Search for periodic signals in noisy time series using Fourier methods

spritzer is a set of R functions developed for detecting strictly or nearly periodic signals in time series dominated by red noise. It is based on code developed and used in

A Bayesian test for periodic signals in red noise Vaughan S., 2010, MNRAS, 402, 307

The name SPRITZER is a blend of the words Strictly Periodic Tester.

spritzer is an R package, but is still in development. To set up from GitHub first install Hadley Wickham's devtools.

install.packages("devtools")

Now you can install straight from GitHub:

devtools::install_github("svdataman/spritzer")

It requires the mnormt package. If you don't already have this, you will also need to install it locally:

install.packages("mnormt")
require(spritzer)

and you're good to go.

Given a data array (or data.frame) as input, containing the time series data in columns (e.g. t, y, dy [optional])

result <- spritz(mrk766)

Spritzer works best if the input time series is regularly sampled, with no gaps, and is a realisation of a red noise process (with a smooth, steep power spectrum), which might contain an additional strictly periodic component. See my 2010 paper for more details.

Lots to do before this is finished.

• strip out the file loading, assume user has data in memory as array (or data.frame)
• replace the MCMC engine with one from tonic (chain generation and diagnostic plots)
• documentation
• unit tests
• better format of output list
• strip out the interactive element (user response to questions) and replace with function arguments on inputs.
• replace simulation in Fourier space with full simulations in time.

MIT