BaSAR.fine: Finely sampled BSA
In JIC-CSB/BaSAR: Bayesian Spectrum Analysis in R

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/BaSAR.R

High-resolution BSA which identifies the highest peak and samples more finely in its vicinity.

1	BaSAR.fine(data, start, stop, nsamples, nbackg, tpoints)

`data`	data as a 1-dimensional vector
`start`	lower limit of period of interest, in seconds
`stop`	upper limit of period of interest, in seconds
`nsamples`	number of samples within the interval start-stop
`nbackg`	number of background functions to be added to the model
`tpoints`	vector of time points, in seconds

BaSAR.fine combines the function BaSAR.post with a Downhill-Simplex optimizer to identify the maximum peak in the frequency range chosen. It then samples over a narrower range around this peak for a high-resolution estimate of the strongest frequency. See e.g. Press (2002) for an example of Downhill-Simplex optimization.

A list containing:

`normp`	1D normalized posterior distribution over omega
`omega`	1D vector of the omega sampled
`stats`	list of statistics from the probability distribution

Emma Granqvist, Matthew Hartley and Richard J Morris.

Granqvist, E., Oldroyd, G. E. and Morris, R. J. (2011) Automated Bayesian model development for frequency detection in biological time series. BMC Syst Biol 5, 97.
http://dx.doi.org/10.1186/1752-0509-5-97

Press, W. H. (2002) Numerical recipes in C++: the art of scientific computing, 2nd Edition. Cambridge, UK: Cambridge University Press.

BaSAR.post

# Create time series with omega = 0.5 and add noise
tpoints = seq(from=1, to=200, length=200)
r1 = rnorm(200, 0, 1)
r2 = rnorm(200, 0, 1)
dpoints = sin(0.5 * tpoints + 0.1 * (0.5-r1)) + 0.7 * r2
# Plot time series
plot(dpoints, type="l", col="blue", xlab="t", ylab="d(t)")
# Run BaSAR 
r = BaSAR.fine(dpoints, 6, 600, 100, 0, tpoints)
# Plot the resulting probability density function around maximum peak 
plot(r$omega, r$normp, xlim=c(0:1), type="h", col="red", ylab="PDF", 
xlab=expression(omega))