mlpY: Network (positive) log-likelihood
In BLSM: Bayesian Latent Space Model
Description
Usage
Arguments
Value
Description
Compute the (positive) log-likelihood of the whole observed network based on the
latent positions estimates and the model assumptions. The inputs are slightly different from those of lpY,
so the function basically applies some preprocessing before calling lpY and returning its value with the opposite sign.
Usage
1
mlpY(avZ, Y, W)
Arguments
avZ
Vector containing the α value and the latent positions
Y
Adjacency matrix of the observed network
W
BLSM Weights matrix of the observed network
Value
Log-likelihood of the observed network
BLSM documentation built on May 2, 2019, 2:45 p.m.
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Description Usage Arguments Value
Description
Compute the (positive) log-likelihood of the whole observed network based on the latent positions estimates and the model assumptions. The inputs are slightly different from those of lpY, so the function basically applies some preprocessing before calling lpY and returning its value with the opposite sign.
Usage
1 | mlpY(avZ, Y, W)
|
Arguments
avZ |
Vector containing the α value and the latent positions |
Y |
Adjacency matrix of the observed network |
W |
BLSM Weights matrix of the observed network |
Value
Log-likelihood of the observed network
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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