How to derive conditional maximum likelihood of the sum of independent negative binomial variables?
1
1
Entering edit mode
21 months ago
Dan ▴ 180

In the paper Small-sample estimation of negative binomial dispersion, with applications to SAGE data, section 4.1 Conditional maximum likelihood:

For RNA sequencing data, assume the counts for a single tag across n libraries is a negative binomial random variable. Consider Y1,⋯,Yn as independent and $$NB(\mu_i = m_i \lambda, \phi)$$, where mi is the library size (i.e. total number of tags sequenced for library i) and λ represents the proportion of the library that is a particular tag. The probability mass function is:

$$f(y_i;\mu,\phi)=P(Y=y_i)=\frac{\Gamma(\phi^{-1}+y_i)}{\Gamma(\phi^{-1})\Gamma(y_i+1)}\left(\frac{1}{\phi^{-1}\mu^{-1}+1}\right)^{y_i}\left(\frac{1}{\phi\mu+1}\right)^{\phi^{-1}} \tag 1$$

$$\text{E}(Y)=\mu$$ and $$\text{Var}(Y)=\mu+\phi\mu^2$$

If all libraries are the same size (i.e. mi≡m), the sum $$Z = Y_1 + \cdots + Y_n \sim NB(nm\lambda, \phi n^{−1})$$

How to derive conditional maximum likelihood for ϕ that is independent of λ, and how to calculate the maximum of the likelihood?

$$l_{Y|Z=z}(\phi)=\left[\sum_{i=1}^{n}\log\Gamma(y_i+\phi^{-1})\right]+\log\Gamma(n\phi^{-1})-\log\Gamma(z+n\phi^{-1})-n\log\Gamma(\phi^{-1})$$

limma voom biostatistics • 668 views
ADD COMMENT
4
Entering edit mode
20 months ago
Dan ▴ 180

I try to answer this question. Based on the Conditional Likelihood defined in https://rss.onlinelibrary.wiley.com/doi/epdf/10.1111/j.2517-6161.1996.tb02101.x, the conditional log-likelihood for ϕ of Y conditioned on Z, dropping terms that don't involve ϕ, is: $$l_{Y|Z=z}(\mathbf y; \phi)=\log f(\mathbf y;\mu,\phi)-\log f_{z}(z;n\mu,n^{-1}\phi)$$

$$=\sum\log \Gamma(y_i+\phi^{-1}) - n \log\Gamma(\phi^{-1}) + \sum y_i\log\left({\phi\mu \over 1 + \phi\mu}\right) + n\phi^{-1}\log\left({1 \over 1 + \phi\mu}\right) $$

$$-\log\Gamma(z+n\phi^{-1})+\log\Gamma(n\phi^{-1})-z\log\left({\phi\mu \over 1 + \phi\mu}\right) - n\phi^{-1}\log\left({1 \over 1 + \phi\mu}\right)$$

$$=\left[\sum_{i=1}^{n}\log\Gamma(y_i+\phi^{-1})\right]+\log\Gamma(n\phi^{-1})-\log\Gamma(z+n\phi^{-1})-n\log\Gamma(\phi^{-1})$$

ADD COMMENT

Login before adding your answer.

Traffic: 2492 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6