mxl_predict: Per-observation simulated choice probabilities for Mixed...

In choicer: Discrete Choice Models for Economic Applications

Per-observation simulated choice probabilities for Mixed Logit

Description

Returns the simulated choice probability for each (individual, alternative) row of X, averaged over the supplied Halton draws. Mirrors mnl_predict.

Usage

mxl_predict(
  theta,
  X,
  W,
  alt_idx,
  M,
  eta_draws,
  rc_dist,
  rc_correlation = TRUE,
  rc_mean = FALSE,
  use_asc = TRUE,
  include_outside_option = FALSE,
  gen_seed = -1L,
  gen_scramble = 1L,
  gen_S = 0L
)

Arguments

theta	parameter vector (beta, [mu], L, delta)
X	design matrix for fixed coefficients; sum(M_i) x K_x
W	design matrix for random coefficients; sum(M_i) x K_w or J x K_w
alt_idx	sum(M) x 1 vector with indices of alternatives; 1-based indexing
M	N x 1 vector with number of alternatives for each individual
eta_draws	Array with draws; K_w x S x N
rc_dist	K_w vector indicating distribution (0=normal, 1=log-normal)
rc_correlation	whether random coefficients are correlated
rc_mean	whether mu parameters are estimated
use_asc	whether ASCs are included
include_outside_option	whether the outside option is present
gen_seed	Integer master seed for the on-the-fly Halton generator. < 0 (default) uses the materialized eta_draws cube; >= 0 generates draws on the fly from this seed.
gen_scramble	Integer scramble mode for on-the-fly generation: 0 = identity permutations (plain Halton, compat), 1 = seeded position-wise digit permutations.
gen_S	Integer number of draws per individual, used only when gen_seed >= 0.

Value

List with choice_prob (length sum(M)), utility (length sum(M), simulated mean of the deterministic + W*gamma component), and, when include_outside_option = TRUE, choice_prob_outside (length N).

choicer documentation built on Sept. 5, 2026, 1:07 a.m.