confint.cp_model_nls: Confidence Intervals for Cross-Price NLS Model Parameters

In beezdemand: Behavioral Economic Easy Demand

Confidence Intervals for Cross-Price NLS Model Parameters

Description

Computes confidence intervals for parameters from a nonlinear cross-price demand model using nlstools::confint2().

Usage

## S3 method for class 'cp_model_nls'
confint(
  object,
  parm = NULL,
  level = 0.95,
  method = c("asymptotic", "profile"),
  ...
)

Arguments

object	A cp_model_nls object from fit_cp_nls().
parm	Character vector of parameter names to compute CIs for. Default includes all parameters.
level	Confidence level (default 0.95).
method	Character. Method for computing intervals passed to nlstools::confint2(): "asymptotic" (default): Wald-type asymptotic intervals "profile": Profile-t confidence intervals
...	Additional arguments passed to nlstools::confint2().

Details

This method wraps nlstools::confint2() to provide confidence intervals for the log10-parameterized coefficients (log10_qalone, I, log10_beta).

For back-transformed natural-scale confidence intervals, apply the transformation: 10^conf.low and 10^conf.high for log10-scale parameters.

Value

A tibble with columns: term, estimate, conf.low, conf.high, level, method.

Examples

data(etm)
fit <- fit_cp_nls(etm, equation = "exponentiated")
confint(fit)

beezdemand documentation built on March 3, 2026, 9:07 a.m.