pred

pred

pred(x, sp = uncor.spec(x), h = 1, p = 5, kernel = "normal", g = 30)

Predicts time series x.

Takes:

x The time series to be predicted, as a vector of observations. Its length t does not have to be a power of two.

sp The uncorrected Haar spectrum of x. To obtain the spectrum, use uncor.spec.

h Prediction lag.

p Number of rows and columns in the Yule-Walker matrix.

kernel The kernel to be used for smoothing the local autocovariance. Like in ksmooth, can be set to "box", "triangle", "parzen" or "normal". Also see help(ksmooth) in S-Plus.

g The value of the bandwidth for kernel smoothing.

Returns:

p The unchanged value of p.

mean The predicted value.

std.err The standard prediction error.

x	The time series to be predicted, as a vector of observations. Its length t does not have to be a power of two.
sp	The uncorrected Haar spectrum of x. To obtain the spectrum, use uncor.spec.
h	Prediction lag.
p	Number of rows and columns in the Yule-Walker matrix.
kernel	The kernel to be used for smoothing the local autocovariance. Like in ksmooth, can be set to "box", "triangle", "parzen" or "normal". Also see help(ksmooth) in S-Plus.
g	The value of the bandwidth for kernel smoothing.

p	The unchanged value of p.
mean	The predicted value.
std.err	The standard prediction error.