pitilde_by_chain {COMBO} | R Documentation |
Compute the Mean Conditional Probability of Second-Stage Correct Classification, by First-Stage and True Outcome Across all Subjects for each MCMC Chain
Description
Compute the Mean Conditional Probability of Second-Stage Correct Classification, by First-Stage and True Outcome Across all Subjects for each MCMC Chain
Usage
pitilde_by_chain(n_chains, chains_list, V, n, n_cat)
Arguments
n_chains |
An integer specifying the number of MCMC chains to compute over. |
chains_list |
A numeric list containing the samples from |
V |
A numeric design matrix. |
n |
An integer value specifying the number of observations in the sample.
This value should be equal to the number of rows of the design matrix, |
n_cat |
The number of categorical values that the true outcome, |
Value
pitilde_by_chain
returns a numeric matrix of the average
conditional probability P( \tilde{Y} = j | Y^* = j, Y = j, V)
across all subjects for
each MCMC chain. Rows of the matrix correspond to MCMC chains, up to n_chains
.
The first column contains the conditional probability P( \tilde{Y} = 1 | Y^* = 1, Y = 1, V)
.
The second column contains the conditional probability P( \tilde{Y} = 2 | Y^* = 2, Y = 2, V)
.