f.expect.cat: computed expected value for categorical model
In alfcrisci/bmdModeling: Benchmark dose modeling

computed expected value for categorical model

f.expect.cat(model.type = 2, model.ans, x, regr.par = 0, th.par = 0,
  sig.par = 0, fct1 = 1, fct2 = 1, CES = 0, CES.cat = 1, latent = F,
  ttt = 0, twice, fct3 = 1, ces.ans, decr.zz = T, dtype, fct4 = 1,
  fct5 = 1, fct1.txt = "", fct2.txt = "", fct3.txt = "",
  fct4.txt = "", fct5.txt = "", covar.txt = "", fct3.ref, track = FALSE)

`model.type`	model type
`model.ans`	type or response fitted
`x`	observations
`regr.par`	parameters
`th.par`	parameter theta
`sig.par`	parameter sigma (standard deviations)?
`fct1`	numeric, value for first parameter
`fct2`	numeric, value for second parameter
`CES`	CES value
`CES.cat`	CES cat
`latent`	latent model
`ttt`	ttt
`twice`	logical, if TRUE two parameters are dependent of the same covariate
`fct3`	numeric, value for third parameter
`ces.ans`	type of benchmark response
`decr.zz`	is decreasing
`dtype`	response data type
`fct4`	numeric, value for fourth parameter
`fct5`	numeric, value for fifth parameter
`fct1.txt`	text for parameter 1
`fct2.txt`	text for parameter 2
`fct3.txt`	text for parameter 3
`fct4.txt`	text for parameter 4
`fct5.txt`	text for parameter 5
`covar.txt`	text for covar
`fct3.ref`	parameter 3 of reference
`track`	logical, if TRUE (FALSE by default) print the name of the function which is currently being run