| generalized_poisson_likelihood {GPseq} | R Documentation |
This function calculates the Maximum Likelihood estimates for theta and lambda when vector y is fit to the Generalized Poisson Model. Newton Raphson Method is employed to calculate the MLE. The values are only valid if the Newton Raphson Method converges.
generalized_poisson_likelihood(y)
y |
Vector of counts. |
mark |
1 if the Newton Raphson Method converges. If mark = 0, then the values of theta and lambda are not applicable |
theta |
Maximum Likelihood Estimate for theta in the Generalized Poisson Model(theta,lambda) |
lambda |
Maximum Likelihood Estimate for lambda in the Generalized Poisson Model(theta,lambda) |
y_bar |
Mean of y which is also the Maximum Likelihood Estimate for lambda for the Poisson model |
length |
Length of y which will be later used to calculate the normalization values |
Sudeep Srivastava, Liang Chen
Consul, P. C. (1989) Generalized Poisson Distributions: Properties and Applications. New York: Marcel Dekker.
Sudeep Srivastava, Liang Chen A two-parameter generalized Poisson model to improve the analysis of RNA-Seq data Nucleic Acids Research Advance Access published July 29,2010 doi : 10.1093/nar/gkq670
y = rpois(100,10);
out = generalized_poisson_likelihood(y);
#Check if it converged
if(out$mark==1)
{
#Value of Theta
cat("theta = ",out$theta,"lambda = ",out$lambda,"lambda_poisson = ",out$y_bar,"Length = ",out$length,"\n");
}