update_alpha: sample alpha - hyperparameter for latent state prevalences...
In zhenkewu/rewind: Reconstructing Etiology with Binary Decomposition
Description
Usage
Arguments
Value
Description
This function samples the parameters from a grid (this is used only for model
with pre-specified latent state dimension M);
NB: currently it uses uniform prior or Beta prior for the reparameterized
hyperparameter; check if this is can be replaced by Gamma.
Usage
1
update_alpha(H_star, t, M, a = 1, b = 1, show_density = FALSE)
Arguments
H_star
binary matrix of latent state profiles (row for clusters, column for
latent states)
t
number of clusters
M
latent state dimension
a, b
hyperparameter for Beta distribution over reparameterized alpha.
show_density
show the full conditional density of alpha
given other unknown parameters; FALSE by default.
Value
an updated alpha value (positive)
zhenkewu/rewind documentation built on Sept. 9, 2020, 3:40 p.m.
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Description Usage Arguments Value
Description
This function samples the parameters from a grid (this is used only for model with pre-specified latent state dimension M); NB: currently it uses uniform prior or Beta prior for the reparameterized hyperparameter; check if this is can be replaced by Gamma.
Usage
1 | update_alpha(H_star, t, M, a = 1, b = 1, show_density = FALSE)
|
Arguments
H_star |
binary matrix of latent state profiles (row for clusters, column for latent states) |
t |
number of clusters |
M |
latent state dimension |
a, b |
hyperparameter for Beta distribution over reparameterized alpha. |
show_density |
show the full conditional density of alpha
given other unknown parameters; |
Value
an updated alpha value (positive)
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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