FIM_logisitic_1par

vector of design points. In IRT <code>x</code> is the person ability parameter.

vector of design weight. Its length must be equal to the length of <code>x</code> and <code>sum(w)</code> should be 1.

parameter $a$. In IRT, it is called difficulty parameter.

param


The mean of response variable is
 $$f(x, a) = 1/(1 + \exp(-(x - a))).$$
 This function returns Fisher information for the design $\xi$ that is
 $$M(\xi; a) = \sum_{i = 1}^kw_iM(x_i, a).$$
  Here $M(x, a)$  is $g(x-a)$, where
 $g(z) = exp(z)/(1 + exp(z))^2$.
 denotes the standard logisitc density.


Finding locally D-optimal, minimax D-optimal, standardized maximin D-optimal, optim-on-the-average and multiple objective optimal designs for nonlinear models. Different Fisher information matrices can also be set by user. There are also  useful functions for verifying the optimality of the designs with respect to different criteria by equivalence theorem. ICA is a meta-heuristic evolutionary algorithm inspired from the socio-political process of humans. See Masoudi et al. (2016) <doi:10.1016/j.csda.2016.06.014>.

FIM_logisitic_1par: Fisher information matrix for the one-parameter logistic model (1PL or Rasch model).

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