priorcontrol.dpm {ROCnReg}

Prior information for the pooledROC.dpm

Description

This function is used to set various parameters controlling the prior information to be used in the pooledROC.dpm function.

Usage

priorcontrol.dpm(m0 = NA, S0 = NA, a = 2, b = NA, alpha = 1, L = 10)

Arguments

m0

A numeric value. Hyperparameter; mean of the normal prior distribution for the means of each component. NA signals autoinitialization, with defaults: 0 if the data are standardised and \bar{y}_d (d \in \{D, \bar{D}\} if the data are not standardised.

S0

A numeric value. Hyperparameter; variance of the normal prior distribution for the means of each component. NA signals autoinitialization, with defaults: 10 if the data are standardised and 100*\frac{s^2_d}{n_d} (d \in \{D, \bar{D}\} if the data are not standardised, where s_d denotes the sample standard deviation.

a

A numeric value. Hyperparameter; shape parameter of the gamma prior distribution for the precisions (inverse variances) of each component. The default is 2.

b

A numeric value. Hyperparameter; rate parameter of the gamma prior distribution for the precisions (inverse variances) of each component. NA signals autoinitialization, with defaults: 0.5 if the data are standardised and \frac{s^2_d}{2} (d \in \{D, \bar{D}\} if the data are not standardised.

alpha

A numeric value. Precision parameter of the Dirichlet Process. The default is 1.

L

A numeric value. Upper bound on the number of mixture components. Setting L=1 corresponds to a normal model. The default is 10.

Value

A list with components for each of the possible arguments.

See Also

pooledROC.dpm