msl.plot {msltrend} | R Documentation |
Screen plotting options.
Description
Screen plotting options.
Usage
msl.plot(x, type = 1, ci = 1)
Arguments
x |
object of class “msl.trend” (see |
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