dpgmm_init: Run MCMC for DPGMMM model, utilizing pilot chain
In emittman/dpOMP: Parallelized Gibbs Sampler for DPGMM Model
Description
Run MCMC for DPGMMM model, utilizing pilot chain
Usage
1
dpgmm_init(data, design, lambda2, alpha, G, V, K, N, iter, init_iter)
Arguments
data
A column-major $G \cdot VN$ gene expressionvector/matrix
design
A column-major $V \cdot V$ experimental design vector/matrix
lambda2
prior variance for base measure
alpha
DP concentration parameter
G
number of genes
V
number of varieties/groups
K
maximum number of clusters
N
samples per variety/group
iter
number of iterations for main chain
init_iter
number of iterations for pilot chain
emittman/dpOMP documentation built on May 16, 2019, 5:09 a.m.
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Description
Run MCMC for DPGMMM model, utilizing pilot chain
Usage
1 | dpgmm_init(data, design, lambda2, alpha, G, V, K, N, iter, init_iter)
|
Arguments
data |
A column-major $G \cdot VN$ gene expressionvector/matrix |
design |
A column-major $V \cdot V$ experimental design vector/matrix |
lambda2 |
prior variance for base measure |
alpha |
DP concentration parameter |
G |
number of genes |
V |
number of varieties/groups |
K |
maximum number of clusters |
N |
samples per variety/group |
iter |
number of iterations for main chain |
init_iter |
number of iterations for pilot chain |
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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