multivariance.timing {multivariance} | R Documentation |
Estimates the computation time. This is relative rough. First run with determine.parameters = TRUE
(which takes a while). Then use the computed parameters to determine the computation time/or sample size.
multivariance.timing(N = NULL, n, sectime = NULL, coef.cdm = 15.2, coef.prod = 2.1, coef.sum = 1.05, determine.parameters = FALSE)
N |
number of samples. If |
n |
number of variables |
sectime |
desired computation time in seconds. If |
coef.cdm |
computation time parameter for the centered distance matrices |
coef.prod |
computation time parameter for matrix products |
coef.sum |
computation time parameter for matrix sums |
determine.parameters |
if |
When detecting the parameters, the median of the computation times is used.
Ns = (1:100)*10 ns = 1:100 fulltime = outer(Ns,ns,FUN = function(N,n) multivariance.timing(N,n)) contour(Ns,ns,fulltime,xlab = "N",ylab = "n", main = "computation time of multivariance in secs", sub = "using default parameters - use 'determine.parameters = TRUE' to compute machine specific values") # Run to determine the parameters of your system: # multivariance.timing(determine.parameters = TRUE)