| 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)