mixture.model {netresponse} | R Documentation

## Mixture model

### Description

Fit Gaussian mixture model

### Usage

    mixture.model(
      x,
      mixture.method = "vdp",
      max.responses = 10,
      implicit.noise = 0,
      prior.alpha = 1,
      prior.alphaKsi = 0.01,
      prior.betaKsi = 0.01,
      vdp.threshold = 1e-05,
      initial.responses = 1,
      ite = Inf,
      speedup = TRUE,
      bic.threshold = 0,
      pca.basis = FALSE,
      min.responses = 1,
      ...
    )

### Arguments

`x` | data matrix (samples x features, for multivariate analysis) or a vector (for univariate analysis)
`mixture.method` | Specify the approach to use in mixture modeling. Options. vdp (nonparametric Variational Dirichlet process mixture model); bic (based on Gaussian mixture modeling with EM, using BIC to select the optimal number of components)
`max.responses` | Maximum number of responses for each subnetwork. Can be used to limit the potential number of network states.
`implicit.noise` | Implicit noise parameter. Add implicit noise to vdp mixture model. Can help to avoid overfitting to local optima, if this appears to be a problem.
`prior.alpha, prior.alphaKsi, prior.betaKsi` | Prior parameters for Gaussian mixture model that is calculated for each subnetwork (normal-inverse-Gamma prior). alpha tunes the mean; alphaKsi and betaKsi are the shape and scale parameters of the inverse Gamma function, respectively.
`vdp.threshold` | Minimal free energy improvement after which the variational Gaussian mixture algorithm is deemed converged.
`initial.responses` | Initial number of components for each subnetwork model. Used to initialize calculations.
`ite` | Maximum number of iterations on posterior update (updatePosterior). Increasing this can potentially lead to more accurate results, but computation may take longer.
`speedup` | Takes advantage of approximations to PCA, mutual information etc in various places to speed up calculations. Particularly useful with large and densely connected networks and/or large sample size.
`bic.threshold` | BIC threshold which needs to be exceeded before a new mode is added to the mixture with mixture.method = "bic"
`pca.basis` | pca.basis
`min.responses` | minimum number of responses
`...` | Further optional arguments to be passed.

### Value

List with two elements: model: fitted mixture model (parameters and free energy); model.params: model parameters

### Author(s)

Contact: Leo Lahti leo.lahti@iki.fi

### References

See citation("netresponse")

### Examples

    res <- mixture.model(NULL)

[Package netresponse version 1.50.0 Index]