Description Usage Arguments Details Value Author(s) Examples
Estimates A, B and f in the harmonic regression, y(t)=mu+A*cos(2*pi*f*t)+B*sin(2*pi*f*t)+e(t). The default algorithm is enumerative but an exact non-linear LS option is also provided.
1 |
y |
series. |
t |
Time points. |
algorithm |
method for the optimization |
Program is interfaced to C for efficient computation.
Object of class "HReg" produced.
A.I. McLeod and Yuanhao Lai
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | set.seed(193)
z <- simHReg(10,f=2.5/10,1,1)
ans <- fitHReg(z)
ans$freq #optimal frequency = 0.2376238
#
#ORF06806 in Cc dataset.
z<-c(0.42, 0.89, 1.44, 1.98, 2.21, 2.04, 0.82, 0.62, 0.56, 0.8, 1.33)
ans2 <- fitHReg(z, algorithm="exact")
sum(resid(ans2)^2) #0.2037463
ans1 <- fitHReg(z)
sum(resid(ans1)^2) #0.242072
#compare with nls()
t <- 1:length(z)
ans <- nls(z ~ mu+alpha*cos(2*pi*lambda*t+phi),
start=list(mu=1, alpha=1, lambda=0.1, phi=0.0))
coefficients(ans)
sum(resid(ans)^2) #0.2037
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