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Specify Prior Distributions

Source: R/priors.R
prior.Rd

Specify prior distributions for model parameters using distribution functions.

Usage

prior(prior, class = "b", coef = "")

Arguments

prior

A distribution object created by normal(), gamma(), student_t(), or cauchy().

class

The parameter class. Valid classes are:

  • "b": Regression coefficients (beta)

  • "Intercept": Cutpoints/thresholds (flexible)

  • "c1": First cutpoint (equidistant)

  • "d": Threshold interval (equidistant)

  • "cpos": Positive cutpoints (symmetric)

  • "df": Degrees of freedom (tlink)

  • "lambda_ao": Lambda parameter (aranda_ordaz)

  • "lambda_lg": Lambda parameter (log_gamma)

  • "xi": Xi parameter (gev)

  • "r": R parameter (sp)

  • "theta1", "theta2": Theta parameters (aep)

coef

Optional coefficient name (for future extension).

Value

An object of class "clm_prior_spec" representing the prior specification.

See also

normal(), gamma(), student_t(), cauchy(), clm_prior()

Examples

# Specify a normal prior for regression coefficients
prior(normal(0, 2.5), class = "b")
#> Prior: normal(0, 2.5)
#> Class: b

# Specify a gamma prior for degrees of freedom
prior(gamma(2, 0.1), class = "df")
#> Prior: gamma(2, 0.1)
#> Class: df

# Combine multiple priors
c(
  prior(normal(0, 2.5), class = "b"),
  prior(normal(0, 10), class = "Intercept")
)
#> Prior specifications:
#>   1. b: normal(0, 2.5)
#>   2. Intercept: normal(0, 10)