Random normal-inverted Wishart variate
Simulates a value from a normal-inverted Wishart distribution. This function may be useful for obtaining starting values of the parameters of a multivariate normal distribution for multiple chains of data augmentation.
ninvwish(s, params)
s |
summary list of an incomplete normal data matrix produced by the
function |
params |
list of parameters of a normal-inverted Wishart distribution. In order, the elements of the list are: tau (a scalar), m (a scalar), mu0 (a vector of length ncol(x)), and lambdainv (a matrix of dimension c(ncol(x),ncol(x))). When using this function to create starting values for data augmentation, mu0 and lambdainv should be chosen in relation to the data matrix after the columns have been centered and scaled to have mean zero and variance one. |
a vector in packed storage representing the simulated normal-inverted
Wishart variate. This vector has the same form as parameter vectors
produced by functions such as em.norm and da.norm, and may be
used directly as a starting value for these functions. This vector can
also be put into a more understandable format by getparam.norm.
Before this function may be used, the random number generator seed
must be initialized with rngseed at least once in the current S
session.
See Section 5.4.2 of Schafer (1996).
rngseed, getparam.norm, em.norm and da.norm.
data(mdata) s <- prelim.norm(mdata) #do preliminary manipulations params <- list(1,.5,rep(0,ncol(mdata)), .5*diag(rep(1,ncol(mdata)))) # gives widely dispersed values rngseed(1234567) start <- ninvwish(s,params) # draw a variate thetahat <- em.norm(s,start=start) # run EM from this starting value
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