The maximum number of cycles of the numeric
procedure to find the estimator. (Default = 1000).
eta
The weight of the exponential prior. The
higher eta, the lower the estimate for the size
parameter. Setting eta = 0 means that the prior is
not used and, therefore, the maximum-likelihood estimator
is calculated. (Default = 0).
rmax
Upper bound on the size parameter. This
corresponds to a truncated exponential prior. If not used
there is a non-zero probability that the estimator for
the size parameter is ∞. (Default = Inf).
This can either be "bisection" or "regula falsi".
(Default="bisection").
Details
Depending on the parameters you can either obtain the
Maximum-likelihood estimator or the
maximum-a-posteriori estimator using an
exponential prior.
maximum-likelihood estimator
eta
= 0
maximum-a-posteriori estimator
eta > 0
By setting the variable rmax to a positive value
one can enforce an upper bound on the parameter.
The inverse of the size parameter is the overdispersion
parameter.
Value
"numeric" An estimate of the size parameter of the
negative binomial distribution. The overdispersion
parameter is the inverse of the size parameter of a
negative binomial distribution
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(dexus)
Loading required package: BiocGenerics
Loading required package: parallel
Attaching package: 'BiocGenerics'
The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLB
The following objects are masked from 'package:stats':
IQR, mad, xtabs
The following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
rbind, rownames, sapply, setdiff, sort, table, tapply, union,
unique, unsplit
Attaching package: 'dexus'
The following object is masked from 'package:BiocGenerics':
sizeFactors
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/dexus/getSizeNB.Rd_%03d_medium.png", width=480, height=480)
> ### Name: getSizeNB
> ### Title: Maximum-likelihood and maximum-a-posteriori estimators for the
> ### negative binomial distribution.
> ### Aliases: getSizeNB
>
> ### ** Examples
>
> x <- rnbinom(mu=50, size=5, n=10)
> getSizeNB(x)
[1] 11.01103
>
>
>
>
>
> dev.off()
null device
1
>