Gradient of function to optimize over Z in EM step.
1 | tgrad(Z_old, sig_diag, Y, alpha, Tkj, a_seq, b_seq, nu)
|
Z_old |
A vector of numerics. The current value of Z. |
sig_diag |
A vector of length |
Y |
A matrix of dimension |
alpha |
A matrix. This is of dimension |
Tkj |
A matrix of numerics. The weights from pi_new. |
a_seq |
A vector of negative numerics containing the left endpoints of the mixing uniforms. |
b_seq |
A vector of positiv numerics containing the right endpoints of the mixing uniforms. |
nu |
A positive numeric. The degrees of freedom of the t-distribution. |
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