metaCDW: Extract Cardinal Dates of Multiple Time Series at Once Using Fitted Weibull Curves

Description

metaCDW determines the relevant peak of several time series and fits four- resp. six-parametric Weibull curves to these peaks of all series at once and extracts ``cardinal dates'' from the fitted curves.

Usage

metaCDW(dat, method = "weibull6", xstart = 55, xmin = 0, xmax = 365, 
        minpeak = 0.1, mincut = 0.382,
        quantile = 0.05, symmetric = FALSE, p0 = NULL, linint = -1, 
        findpeak = TRUE, maxit = 2000)
# S3 method for cardiMetacdw
summary(object, file="", ...)

Value

A list with components:

metares: data frame with cardinal dates and fitted parameters, see CDW for details,
weibullfits: list of fit details for all fits, see fitweibull for details.

Arguments

dat: a data.frame containig the columns: sample (description of the timeseries such as year, water body, or any other code (should be numeric or factor), x (the independend variable, e.g. Julian day of the year), y (the dependend variable, e.g. phytoplankton biovolume) and an optional column flag (of type boolean indicating whether a data point should be included in analysis),
method: either "weibull6" or "weibull4",
xstart: offset (day of year) for the "spring" peak; either a single numeric value for all years or a vector of the same length as number of samples,
xmin: left boundary (in day of year) of the integral under the curve,
xmax: right boundary (in day of year) of the integral under the curve,
quantile: two-sided quantile (percentage of integral) which defines beginning and end of the peak,
minpeak: minimum value of the total maximum which is regarded as peak (default value is derived from golden section),
mincut: minimum relative height of a pit compared to the lower of the two neighbouring maxima at which these maxima are regarded as separate peaks.
symmetric: if (TRUE), quantiles are calculated for the whole area under the curve, otherwise for each of the branches separately.
p0: initial parameters for optimization. In case of p0 = NULL a heuristic algorithm to derive initial values is used for fitweibull6,
linint: control parameter to select interpolation behavior. Negative values (default) specify automatic selection heuristic, zero disables interpolation. A positive value is interpreted as mandatory interpolation time step.
maxit: maximum number of iterations passed to the optimisation functions,
findpeak: a logical value indicating whether the relevant peaks of the time series should be identified automatically with peakwindow before the computation proceeds,
object: a result from a call to metaCDW,
file: file name where the data are to be written to, defaults to screen,
...: other parameters of summary passed to write.

Details

This is a top-level function which calls peakwindow, fitweibull and CDW for a series of data sets and returns a table (data frame) of all results.

Examples

Run this code


## open test data set (3 years) with 4 columns
## sample, x, y, flag
data(carditest)
dat <- carditest

## alternatively: import data from spreadsheet via the clipboard
# dat <- read.table("clipboard", sep = "\t", header = TRUE)

## or, for languages with comma as decimal separator:
# dat <- read.table("clipboard", sep = "\t", header = TRUE, dec = ",")

## Note: as.numeric recodes factor year to numeric value
plot(as.numeric(dat$sample)*365 + dat$x, dat$y, type = "b")

## do the analysis
tt <- metaCDW(dat, xstart = 55)

## plot results
par(mfrow=c(1, 3))
lapply(tt$weibullfits, plot)

## return table of results
summary(tt)

if (FALSE) {
## copy to clipboard in spreadsheet compatible format
summary(tt, file = "clipboard", sep = "\t", quote = FALSE, row.names = FALSE)

## or, for languages with comma as decimal separator:
#summary(tt, file = "clipboard", sep = "\t", dec = ",",
#  quote = FALSE, row.names = FALSE)
}