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)))