summary.nsCosinor: Summary for a Non-stationary cosinor
Description
The default summary method for a nsCosinor object produced by nscosinor.Usage
## S3 method for class 'nsCosinor':
summary(object, ...)
## S3 method for class 'summary.nsCosinor':
print(x, ...)
Arguments
object
a nsCosinor object produced by nscosinor.
x
a summary.nsCosinor object produced by
summary.nsCosinor.
...
further arguments passed to or from other methods.
Value
- cyclesvector of cycles in units of time, e.g., for a six and twelve month pattern
cycles=c(6,12). - niterstotal number of MCMC samples.
- burninnumber of MCMC samples discarded as a burn-in.
- tauvector of smoothing parameters, tau[1] for trend, tau[2] for
1st seasonal parameter, tau[3] for 2nd seasonal parameter, etc.
- statssummary statistics (mean and confidence interval) for the
residual standard deviation, the standard deviation for each seasonal
cycle, and the amplitude and phase for each cycle.
Details
The amplitude describes the average height of each seasonal
cycle, and the phase describes the location of the peak. The results
for the phase are given in radians (0 to 2$\pi$), they can be
transformed to the time scale using the invyrfraction making
sure to first divide by 2$\pi$.
The larger the standard deviation for the seasonal cycles, the greater
the non-stationarity. This is because a larger standard deviation means
more change over time.See Also
nscosinor, plot.nsCosinor