blp.choicer_nl: BLP contraction mapping for nested logit model

In choicer: Discrete Choice Models for Economic Applications

BLP contraction mapping for nested logit model

Description

BLP contraction mapping for nested logit model

Usage

## S3 method for class 'choicer_nl'
blp(
  object,
  target_shares,
  delta_init = NULL,
  damping = 1,
  tol = 1e-08,
  max_iter = 1000,
  ...
)

Arguments

object	A choicer_nl object fitted with keep_data = TRUE.
target_shares	Numeric vector of target market shares. Length J_inside when no outside option, or J_inside + 1 (with the outside option's share at index 1) when include_outside_option = TRUE.
delta_init	Initial guess for delta (ASC) values. If NULL, uses the estimated ASCs from the fitted model.
damping	Contraction damping factor in (0, 1] (default 1).
tol	Convergence tolerance (default 1e-8).
max_iter	Maximum iterations (default 1000).
...	Additional arguments (ignored).

Value

Converged delta (ASC) vector.

Examples

library(data.table)
set.seed(42)
N <- 50; J <- 4
dt <- data.table(id = rep(1:N, each = J), alt = rep(1:J, N))
dt[, nest := rep(c(1L, 1L, 2L, 2L), N)]
dt[, `:=`(x1 = rnorm(.N), x2 = rnorm(.N))]
dt[, choice := 0L]
dt[, choice := sample(c(1L, rep(0L, J - 1))), by = id]
fit <- run_nestlogit(dt, "id", "alt", "choice", c("x1", "x2"), "nest")
blp(fit, target_shares = rep(1/J, J))

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