tau2.0.objective {edgeR} | R Documentation |
Objective function for tau2 which is used in the rule of how much to squeeze the dispersion parameters towards the common value
tau2.0.objective(tau2.0, info.g, score.g)
tau2.0 |
scalar, value for tau2 |
info.g |
observed information for each gene |
score.g |
observed score (first derivative of log-likelihood) for each gene |
scalar, value of objective function at tau2.0
Mark Robinson
y<-matrix(rnbinom(20,size=1,mu=10),nrow=5) x<-list(data=y,group=rep(1:2,each=2),lib.size=rep(1000:1001,each=2)) scores <- condLogLikDerDelta(y, delta=0.5, der = 1, doSum = TRUE) qA <- quantileAdjust(x, alpha = 10, null.hypothesis = TRUE) exp.inf <- approx.expected.info(x, d=0.5, qA) sigma2.0.est <- optimize(tau2.0.objective, c(0, 500), info.g = exp.inf, score.g = scores)$min