Description Usage Arguments Details Value Author(s) See Also Examples
Summarizes the Poisson P-spline model fitted to a unidimensional data. It returns various settings and measures.
1 2 |
object |
an object of class "Mort1Dsmooth", usually, a result of
a call to |
... |
further arguments passed to or from other methods. |
print.summary.Mort1Dsmooth
tries to be smart about formatting
settings, outcomes, etc. After the matched call, the function presents
several outcomes of the model, such as AIC, BIC, effective dimension,
selected smoothing parameter, overdispersion parameter and a summary
of the deviance residuals. The last lines show specifications and
control parameters of the fitted model.
It produces an object of class summary.Mort1Dsmooth
which
contains exactly the same components of the associated
Mort1Dsmooth
object.
Carlo G Camarda
1 2 3 4 5 6 7 8 9 10 11 | ## selected data
years <- 1970:2006
death <- selectHMDdata("Sweden", "Deaths", "Females",
ages = 0, years = years)
exposure <- selectHMDdata("Sweden", "Exposures", "Females",
ages = 0, years = years)
## fit
fit <- Mort1Dsmooth(x=years, y=death, offset=log(exposure),
method=3, lambda=30)
## summary
summary(fit)
|
Loading required package: svcm
Loading required package: Matrix
Loading required package: splines
Loading required package: lattice
Call:
Mort1Dsmooth(x = years, y = death, offset = log(exposure), lambda = 30,
method = 3)
Number of Observations : 37
Effective dimension : 5.965
(Selected) smoothing parameter : 30
Bayesian Information Criterion (BIC) : 68.779
Akaike's Information Criterion (AIC) : 59.169
(Estimated) dispersion parameter (psi^2): 1.52
Residuals:
Min 1Q Median 3Q Max
-1.9481 -0.9754 -0.2397 0.8979 2.8307
Settings and control:
number of B-splines : 10
degree of the B-splines: 3
order of differences : 2
convergence tolerance : 7.3164e-07
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.