Description Usage Arguments Details Value Author(s) References See Also Examples
This function realizes the ACM filter with a S-Plus type signature.
1 |
x |
univarite time series (vector) |
gm |
list as produced by function |
s0 |
scale of nominal Gaussian component of additive noise |
psi |
influence function to be used (default: Hampel's ψ function, which is the only one available at the moment) |
a,b,c |
tuning constants for Hampel's ψ-function |
flag |
character, if "weights", use ψ(t)/t to calculate the weights; if "deriv", use ψ'(t) |
lagsmo |
logical, if |
to be filled
a list with elements
filt.ck |
the classical Kalman filter |
filt |
the ACM filter |
st |
time-dependent scale parameter estimate |
r |
AR-residuals |
Bernhard Spangl bernhard.spangl@boku.ac.at,
Martin, R.D. and Zeh, J.E. (1978): Generalized M-estimates for Autoregression Including Small-sample Efficiency Robustness
Martin, R.D. (1980): Robust Estimation of Autoregressive Models.
Martin, R.D. and Thomson, D.J. (1982): Robust-resistent Spectrum Estimation.
Stockinger, N. and Dutter, R. (1987): Robust Time Series Analysis: A Survey.
internalarGM
, internalpsi
, internalACM
,
arGM
, recFilter
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | require(robKalman)
## AO model:
set.seed(361)
Eps <- as.ts(rnorm(100))
ar2 <- arima.sim(list(ar = c(1, -0.9)), 100, innov = Eps)
Binom <- rbinom(100, 1, 0.1)
Noise <- rnorm(100,sd = 10)
y <- ar2 + as.ts(Binom*Noise)
y.arGM <- arGM(y, 3)
y.ACMfilt <- ACMfilt(y, y.arGM)
plot(y)
lines(y.ACMfilt$filt, col=2)
lines(ar2,col="green")
|
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