Evaluate the partial derivatives of the log likelihood with
respect to each parameter at where with weight.
rpf.dLL(m, param, where, weight)first and second order partial derivatives of the log
likelihood evaluated at where. For p parameters, the first
p values are the first derivative and the next p(p+1)/2 columns
are the lower triangle of the second derivative.
item model
item parameters
location in the latent space
per outcome weights (typically derived by observation)
It is not easy to write an example for this function. To evaluate the derivative, you need to sum the derivatives across a quadrature. You also need response outcome weights at each quadrature point. It is not anticipated that this function will be often used in R code. It's mainly to expose a C-level function for occasional debugging.
The numDeriv package.