pVals | R Documentation |
This is one of the auxiliary functions used to execute the rpdTest function. This function can be used to calculate p-values based on Monte Carlo simulation. Users generally do not need to call this function except for testing purposes. For more detailed description one can find inrpdTest.
pVals(x, p, lambda = 1, B = 200, z = 40, rs = 1250, n.cores, nDim, r)
x |
the obtained multinomial distribution data.Same data structure as the data parameter in rpdTest. |
p |
the probability vector in the null hypothesis. It is necessary to ensure beforehand that the vectors are valid. |
lambda |
a control parameter of the statistic calculation, adjusting it will significantly change the final obtained statistic. |
B |
an integer specifying the number of simulation data on the expected null distribution (p) of the Monte Carlo simulation. |
z |
an integer specifying the number by which to divide the observation data group in a Monte Carlo simulation. |
rs |
an integer that adjusts the number of statistics calculated in simulation. |
n.cores |
an integer used to specify the number of cores used to perform parallel operations. The default is to use the maximum number of cores available to the computer minus one. |
nDim |
an integer indicating the dimension of the uniformly distributed vectors generated during the computation of the statistic. It is equal to the number of experiments for the multinomial distribution. |
r |
an integer indicating the dimension of the data parameter. It is equal to the number of possible outcomes of the multinomial distribution. |
an numeric value indicating simulated p-value.
d <- c(20,40)
#The next line is equivalent to rpdTest(d,sim.pValue = TRUE,n.cores = 2)$p.value
#It usually takes 1-2 minutes to perform this calculation process
pVals(d, c(1/2,1/2), B = 200, z = 40, rs = 1250, n.cores = 2, nDim = sum(d), r = length(d))
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