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This uses simulations to match the rse
dfWishart(omega, n, rse, upper, totN = 1000, diag = TRUE, seed = 1234)
output from uniroot() to find the right estimate
uniroot()
represents the matrix for simulation
This represents the number of subjects/samples this comes from (used to calculate rse). When present it assumes the rse= sqrt(2)/sqrt(n)
This is the rse that we try to match, if not specified, it is derived from n
n
The upper boundary for root finding in terms of degrees of freedom. If not specified, it is n*200
This represents the total number of simulated inverse wishart deviates
When TRUE, represents the rse to match is the diagonals, otherwise it is the total matrix.
TRUE
to make the simulation reproducible, this represents the seed that is used for simulating the inverse Wishart distribution
Matthew L. Fidler
dfWishart(lotri::lotri(a+b~c(1, 0.5, 1)), 100)
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