posteriorDiscard.CatHDP2 {bbricks} | R Documentation |
For the model structure:
G |eta \sim DP(eta,U)
G_m|gamma \sim DP(gamma,G), m = 1:M
pi_{mj}|G_m,alpha \sim DP(alpha,G_m), j = 1:J_m
z|pi_{mj} \sim Categorical(pi_{mj})
k|z,G_m \sim Categorical(G_m), \textrm{ if z is a sample from the base measure }G_m
u|k,G \sim Categorical(G), \textrm{ if k is a sample from the base measure G}
where DP(eta,U) is a Dirichlet Process on positive integers, eta is the "concentration parameter", U is the "base measure" of this Dirichlet process, U is an uniform distribution on all positive integers. DP(gamma,G) is a Dirichlet Process on integers with concentration parameter gamma and base measure G. DP(alpha,G_m) is a Dirichlet Process on integers with concentration parameter alpha and base measure G_m. Categorical() is the Categorical distribution. See dCategorical
for the definition of the Categorical distribution.
In the case of CatHDP2, u, z and k can only be positive integers.
Contrary to posterior(), this function will update the prior knowledge by removing the information of observed samples u, z and k. The model structure and prior parameters are stored in a "CatDP" object, the prior parameters in this object will be updated after running this function.
## S3 method for class 'CatHDP2' posteriorDiscard(obj, ss1, ss2, ss3, m, j, w = NULL, ...)
obj |
A "CatHDP2" object. |
ss1 |
Sufficient statistics of u. In CatHDP2 case the sufficient statistic of sample u is u itself(if u is a integer vector with all positive values). |
ss2 |
Sufficient statistics of k. In CatHDP2 case the sufficient statistic of sample k is k itself(if k is a integer vector with all positive values). |
ss3 |
Sufficient statistics of z. In CatHDP2 case the sufficient statistic of sample z is z itself(if z is a integer vector with all positive values). |
m |
integer, group label. |
j |
integer, subgroup label. |
w |
Sample weights, default NULL. |
... |
Additional arguments to be passed to other inherited types. |
None. the model stored in "obj" will be updated based on "ss1" and "ss2".
Teh, Yee W., et al. "Sharing clusters among related groups: Hierarchical Dirichlet processes." Advances in neural information processing systems. 2005.
CatHDP2
,posteriorDiscard.CatHDP2