Lspec: logspline estimation of a spectral distribution

Summary of a model fitted with lspec

# S3 method for class 'lspec'
summary(object, ...) 
# S3 method for class 'lspec'
print(x, ...)

Arguments

object,x

lspec object, typically the result of lspec.

...

other options are ignored.

Details

These function produce an identical printed summary of an lspec object.

References

Charles Kooperberg, Charles J. Stone, and Young K. Truong (1995). Logspline Estimation of a Possibly Mixed Spectral Distribution. Journal of Time Series Analysis, 16, 359-388.

Charles J. Stone, Mark Hansen, Charles Kooperberg, and Young K. Truong. The use of polynomial splines and their tensor products in extended linear modeling (with discussion) (1997). Annals of Statistics, 25, 1371–1470.

Author

Charles Kooperberg clk@fredhutch.org.

See also

lspec, plot.lspec, clspec, dlspec, plspec, rlspec.

Examples

data(co2)
co2.detrend <- lm(co2~c(1:length(co2)))$residuals
fit <- lspec(co2.detrend)
summary(fit)
#>  Logspline Spectral Estimation
#>  =============================
#>  The fit was obtained by the command:
#>  lspec(data = co2.detrend)
#>  A spline with 5 knots, was fitted; there were also 3 lines in the model.
#>  The log-likelihood of the model was 722.42 which corresponds to an AIC
#>  value of -1401.19 .
#> 
#>  The program went though 3 updown cycles, and reached a stable solution.
#>  Both penalty (AIC) and minmass were the default values. For penalty this
#>  was log(n)=log( 234 )= 5.46  (as in BIC) and for minmass this was 0.1086 .
#>  The locations of the knots were: 0.013 0.483 0.524 0.591 0.631 
#>  The locations and the mass in each line were:
#>  angular frequency period    mass % of total mass
#>              0.013    468 1.04797           15.45
#>              0.524     12 1.95568           28.82
#>              1.047      6 0.14723            2.17