anova.evd {evd} | R Documentation |
Compute an analysis of deviance table for two or more nested evd objects.
## S3 method for class 'evd': anova(object, object2, ...)
object |
An object of class "evd" . |
object2 |
An object of class "evd" that
represents a model nested within object . |
... |
Further successively nested objects. |
An object of class c("anova", "data.frame")
, with one
row for each model, and the following five columns
M.Df |
The number of parameters. |
Deviance |
The deviance. |
Df |
The number of parameters of the model in the previous row minus the number of parameters. |
Chisq |
The deviance minus the deviance of the model in the previous row. |
Pr(>chisq) |
The p-value calculated by comparing the quantile
Chisq with a chi-squared distribution on Df degrees
of freedom. |
Circumstances may arise such that the asymptotic distribution of the test statistic is not chi-squared. In particular, this occurs when the nested model is constrained at the edge of the parameter space. It is up to the user recognize this, and to interpret the output correctly.
fbvevd
, fextreme
,
fgev
, forder
uvdata <- rgev(100, loc = 0.13, scale = 1.1, shape = 0.2) trend <- (-49:50)/100 M1 <- fgev(uvdata, nsloc = trend) M2 <- fgev(uvdata) M3 <- fgev(uvdata, shape = 0) anova(M1, M2, M3) bvdata <- rbvevd(100, dep = 0.75, model = "log") M1 <- fbvevd(bvdata, model = "log") M2 <- fbvevd(bvdata, model = "log", dep = 0.75) anova(M1, M2)