quant: q<sup>th</sup> percentile of LFD (Length Frequency... In MEDITS: Analysis of MEDITS-Like Survey Data

Description

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

Usage

 1 quant(freq, quantile)

Arguments

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

Details

Length at the qth 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 fqj,l is the number of individuals in the length class l from the haul j standardised to the km2, and Aj is the surface trawled in the haul j. The length at the qth percentile (Lq) is computed as: Where l is the length class corresponding to the qth percentile (0 < q < 1) for the species i, and yl,i is the value of the catch for the length class l. The variance of the length at the 95th percentile is computed as: Value

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

Walter Zupa

Examples

 1 2 3 4 5 6 7 8 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)

MEDITS documentation built on Dec. 23, 2019, 1:06 a.m.