ISOpure.model_optimize.vv.vv_deriv_loglikelihood: Compute the derivative of the loglikelihood relevant to vv...
In ISOpureR: Deconvolution of Tumour Profiles
Description
Usage
Arguments
Value
Author(s)
Description
Computes the derivative of the loglikelihood function relevant to optimizing vv for
step 1
Usage
1
ISOpure.model_optimize.vv.vv_deriv_loglikelihood(ww, sum_log_theta, DD)
Arguments
ww
log(vv-1), a Kx1 matrix
sum_log_theta
the column sums of log(theta), a 1xK matrix
DD
the number of patients (a scalar)
Value
The negative derivative of the part of the loglikelihood function relevant to vv with
respect to (log) 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 derivative of the loglikelihood function relevant to optimizing vv for step 1
Usage
1 | ISOpure.model_optimize.vv.vv_deriv_loglikelihood(ww, sum_log_theta, DD)
|
Arguments
ww |
log(vv-1), a Kx1 matrix |
sum_log_theta |
the column sums of log(theta), a 1xK matrix |
DD |
the number of patients (a scalar) |
Value
The negative derivative of the part of the loglikelihood function relevant to vv with respect to (log) 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.