aldvmm.gof {aldvmm}  R Documentation 
aldvmm.gof
calculates residual and likelihoodbased goodness of fit measures.
aldvmm.gof(res, par, ll)
res 
a numeric vector of residuals of all observations in the estimation data. 
par 
a named numeric vector of parameter estimates. 
ll 
a numeric value of the loglikelihood. 
aldvmm.gof
calculates mean squared errors as (sum(y  yhat)^2)/(n  k), and mean absolute
errors as sum(y  yhat)/(n  k), where y denotes observed
outcomes, yhat denotes fitted values, n
denotes the sample size, and k denotes the number of parameters.
The Akaike information criterion is calculated as 2*k 
2*ll, and the Bayesian information criterion is calculated as
k*log(n)  2*ll, where ll denotes the
loglikelihood.
aldvmm.gof
returns a list including the following objects.

a numeric value of the mean squared error of observed versus fitted outcomes. 

a numeric value of the mean absolute error of observed versus fitted outcomes. 

a numeric value of the negative loglikelihood. 

a numeric value of the Akaike information criterion. 

a numeric value of the Bayesian information criterion. 