
)Z_CPUE
functionscore_mat
in ELEFAN
functionLazyData = false
which implies that data("...")
has to be used to load a
package into the R environment, e.g. data("snyLFQ7")
plots_refs
in plot.predict_mod
function to select which reference
points in the prediction models should be plotted. By default all reference
points are plotted: plot_refs = c("F01","Fmax","F05","F04")
.cols_refs
in plot.predict_mod
function to select the colour for
the reference points in the prediction models. Default colours are cols_refs = c("goldenrod2","darkred","darkgreen","darkorange")
. - Use of matrices was adjusted to comply with new R matrix classes
- ELEFAN_GA was adjusted to use new arguments of the underlying GA::ga
function
- The LBB functionality was removed from the package.
- The Length-based Bayesian biomass estimator method (LBB) by
Froese et al. (2018) has been added to the package.
- Improved implementation of compilation of length-frequency
data allowing for faster compilation of lfq data with
lfqCreate and lfqModify (with argument bin_size) and allowing
compilation of large data sets
- New possibilities to easily modify length-frequency data
objects by means of "lfqModify", including aggregating catch
matrix per year, per quarter, or per month, subsetting lfq
data with range of length classes or sampling dates
- A new vignette "LBBmanual" with the introduction and
demonstration of LBB within TropFishR has been added.
- Seasonal growth parameters are now added correctly to the lfq
object in lfqModify
- A new vignette has been added to the package. The vignette "ELEFANTutorial" outlines
all ELEFAN functions available in TropFishR in detail.
- The ELEFAN functions did not overwrite any element of the lfq object but instead
concatinated parameters onto the object. This can have unintended side effects, e.g. if several
growth parameters are saved in the lfq object and the plotting functions are called.
Now, the application of ELEFAN functions overwrites any growth parameters in the lfq object.
- Due to more efficient matrix computations ELEFAN is 2-4 times faster as before
- missing seed values were added in ELEFAN_GA()
- `plot.lfq()` allows plotting relative frequencies, this is
in particular useful in cases where one sampling time has a large number of samples
- `plot.catchCurve()` allows plotting results according to length rather
than relative age. This can be done with the argument `xaxis`.
- lfq plot can be used to plot 2 different lfq data sets; this allows to visually compare the two data sets
- `lfqModfiy()` allows combining two different lfq data sets. This
might be interesting when different fleets are investigated separately
- possible to define and plot multiple regression lines
in the catch curve analysis
- length converted catch curve can account for the seasonalized VBGF
- better control over graphical devices with par(),
when par() defined the default settings are not used
- growth parameters can now be added to lfq lists as "par" elements, this
is convenient as it is in line with the results of the ELEFAN methods
- new vignette with a short description of lfq data and
how to import lfq data into R
- updated tutorial vignette
- more informative error and warning messages for many functions
- document with news and changes about package version was added
- crash report of ELEFAN_GA with interactive sessions (Rstudio) fixed
and more stable on windows
- plot.catchCurve() was not displaying the regression line, but
a straight line from the first to last point of the chosen interval
- restructering of lfq data was not in line with FiSAT implementation
- fixing bug in handling of leap years
- when merging lfq data with another list using c() one has to reassign
the class "lfq" to the merged object, this has been added in the tutorial
- beep sound was causing R crashes on windows computers and was therefore removed
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.