Description Usage Arguments Details Value References Examples
Find relative frequencies and frequency distribution of distinct cohorts in the observed length frequency distribution by resolving it into Gaussian components.
1  Bhattacharya(param, n_rnorm = 1000, savePlots = FALSE)

param 
a list consisting of following parameters:

n_rnorm 
number of observations for the function 
savePlots 
logical; indicating whether the analyis graphs should be recorded 
This method includes the identify
function, which allows to
choose points on a graphical device manually. To stop this process please press
right mouse click on the graph, and in case you are working on a windows
maschine click on "Stop". An error will be caused if the graphical device
is closed manually. After you have selected the points for regression analysis
you will be asked if you want to redo the selection or if you want to continue.
Please enter in the Console "y" for continuation if you are satisfied
with your selection and the corresponding Gaussian distribution or enter
"redo" if you want to repeat the selection procedure. This function
allows a maximum of 12 cohorts or seperate distributions in one sample. Please
find more details in the Vignette of this package or in the FAO manual by
Sparre and Venema (1998) (Section 3.4.1, p. 80).
A list with the input parameters and
regressionLines dataframe with intercept, slope, start and end points of the regression lines,
Lmean_SD_list dataframe with the mean length (Lmean), standard deviation (SD), and seperation index (SI) for each cohort,
bhat_results dataframe with the results of the Bhattacharya method,
distributions list with the x and y values of selected distributions,
cohort_plots list with analysis plots (when savePlots = TRUE).
Bhattacharya, C.G., 1967. A simple method of resolution of a distribution into Gaussian components, Biometrics, 23:115135
Sparre, P., Venema, S.C., 1998. Introduction to tropical fish stock assessment. Part 1. Manual. FAO Fisheries Technical Paper, (306.1, Rev. 2). 407 p.
1 2 3 4 5 6 7 8 9  # The following example requires to choose certain values for the regression analyses:
# first cohort: point 2 to 8
# second cohort: point 12 to 17
# third cohort: point 19 to 23
# fourth cohort: point 26 to 30
data(synLFQ1)
Bhattacharya(param = synLFQ1)

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