## S3 method for class 'dynrCook'
nobs(object, ...)

# Minimal model
require(dynr)

meas <- prep.measurement(
	values.load=matrix(c(1, 0), 1, 2),
	params.load=matrix(c('fixed', 'fixed'), 1, 2),
	state.names=c("Position","Velocity"),
	obs.names=c("y1"))

ecov <- prep.noise(
	values.latent=diag(c(0, 1), 2),
	params.latent=diag(c('fixed', 'dnoise'), 2),
	values.observed=diag(1.5, 1),
	params.observed=diag('mnoise', 1))

initial <- prep.initial(
	values.inistate=c(0, 1),
	params.inistate=c('inipos', 'fixed'),
	values.inicov=diag(1, 2),
	params.inicov=diag('fixed', 2))

dynamics <- prep.matrixDynamics(
	values.dyn=matrix(c(0, -0.1, 1, -0.2), 2, 2),
	params.dyn=matrix(c('fixed', 'spring', 'fixed', 'friction'), 2, 2),
	isContinuousTime=TRUE)

data(Oscillator)
data <- dynr.data(Oscillator, id="id", time="times", observed="y1")

model <- dynr.model(dynamics=dynamics, measurement=meas,
	noise=ecov, initial=initial, data=data)

cook <- dynr.cook(model,
	verbose=FALSE, optimization_flag=FALSE, hessian_flag=FALSE)

# Now get the total number of observations
nobs(cook)