negbin.pow: Estimates power for given sample size using simulation from...
In RSPS: RNA-Seq Power Simulation

Description Usage Arguments Details Value Note Author(s) References See Also Examples

View source: R/negbin.pow.R

The function provides estimate of power for given sample size when there is over-dispersion. The data is simulated from Negative Binomial distribution.

1	negbin.pow(n, lambda1, k, disp, alpha, seed, numsim, monitor, sig)

`n`	A vector of positive integers representing the sample size
`lambda1`	Mean count under the null distribution. It can be a vector.
`k`	Fold change desired under the alternative distribution. It can be a vector.
`disp`	The over-dispersion parameter. 1 represent no pver-dispersion and values above one represent over-dispersion.
`alpha`	Type I error rate: a value between 0 and 1. It can be a vector.
`seed`	Value of seed to ensure reproducibility of results.
`numsim`	Number of simulations. 1000 is recommended.
`monitor`	If TRUE, it allows us to view the progress of the function.
`sig`	Number of significant digits after decimal.

The test statistic used is the scaled difference. Please contact the authors for more details on algorithm.

`Mean.Null`	Mean Count under Null distribution.
`Effect.Size`	Fold Change Under the alternate hypothesis.
`Disp.Par`	Over-dispersion parameter.
`Power`	Estimated Power.
`Std.Err`	Standard Error.

The alternative ecological parameterization is used for Negative binomial distribution.

Milan Bimali

None

rnbinom

power.negbin <- negbin.pow(n=c(5,10),lambda1=c(3,5),
k=c(2,3),disp=2,alpha=0.001,seed = 20,
numsim=100,monitor=TRUE)
power.plot(power.negbin)
# Another example (takes longer to run)
#power.negbin <- negbin.pow(n=c(3,5,10,15),lambda1=c(3,5),
#k=c(2,2.5,3),disp=2,alpha=0.001,seed = 20,
#numsim=1000,monitor=TRUE)
#head(power.negbin)