omega_samp: Sample precision matrix
In bpnreg: Bayesian Projected Normal Regression Models for Circular Data
Description
Sample precision matrix
Usage
1
omega_samp(b, B, v, q, N)
Arguments
b
subject specific random effects vectors
B
prior sum of squares matrix, scale parameter Wishart distribution
(of b=random effect if prior close to 0–>no random effect)
v
prior df=dimension Z
q
dimension Z(number of random effects)
N
sample size at second level
bpnreg documentation built on Aug. 6, 2021, 9:07 a.m.
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Description
Sample precision matrix
Usage
1 | omega_samp(b, B, v, q, N)
|
Arguments
b |
subject specific random effects vectors |
B |
prior sum of squares matrix, scale parameter Wishart distribution (of b=random effect if prior close to 0–>no random effect) |
v |
prior df=dimension Z |
q |
dimension Z(number of random effects) |
N |
sample size at second level |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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