Compute Probability of Each True Outcome, for Every Subject
pi_compute(beta, X, n, n_cat)pi_compute returns a matrix of probabilities,
\(P(Y_i = j | X_i) = \frac{\exp(X_i \beta)}{1 + \exp(X_i \beta)}\)
for each of the \(i = 1, \dots,\)
n subjects. Rows of the matrix
correspond to each subject. Columns of the matrix correspond to the true outcome
categories \(j = 1, \dots,\)
n_cat.
A numeric column matrix of regression parameters for the
Y (true outcome) ~ X (predictor matrix of interest).
A numeric design matrix.
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, X.
The number of categorical values that the true outcome, Y,
can take.