View source: R/dependentData_armaEstBipTau.R
arma_est_bip_tau | R Documentation |
The function arma_est_bip_tau(x,p,q) comuptes BIP tau-estimates of the ARMA model parameters. It also computes an outlier cleaned signal using BIP-ARMA(p,q) predictions
arma_est_bip_tau(x, p, q, tolx = 1e-08)
x: |
numeric vector. The signal |
p: |
AR order |
q: |
MA order |
tolx: |
threshold value that is passed to pracma::lsqnonlin. Default = 1e-8 |
result: named list with following fields
ar_coeffs |
numeric vector of length p. BIP-AR(p) tau estimates |
ma_coeffs |
numeric vector of length q. BIP-AR(q) tau estimates |
inno_scale |
numeric, BIP s-estimate of the innovations scale |
ar_coeffs_init |
numeric vector of length p. Robust starting point for estimation |
ma_coeffs_init |
numeric vector of length q. Robust starting point for estimation |
file is in dependentData_arma_Est_BipTau.R
"Robust Statistics for Signal Processing" Zoubir, A.M. and Koivunen, V. and Ollila, E. and Muma, M. Cambridge University Press, 2018.
"Bounded Influence Propagation τ-Estimation: A New Robust Method for ARMA Model Estimation." Muma, M. and Zoubir, A.M. IEEE Transactions on Signal Processing, 65(7), 1712-1727, 2017.
library(signal) N <- 500 a <- rnorm(N) p <- 1 q <- 0 x <- signal::filter(1, c(1, -0.8), a) arma_est_bip_tau(x, p, q)
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