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Main function of the ICMg algorithm. ICMg.combined.sampler computes samples from the posterior of the assignments of datapoints (interactions and expression profiles) to latent components. From these we can then obtain component membership distributions and clusterings for genes.
● Data Source:
BioConductor
● Keywords: methods
● Alias: ICMg.combined.sampler
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Function for computing the component memberships for each data point from the MCMC samples.
● Data Source:
BioConductor
● Keywords: methods
● Alias: ICMg.get.comp.memberships
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ICMg.links.sampler computes samples from the posterior of the assignments of datapoints (interactions) to latent components. From these we can then obtain component membership distributions and clusterings for genes.
● Data Source:
BioConductor
● Keywords: methods
● Alias: ICMg.links.sampler
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A NetResponse model.
● Data Source:
BioConductor
● Keywords: classes
● Alias: NetResponseModel-class, [[,NetResponseModel-method, show,NetResponseModel-method
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P.S
(Package: netresponse) :
Description: Probabiity density for sample
Arguments: @param dat features x samples data matrix for mixture modeling @param pars Gaussian mixture model parameters (diagonal covariances); list with elements mu (mean vectors), sd (covariance diagonals), w (weights). The mu and sd are component x features matrices, w is vector giving weight for each component. @param log Logical. Return densities in log domain.
● Data Source:
BioConductor
● Keywords: internal, utilities
● Alias: P.S
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P.Sr
(Package: netresponse) :
Description: Probabiity density for sample group given mode
Arguments: @param dat features x samples data matrix for mixture modeling @param pars Gaussian mixture model parameters (diagonal covariances); list with elements mu (mean vectors), sd (covariance diagonals), w (weights). The mu and sd are component x features matrices, w is vector giving weight for each component. @param log Logical. Return densities in log domain.
● Data Source:
BioConductor
● Keywords: internal, utilities
● Alias: P.Sr
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P.r.s
(Package: netresponse) :
Description: Probabiity of mode given a sample (a data vector)
Arguments: @param dat features x samples data matrix for mixture modeling @param pars Gaussian mixture model parameters (diagonal covariances); list with elements mu (mean vectors), sd (covariance diagonals), w (weights). The mu and sd are component x features matrices, w is vector giving weight for each component. @param log Logical. Return densities in log domain. @param scaling Try to avoid floating errors. To be improved later.
● Data Source:
BioConductor
● Keywords: internal, utilities
● Alias: P.r.s
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P.rS
(Package: netresponse) :
Description: Probabiity of mode given multiple samples (ie. data matrix)
Arguments: @param dat features x samples data matrix for mixture modeling @param pars Gaussian mixture model parameters (diagonal covariances); list with elements mu (mean vectors), sd (covariance diagonals), w (weights). The mu and sd are component x features matrices, w is vector giving weight for each component. @param log Logical. Return densities in log domain.
● Data Source:
BioConductor
● Keywords: internal, utilities
● Alias: P.rS
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P.rs.joint
(Package: netresponse) :
Description: Joint probabiity density for mode and sample group
Arguments: @param dat features x samples data matrix for mixture modeling @param pars Gaussian mixture model parameters (diagonal covariances); list with elements mu (mean vectors), sd (covariance diagonals), w (weights). The mu and sd are component x features matrices, w is vector giving weight for each component. @param log Logical. Return densities in log domain.
● Data Source:
BioConductor
● Keywords: internal, utilities
● Alias: P.rs.joint
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P.rs.joint.individual
(Package: netresponse) :
Description: Joint probabiity density for mode and sample
Arguments: @param dat features x samples data matrix for mixture modeling @param pars Gaussian mixture model parameters (diagonal covariances); list with elements mu (mean vectors), sd (covariance diagonals), w (weights). The mu and sd are component x features matrices, w is vector giving weight for each component. @param log Logical. Return densities in log domain.
● Data Source:
BioConductor
● Keywords: internal, utilities
● Alias: P.rs.joint.individual
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providing 
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