simulate {shiftR} | R Documentation |
These functions generate two artificial data sets with local dependence of observations.
simulateNumeric(n, corWithin, corAcross = 0) simulateBinary(n, corWithin, corAcross = 0)
n |
Total number of elements in each data set. |
corWithin |
Correlation of adjacent observations within each data set. |
corAcross |
Correlation of observations across data sets. |
Returns the Cramer's V coefficient.
The simulateNumeric
function generates two data sets with elements
having standard normal distribution.
The simulateBinary
function generates data sets with 0/1 values
by thresholding the numeric data sets from simulateNumeric
.
The simulatePValues
function generates data sets of p-values
by applying pnorm
to the data sets
from simulateNumeric
.
Andrey A Shabalin andrey.shabalin@gmail.com
n = 100000 sim = simulateNumeric(n, 0.5, 0.3) # Means should be close to 0 (zero) mean(sim$data1) mean(sim$data2) # Variances should be close to 1 var(sim$data1) var(sim$data2) # Correlation of adjacent observations # should be close to 0.5 cor(sim$data1[-1], sim$data1[-n]) cor(sim$data2[-1], sim$data2[-n]) # Correlation between data sets # should be close to 0.3 cor(sim$data1, sim$data2)