nobs.dynrCook {dynr}

Extract the number of observations for a dynrCook object

Description

Extract the number of observations for a dynrCook object

Usage

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

Arguments

object

A fitted model object

...

Further named arguments. Ignored.

Details

We return the total number of rows of data, adding up the number of time points for each person. For some purposes, you may want the mean number of observations per person or the number of people instead. These are not currently supported via nobs.

Value

A single number. The total number of observations across all IDs.

Examples

# 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)

## Not run: 
cook <- dynr.cook(model,
	verbose=FALSE, optimization_flag=FALSE, hessian_flag=FALSE)

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

## End(Not run)