[R] nls start values

[Niklaus Fankhauser]

I'm using nls to fit periodic gene-expression data to sine waves. I need
to set the upper and lower boundaries, because I do not want any
negative phase and amplitude solutions. This means that I have to use
the "port" algorithm. The problem is, that depending on what start value
I choose for phase, the fit works for some cases, but not for others.
In the example below, the fit works using phase=pi,  but not using
phase=0. But there are many examples which fit just fine using 0.

Is there a comparable alternative to nls that is not so extremely
influenced by the start values?

# Data for example fit
lowervals <- list(phase=0, amp=0)
uppervals <- list(phase=2*pi, amp=2)
afreq <- 1 / (24 / 2 / pi)
gene_expression <- c(1.551383, 1.671742, 1.549499, 1.694480, 1.632436,
1.471568, 1.623381,
1.579361, 1.809394, 1.753223, 1.685918, 1.754968, 1.963069, 1.820690,
1.985159, 2.205064,
2.160308, 2.120189, 2.194758, 2.165993, 2.189981, 2.098671, 2.122207,
2.012621, 1.963610,
1.884184, 1.955160, 1.801175, 1.829686, 1.773260, 1.588768, 1.563774,
1.559192)
tpoints <-
c(0,0,0,2,2,2,4,4,4,6,6,6,8,8,8,12,12,12,14,14,14,16,16,16,18,18,18,20,20,20,24,24,24)
shift=mean(gene_expression) # y-axis (expression) shift

# Perfect fit
startvals <- list(phase=pi, amp=0.5)
sine_nls <- nls(gene_expression ~ sin(tpoints * afreq + phase) * amp +
shift, start=startvals, algorithm="port", lower=lowervals, upper=uppervals)

# Convergence failure
startvals <- list(phase=0, amp=0.5)
sine_nls <- nls(gene_expression ~ sin(tpoints * afreq + phase) * amp +
shift, start=startvals, algorithm="port", lower=lowervals, upper=uppervals)