msl.plot: Screen plotting options.

In msltrend: Improved Techniques to Estimate Trend, Velocity and Acceleration from Sea Level Records

Description

Screen plotting options.

Usage

msl.plot(x, type = 1, ci = 1)

Arguments

x	object of class “msl.trend” (see msl.trend and s) or “msl.forecast” (see msl.forecast and t).
type	numeric, enables a user defined input to select the type of chart to be plotted. The default setting (type = 1) provides 3 charts in the same plot area with the time series in the top panel, instantaneous velocity in the middle panel and instantaneous acceleration in the bottom panel. The alternatives (2, 3 and 4) are single panel plots of time series, instantaneous velocity and instantaneous acceleration, respectively.
ci	numeric, enables a user defined input to select the type of confidence interval to be displayed on the plots. The default setting (ci = 1) corresponds to a 95% confidence interval whilst ci=2 provides a 99% confidence interval.

Details

This routine provides a range of screen plotting options for both “msl.trend” (see msl.trend) and “msl.forecast” (see msl.forecast) objects. The same range of alternative pdf plotting options are available via msl.pdf.

See Also

msl.trend, msl.forecast, msl.pdf, Balt, s, t

Examples

# -------------------------------------------------------------------------
# Isolate trend from Baltimore record, filling gaps with spline interpolation,
# 500 iterations and adding 1000 mm of slr to 2100. Use raw 'Balt.csv' data file.
# Note: ordinarily user would call 'File.csv' direct from working directory
# using the following sample code:
# s <- msl.trend('Balt.csv', fillgaps = 3, iter = 500, 'BALTIMORE, USA')
# t <- msl.forecast(s, slr = 1000)
# -------------------------------------------------------------------------

data(s) # msl.trend object from above-mentioned example
data(t) # msl.forecast object from above-mentioned example
msl.plot(s) # default screen plot output, 3 panels, 95% confidence intervals
msl.plot(s, type = 2) # plot time series, 95% confidence intervals
msl.plot(s, type = 3) # plot instantaneous velocity, 95% confidence intervals
msl.plot(s, type = 4, ci = 2) # plot acceleration, 99% confidence intervals
msl.plot(t) # default screen plot output, 3 panels, 95% confidence intervals
msl.plot(t, type = 2) # plot time series, 95% confidence intervals
msl.plot(t, type = 3) # plot instantaneous velocity, 95% confidence intervals
msl.plot(t, type = 4, ci = 2) # plot acceleration, 99% confidence intervals

msltrend documentation built on May 2, 2019, 5:41 a.m.