Item parameter derivatives
Evaluate the partial derivatives of the log likelihood with
respect to each parameter at where with weight.
rpf.dLL(m, param, where, weight)
m |
item model |
param |
item parameters |
where |
location in the latent space |
weight |
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.
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.
The numDeriv package.
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