ISOpureS1.model_optimize.vv.vv_compute_loglikelihood: Compute loglikelihood relevant to vv for step 1
In ISOpureR: Deconvolution of Tumour Profiles
Description
Usage
Arguments
Value
Author(s)
Description
Computes the part of the loglikelihood function relevant to optimizing vv for step 1.
Usage
1
ISOpureS1.model_optimize.vv.vv_compute_loglikelihood(vv, sum_log_theta, DD)
Arguments
vv
Kx1 matrix representing the weights of the normal profiles B_i used to make the
weighted combination that forms the mean parameter vector for the Dirichlet distribution
over m
sum_log_theta
the column sums of log(theta), a 1xK matrix
DD
the number of patients (a scalar)
Value
The negative of the loglikelihood relevant to optimizing vv
Author(s)
Gerald Quon, Catalina Anghel, Francis Nguyen
ISOpureR documentation built on May 11, 2019, 1:02 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Usage Arguments Value Author(s)
Description
Computes the part of the loglikelihood function relevant to optimizing vv for step 1.
Usage
1 | ISOpureS1.model_optimize.vv.vv_compute_loglikelihood(vv, sum_log_theta, DD)
|
Arguments
vv |
Kx1 matrix representing the weights of the normal profiles B_i used to make the weighted combination that forms the mean parameter vector for the Dirichlet distribution over m |
sum_log_theta |
the column sums of log(theta), a 1xK matrix |
DD |
the number of patients (a scalar) |
Value
The negative of the loglikelihood relevant to optimizing vv
Author(s)
Gerald Quon, Catalina Anghel, Francis Nguyen
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.