| worstErrors {qvcalc} | R Documentation |
Computes the worst relative error, among all contrasts, for the standard error as derived from a set of quasi-variances. For details of the method see Menezes (1999) or Firth and Menezes (2002).
worstErrors(qv.object)
qv.object |
An object of class qv |
A numeric vector of length 2, the worst negative relative error and the worst positive relative error.
David Firth, david.firth@nuffield.ox.ac.uk
Firth, D. and Mezezes, R. X. de (2002) Quasi-variances. Submitted for publication. At http://www.stats.ox.ac.uk/~firth/papers/.
McCullagh, P. and Nelder, J. A. (1989) Generalized Linear Models. London: Chapman and Hall.
Menezes, R. X. (1999) More useful standard errors for group and factor effects in generalized linear models. D.Phil. Thesis, Department of Statistics, University of Oxford.
## Overdispersed Poisson loglinear model for ship damage data
## from McCullagh and Nelder (1989), Sec 6.3.2
library(MASS)
data(ships)
ships$year <- as.factor(ships$year)
ships$period <- as.factor(ships$period)
shipmodel <- glm(formula = incidents ~ type + year + period,
family = quasipoisson,
data = ships, subset = (service > 0), offset = log(service))
shiptype.qvs <- qvcalc(shipmodel, "type")
summary(shiptype.qvs, digits=4)
worstErrors(shiptype.qvs)