q_delta_f {COMBO} | R Documentation |
Objective function of the form:
Q_{\delta} = \sum_{i = 1}^N \Bigl[\sum_{j = 1}^2 \sum_{k = 1}^2 \sum_{\ell = 1}^2 w_{ij} y^*_{ik} \tilde{y}_{i \ell} \text{log} \{ \tilde{\pi}_{i \ell kj} \}\Bigr]
.
Used to obtain estimates of \delta
parameters.
q_delta_f(
delta_v,
V,
obs_Ystar_matrix,
obs_Ytilde_matrix,
w_mat,
sample_size,
n_cat
)
delta_v |
A numeric array of regression parameters for the second-stage observed
outcome mechanism, |
V |
A numeric design matrix. |
obs_Ystar_matrix |
A numeric matrix of indicator variables (0, 1) for the observed
outcome |
obs_Ytilde_matrix |
A numeric matrix of indicator variables (0, 1) for the observed
outcome |
w_mat |
Matrix of E-step weights obtained from |
sample_size |
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, |
q_beta_f
returns the negative value of the expected log-likelihood function,
Q_{\delta} = \sum_{i = 1}^N \Bigl[\sum_{j = 1}^2 \sum_{k = 1}^2 \sum_{\ell = 1}^2 w_{ij} y^*_{ik} \tilde{y}_{i \ell} \text{log} \{ \tilde{\pi}_{i \ell kj} \}\Bigr]
,
at the provided inputs.