Description Usage Arguments Value
Compute ordinary & penalized log-likelihood ratio resulting from MEM algorithm at k=1,2,3.
1 2 3 |
y |
n by 1 vector of data |
parlist |
The parameter estimates as a list containing alpha, mu, sigma, and gamma in the form of (alpha = (alpha_1, ..., alpha_m), mu = (mu_1, ..., mu_m), sigma = (sigma_1, ..., sigma_m), gam = (gamma_1, ..., gamma_m)) |
z |
n by p matrix of regressor associated with gamma |
an |
a term used for penalty function |
tauset |
A set of initial tau value candidates |
ninits |
The number of randomly drawn initial values. |
epsilon.short |
The convergence criterion in short EM. Convergence is declared when the penalized log-likelihood increases by less than |
epsilon |
The convergence criterion. Convergence is declared when the penalized log-likelihood increases by less than |
maxit.short |
The maximum number of iterations in short EM. |
maxit |
The maximum number of iterations. |
verb |
Determines whether to print a message if an error occurs. |
parallel |
Determines what percentage of available cores are used, represented by a double in [0,1]. 0.75 is default. |
cl |
Cluster used for parallelization; if it is |
A list with items:
loglik |
Log-likelihood resulting from MEM algorithm at k=1,2,3. |
penloglik |
Penalized log-likelihood resulting from MEM algorithm at k=1,2,3. |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.