dfWishart function

This uses simulations to match the rse

dfWishart(omega, n, rse, upper, totN = 1000, diag = TRUE, seed = 1234)

Arguments

• omega: represents the matrix for simulation
• n: This represents the number of subjects/samples this comes from (used to calculate rse). When present it assumes the rse= sqrt(2)/sqrt(n)
• rse: This is the rse that we try to match, if not specified, it is derived from n
• upper: The upper boundary for root finding in terms of degrees of freedom. If not specified, it is n*200
• totN: This represents the total number of simulated inverse wishart deviates
• diag: When TRUE, represents the rse to match is the diagonals, otherwise it is the total matrix.
• seed: to make the simulation reproducible, this represents the seed that is used for simulating the inverse Wishart distribution

Returns

output from uniroot() to find the right estimate

Examples

dfWishart(lotri::lotri(a+b~c(1, 0.5, 1)), 100)

Author(s)

Matthew L. Fidler