residuals.Mort1Dsmooth {MortalitySmooth} | R Documentation |
Extracting different types of residuals from a Mort1Dsmooth
object.
## S3 method for class 'Mort1Dsmooth': residuals(object, type = c("deviance", "pearson", "anscombe", "working"), ...)
object |
An object of class "Mort1Dsmooth", usually, a result of
a call to Mort1Dsmooth . |
type |
The type of residuals which should be returned. The alternatives are: "deviance" (default), "anscombe", "pearson" and "working". |
... |
Further arguments passed to or from other methods. |
The references define the types of residuals.
The way of computing the residuals are described in Section 2.4 of McCullagh and Nelder's book. The working residuals are merely the differences between fitted and actual counts.
A vector of the selected type of residuals for each of the predictor
in the Mort1Dsmooth
object.
Carlo G Camarda
Davison, A. C. and Snell, E. J. (1991). Residuals and diagnostics. In: Statistical Theory and Modelling. In Honour of Sir David Cox, FRS, eds. Hinkley, D. V., Reid, N. and Snell, E. J., Chapman & Hall.
McCullagh P. and Nelder, J. A. (1989). Generalized Linear Models. London: Chapman and Hall.
Mort1Dsmooth
for computing
Mort1Dsmooth.object
, residuals
.
# selected data years <- 1970:2006 death <- selectHMDdata("Denmark", "Deaths", "Females", ages = 60, years = years) exposure <- selectHMDdata("Denmark", "Exposures", "Females", ages = 60, years = years) # fit fit <- Mort1Dsmooth(x=years, y=death, offset=log(exposure), method=3, lambda=1000) # extracting residuals devR <- resid(fit, type="deviance") ansR <- resid(fit, type="anscombe") peaR <- resid(fit, type="pearson") worR <- resid(fit, type="working") # summaries summary(devR) summary(ansR) summary(peaR) summary(worR)