MC.ZT.statistics function

Size and Power of Goodness of Fit Test: Multinomial vs. Dirichlet-Multinomial

This Monte-Carlo simulation procedure provides the power and size of the Multinomial vs. Dirichlet-Multinomial goodness of fit test, using the C($\alpha$)-optimal test statistics of Kim and Margolin (1992) (t statistics) and the C($\alpha$)-optimal test statistics of (Paul et al., 1989).

MC.ZT.statistics(Nrs, numMC = 10, fit, type = "ha", siglev = 0.05)

Arguments

• Nrs: A vector specifying the number of reads/sequence depth for each sample.

• numMC: Number of Monte-Carlo experiments. In practice this should be at least 1,000.

• fit: A list (in the format of the output of dirmult function) containing the data parameters for evaluating either the size or power of the test.

• type: If "hnull": Computes the size of the test.

  If "ha": Computes the power of the test. (default)

• siglev: Significance level for size of the test / power calculation. The default is 0.05.

Returns

A vector containing both the size of the test statistics (under "hnull") or power (under "ha") of the test for both the z and t statistics.

Details

Note: Though the test statistic supports an unequal number of reads across samples, the performance has not yet been fully tested.

Examples

data(saliva) 
        
        ### Get a list of dirichlet-multinomial parameters for the data
        fit.saliva <- DM.MoM(saliva) 
        
        ### Set up the number of Monte-Carlo experiments
        ### We use 1 for speed, should be at least 1,000
        numMC <- 1
        
        ### Generate the number of reads per sample
        ### The first number is the number of reads and the second is the number of subjects
        nrs <- rep(15000, 25)
        
        ### Computing size of the test statistics (Type I error)
        pval1 <- MC.ZT.statistics(nrs, numMC, fit.saliva, "hnull") 
        pval1
        
        ### Computing Power of the test statistics (Type II error)
        pval2 <- MC.ZT.statistics(nrs, numMC, fit.saliva)
        pval2