This creates a time-series of predicted tides, based on a
tidal model object that was created by as.tidem()
or tidem()
.
# S3 method for tidem
predict(object, newdata, ...)
a tidem object.
vector of POSIXt times at which to make the
prediction. For models created with tidem()
,
the newdata
argument is optional, and if it is not provided, then
the predictions are at the observation times given to
tidem()
. However, newdata
is required if as.tidem()
had been used to create object
.
optional arguments passed on to children.
A vector of predictions.
All the tidal constituents that are stored in object
are used,
not just those that are statistically significant or that have amplitude
exceeding any particular value. In this respect, predict.tidem()
follows a pattern established by e.g. predict.lm()
. Note that
the constituents in object
are straightforward if it
was constructed with as.tidem()
, but considerably more complicated
for tidem()
, and so the documentation for the latter ought to
be studied closely, especially with regard to the Rayleigh criterion.
# prediction at specified times
data(sealevel)
m <- tidem(sealevel)
# Check fit over 2 days (interpolating to finer timescale)
look <- 1:48
time <- sealevel[["time"]]
elevation <- sealevel[["elevation"]]
oce.plot.ts(time[look], elevation[look])
# 360s = 10 minute timescale
t <- seq(from=time[1], to=time[max(look)], by=360)
lines(t, predict(m, newdata=t), col="red")
legend("topright", col=c("black","red"),
legend=c("data","model"),lwd=1)
Other things related to tides:
[[,tidem-method
,
[[<-,tidem-method
,
as.tidem()
,
plot,tidem-method
,
summary,tidem-method
,
tidalCurrent
,
tidedata
,
tidem
,
tidem-class
,
tidemAstron()
,
tidemVuf()
,
webtide()
# Show non-tidal sealevel signal in Halifax Harbour during
# the year 2002. The spike resulted from Hurricane Juan.
library(oce)
data(sealevel)
time <- sealevel[["time"]]
elevation <- sealevel[["elevation"]]
prediction <- tidem(sealevel) |> predict()
#> Note: the tidal record is too short to fit for constituents: SA, PI1, S1, PSI1, GAM2, H1, H2, T2, R2
oce.plot.ts(time, elevation - prediction)