sim.wordfish: Simulate data and parameters for a Wordfish model
In conjugateprior/austin: Do Things with Words

Description Usage Arguments Details Value Author(s)

Simulates data and returns parameter values using Wordfish model assumptions: Counts are sampled under the assumption of independent Poisson draws with log expected means linearly related to a lattice of document positions.

sim.wordfish(
  docs = 10,
  vocab = 20,
  doclen = 500,
  dist = c("spaced", "normal"),
  scaled = TRUE
)

`docs`	How many ‘documents’ should be generated
`vocab`	How many ‘word’ types should be generated
`doclen`	A scalar ‘document’ length or vector of lengths
`dist`	the distribution of ‘document’ positions
`scaled`	whether the document positions should be mean 0, unit sd

This function draws ‘docs’ document positions from a Normal distribution, or regularly spaced between 1/‘docs’ and 1.

‘vocab’/2 word slopes are 1, the rest -1. All word intercepts are 0. ‘doclen’ words are then sampled from a multinomial with these parameters.

Document position (theta) is sorted in increasing size across the documents. If ‘scaled’ is true it is normalized to mean zero, unit standard deviation. This is most helpful when dist=normal.

`Y`	A sample word-document matrix
`theta`	The ‘document’ positions
`doclen`	The ‘document’ lengths
`beta`	‘Word’ intercepts
`psi`	‘Word’ slopes