Test of Goodness-of-Fit of Models for Count data
The function returns a chi-squared test of goodness of fit for models of class glm, aodml or aodql.
gof(object)
gof.default(object)
## S3 method for class 'gof'
print(x, ..., digits = max(3, getOption("digits") - 3))object |
An object of class |
x |
An object of class |
digits |
A numerical scalar indicating the number of digits to be printed after the decimal place. |
... |
Further arguments passed to |
Function gof calculates the deviance D and the Pearson chi-squared X^2 statistics for the model under consideration. Let y be the observed response, and E[y] = μ and Var[y] its mean and variance estimated from the model, statistic X^2 is calculated by:
X^2 = ∑_{i}( (y_i - μ)^2/Var[y_i] )
Assuming that the data length is N and the number of the parameters in the model is p, eqnD and eqnX^2 are compared to a chi-squared distribution with N-p degrees of freedom.
An object of class gof, printed with print.gof.
Agresti, A. Categorical data analysis. Wiley, 1990.
data(orob2) fm1 <- glm(cbind(m, n - m) ~ seed, data = orob2, family = binomial) fm2 <- aodml(cbind(m, n - m) ~ seed, data = orob2, family = "bb") gof(fm1) gof(fm2)
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