NOAV {avar} | R Documentation |
Calculation of the theoretical Non-overlapping Allan variance for constant-mean non-stationary time series data.
NOAV(n, covmat)
n |
An |
covmat |
A |
This calculation of Non-overlapping Allan variance is based on the definition on "A Study of the Allan Variance for Constant-Mean Non-Stationary Processes" by Xu et al., 2017, IEEE Signal Processing Letters, 24(8): 1257–1260. Here n is an integer larger than 1 and smaller than floor(log2(dim(T)[1]))-1.
A field <numeric>
that is the theoretical Non-overlapping Allan variance for constant-mean non-stationary time series data.
Haotian Xu
set.seed(999) Xt = arima.sim(n = 100, list(ar = 0.3)) avar(Xt, type = "to") a = matrix(rep(0, 1000^2), nrow = 1000) for (i in 1:1000){ a[,i] = seq(from = 1 - i, length.out = 1000) } a.diag = diag(a) a[upper.tri(a,diag=TRUE)] = 0 a = a + t(a) + diag(a.diag) covmat = 0.3^a sapply(1:8, function(y){NOAV(2^y, covmat)})