kernel(coef, m, r, name) df.kernel(k) bandwidth.kernel(k) is.tskernel(k) print(k, digits = max(3,.Options$digits-3)) plot(k)
coef
|
the upper half of the smoothing kernel coefficients
(inclusive of coefficient zero) or the name of a kernel
(currently "daniell", "dirichlet", "fejer" or
"modified.daniell".
|
m
|
the kernel dimension. The number of kernel coefficients is
2*m+1.
|
name
| the name of the kernel. |
r
| the kernel order for a Fejer kernel. |
digits
| the number of digits to format real numbers. |
"tskernel" class is designed to represent discrete symmetric
normalized smoothing kernels. These kernels can be used to smooth
vectors, matrices, or time series objects.kernel is used to construct a general kernel or
named specific kernels. The modified Daniell kernel
halves the end coefficients (as used by S-PLUS).
df.kernel returns the "equivalent degrees of freedom" of a
smoothing kernel as defined in Brockwell and Davies (1991), p. 362,
and bandwidth.kernel returns the equivalent bandwidth as
defined in Bloomfield (1991), p. 201, with a continuity correction.
kernel returns a list with class "tskernel", and
components the coefficients
coef and the kernel dimension m. An additional
attribute is "name".Brockwell, P.J. and Davis, R.A. (1991) Time Series: Theory and Methods. Second edition. Springer, pp. 350-365.
kernapply
data(EuStockMarkets) # Demonstrate a simple trading strategy for the
x <- EuStockMarkets[,1] # financial time series German stock index DAX.
k1 <- kernel("daniell", 50) # a long moving average
k2 <- kernel("daniell", 10) # and a short one
plot(k1)
plot(k2)
x1 <- kernapply(x, k1)
x2 <- kernapply(x, k2)
plot(x)
lines(x1, col = "red") # go long if the short crosses the long upwards
lines(x2, col = "green") # and go short otherwise
data(sunspot) # Reproduce example 10.4.3 from Brockwell and Davies (1991)
spectrum(sunspot.year, kernel=kernel("daniell", c(11,7,3)))