features {qualV} | R Documentation |
Qualitative Features of Time Series
Description
A time series is characterised by a sequence of characters,
indicating features of the time series itself, of its first or second
derivative, steepness or level of values.
Usage
f.slope(x, y, f = 0.1, scale = c("mean", "range", "IQR", "sd", "none"))
f.curve(x, y, f = 0.1, scale = c("mean", "range", "IQR", "sd", "none"))
f.steep(x, y, f1 = 1, f2 = 0.1)
f.level(y, high = 0.8, low = 0.2)
Arguments
x |
vector of time |
y |
input y values |
f |
factor defining the limit for constant (f.slope ) or linear
(f.curve ) sequences |
f1 |
factor for the upper bound of steepness |
f2 |
factor for the lower bound of steepness |
scale |
method for internal scaling, f is multiplied with mean
value, range, interquartile range (IQR) or standard deviation of increments
(abs(delta y / delta x)). |
high |
lower limit of high values |
low |
upper limit of low values |
Details
For the first derivative the segment between two values is
characterised by increasing ('A'), decreasing ('B') or constant ('C') and for
the second by convex ('K'), concave ('I') or linear ('J'). For the property of
the first derivative the segment between two values is characterised
by very steep ('S'), steep ('T') or not steep ('U') or the values are divided
into high ('H'), low ('L') or values in between ('M'). Note that for
the last two cases the original values and the not increments are
standardised (to [0, 1]).
Value
See Also
LCS
, qvalLCS
Examples
data(phyto)
bbobs <- dpill(obs$t, obs$y)
n <- tail(obs$t, n = 1) - obs$t[1] + 1
obsdpill <- ksmooth(obs$t, obs$y, kernel = "normal", bandwidth = bbobs,
n.points = n)
obss <- data.frame(t = obsdpill$x, y = obsdpill$y)
obss <- obss[match(sim$t, obss$t), ]
f.slope(obss$t, obss$y)
f.curve(obss$t, obss$y)
f.steep(obss$t, obss$y, f1 = 30, f2 = 10)
f.level(obss$y)
[Package
qualV version 0.2-4
Index]