R: Item parameter derivatives

rpf.dLL {rpf} | R Documentation

## Item parameter derivatives

### Description

Evaluate the partial derivatives of the log likelihood with respect to each parameter at `where` with `weight`.

### Usage

    rpf.dLL(m, param, where, weight)

### Arguments

`m` | item model
`param` | item parameters
`where` | location in the latent space
`weight` | per outcome weights (typically derived by observation)

### Details

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.

### Value

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.

### See Also

The numDeriv package.

[Package rpf version 0.56.1 Index]