Growth model of the reared sea urchin Paracentrotus ... - SciViews

plot(cumsum(dat[,columns[1]])/sum(dat[,columns[1]])*100, type="s",
col=cols[1],...)
for (i in 1:length(columns-1)) {
lines(cumsum(dat[,columns[i]]/sum(dat[,columns[i]])*100),
type="s", col=cols[i])
}
} else { # Relative==FALSE
plot(cumsum(dat[,columns[1]]), type="s", col=cols[1],...)
for (i in 1:length(columns-1)) {
lines(cumsum(dat[,columns[i]]), type="s", col=cols[i])
}
}
}
###=== Basic functions for envelope model =================================
# Data are stored in an EGMData presentation which is a list containing:
# - x: the time values in day, from birthday (or metamorphosis day) being 0
# time is assumed to be known without error (follow up of animal born
# in captivity and tagged for instance).
# - y: the vector of all classes upper bounds (lower bound of first class is
# always 0, and of course, lower bound of following classes are upper
# bounds of the preceeding classes). Classes limits are: ] x ].
# y is the size increase, and is thus Y - Yini where Y is the measured
# size and Yini is the initial size at birth
# - freq: the table of all frequencies of individuals measured at time t and
# whose y is included in the corresponding class y
# - n: the vector of the number of individuals counted in the batch at each
# sampled time. It only correspond to the number of individuals in freq
# if ALL the batch is measured at each sampled time (if possible!).
# - sizes: (facultative) the table of all measured sizes (or its approximation
# as back-calculated from freq table
# - units: a list with time and size units, ex: c("days", "mm")
# - desc: (facultative) a description of the data set
# - info: (facultative) information about sizes. How it was obtained (measured
# or back-calculated (and with which algorithm), and do the data in a
# row correspond to the same animal (individual tagging) or not.
# An example dataset is a whole batch of reared sea urchins Paracentrotus
# lividus grown in aquaculture, and is presented in Grosjean et al (in prep.)
# The next function create the EGMData corresponding to this dataset
# Usage: Pl