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

## Description

The function provides estimate of power for given sample size when there is no over-dispersion. The data is simulated from Poisson distribution.

## Usage

 `1` ```poiss.pow(n, lambda1, k, alpha = 0.05, seed = 20, numsim = 2000, monitor = TRUE, sig = 3) ```

## Arguments

 `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. `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.

## Details

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

## Value

 ` Mean.Null ` Mean Count under Null distribution. ` Effect.Size ` Fold Change Under the alternate hypothesis. ` Power ` Estimated Power. ` Std.Err ` Standard Error.

None

Milan Bimali

## References

None

 ```1 2 3 4 5 6 7 8``` ```#-------------------------------------------------- power.poiss <- poiss.pow(n=c(5,10,15),lambda1=c(3),k=c(2,3), alpha=0.001,seed = 20,numsim=100,monitor=TRUE) power.poiss # Another example (takes longer to run) #power.poiss <- poiss.pow(n=c(3,5,10,15),lambda1=c(3),k=c(2,2.5,3), #alpha=0.001,seed = 20,numsim=1000,monitor=TRUE) #power.poiss ```