percentile of LFD (Length Frequency...
In MEDITS: Analysis of MEDITS-Like Survey Data

Description Usage Arguments Details Value Author(s) Examples

The quant function estimates the length class corresponding to the selected percentile of the annual length frequency distribution (LFD) of a time series.

1	quant(freq, quantile)

`freq`	data frame of the time series of the LFD, as estimated by `LFD` function
`quantile`	percentile value

Length at the q^th percentile (Lq)
The different percentiles of a length frequency distribution (LFD) are expected to respond differently to fishing, recruitment pulses, and loss of spawning stock. It is computed from the standardised LFD that is:

where fq_j,l is the number of individuals in the length class l from the haul j standardised to the km², and A_j is the surface trawled in the haul j. The length at the q^th percentile (Lq) is computed as:

Where l is the length class corresponding to the q^th percentile (0 < q < 1) for the species i, and y_l,i is the value of the catch for the length class l. The variance of the length at the 95^th percentile is computed as:

The function returns a data frame containing the time series of the selected percentiles and the relative variance values.

Walter Zupa

library(MEDITS)
merge_TATB <-  m.TATB(TA,TB,"ARISFOL")
merge_TATC <-  m.TATC(TA,TC,"ARISFOL")
GSA <- unique(TA$AREA)
indices <- index.ts(merge_TATB,GSA,"ARISFOL",index = "abundance",
depth_range=c(500,800), sampling = "RSS",plot=FALSE)
freq <- LFD(merge_TATC,indices,sex="m",LC=1,depth_range=c(500,800))
quant(freq,0.95)