Me being as careful as possible when calculating the succotash log-likelihood.
1 2 | llike_unif_simp(Y, Z, pi_vals, alpha, sig_diag, left_seq, right_seq,
scale_val = 1, likelihood = c("normal", "t"), df = NULL)
|
Y |
a p by 1 matrix of numerics. |
Z |
a k by 1 matrix of numerics. |
pi_vals |
A vector of non-negative numerics that sum to one. The mixing proportions. |
alpha |
A p by k matrix of numerics. |
sig_diag |
A p-vector of numerics. |
left_seq |
The left endpoints of the uniforms. |
right_seq |
The right endpoints of the uniforms |
scale_val |
A positivie numeric. |
likelihood |
Can be |
df |
A positive numeric. The degrees of freedom if the likelihood is t. |
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