sampleSig2b {hbmem} | R Documentation |
Samples posterior of the variance of a normal distibution which has the same additive structure on the mean and the log of variance. Usually used within MCMC loop, but it is broken as of version .1!
sampleSig2b(sample,y,sub,item,lag,I,J,R,nsub,nitem,s2mu,s2a,s2b,met,blockMean,sampLag)
sample |
Previous sample of block variances. |
y |
Vector of data |
sub |
Vector of subject index, starting at zero. |
item |
Vector of item index, starting at zero. |
lag |
Vector of lag index, zero-centered. |
I |
Number of subjects. |
J |
Number of items. |
R |
Total number of trials. |
nsub |
Vector of length (I) containing number of trials per each subject. |
nitem |
Vector of length (J) containing number of trials per each item. |
s2mu |
Prior variance on the grand mean mu; usually set to some large number. |
s2a |
Shape parameter of inverse gamma prior placed on effect variances. |
s2b |
Rate parameter of inverse gamma prior placed on effect variances. Setting both s2a AND s2b to be small (e.g., .01, .01) makes this an uninformative prior. |
met |
Vector of metropolis-hastins tuning parameters. |
blockMean |
Block of parameters for the mean of the distribution. |
sampLag |
Logical. Whether or not to sample the lag effect. |
This function is for a model with an additive structure on the log of the variance of a normal distribuiton. This model is under development, the code is buggy, and it might not even work in the end.
The function returns a new sample of a block of Sigma2 paramters.
Michael S. Pratte
hbmem
#no example yet