lfo.test {RTisean} | R Documentation |
Estimates the average one step prediction error of for a local linear ansatz fit.
lfo.test(series, l, x = 0, c=1, m = c(1,2), d = 1, n, k = 30, r, f = 1.2, s = 1, C)
series |
a vector or a matrix. |
l |
number of data to use. |
x |
number of lines to be ignored. |
c |
column to be read. |
m |
embedding dimension. |
d |
delay for the embedding. |
n |
number of points for which the error should be calculated. |
k |
minimal numbers of neighbors for the fit. |
r |
neighborhood size to start with. |
f |
factor to increase the neighborhood size if not enough neighbors were found. |
s |
steps to be forecasted. |
C |
width of causality window. |
A scalar corresponding to the relative forecast error, namely the forecast error devided by the standard deviation of the data.
## Not run: library(tseriesChaos) dat <- rossler.ts errors <- NULL for(i in 1:100) errors[i] <- lfo.test(dat,s=i) plot(errors,t="l",xlab="Forecasted steps", ylab="Relative error",main="Relative forecast error for a local linear fit") ## End(Not run)