Evaluate the partial derivatives of the log likelihood
with respect to each parameter at where with
weight.
Arguments
m
item model
param
item parameters
where
location in the latent space
weight
per outcome weights (typically derived by
observation)
Value
first and second order partial derivatives of the log
likelihood evaluated at where organized in the
same manner as Bates and Watts. 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.
References
Bates, D. M. & Watts, D. (1980). Relative curvature
measures of nonlinearity. Journal of the Royal
Statistical Society. Series B (Methodological), 42,
1-25.