aic: Model selection for Gaussian mixture models
In PrInCE: Predicting Interactomes from Co-Elution
Description
Usage
Arguments
Value
Description
Calculate the AIC, corrected AIC, or BIC for a curve fit with a Gaussian
mixture model by nonlinear least squares optimization. This function
permits the calculation of the AIC/AICc/BIC after rejecting some Gaussians
in the model, for example because their centres are outside the bounds of
the profile.
Usage
1
2
3
4
5
gaussian_aic(coefs, chromatogram)
gaussian_aicc(coefs, chromatogram)
gaussian_bic(coefs, chromatogram)
Arguments
coefs
the coefficients of the Gaussian mixture model, output by
fit_gaussians
chromatogram
the raw elution profile
Value
the AIC, corrected AIC, or BIC of the fit model
PrInCE documentation built on Nov. 8, 2020, 6:34 p.m.
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Description Usage Arguments Value
Description
Calculate the AIC, corrected AIC, or BIC for a curve fit with a Gaussian mixture model by nonlinear least squares optimization. This function permits the calculation of the AIC/AICc/BIC after rejecting some Gaussians in the model, for example because their centres are outside the bounds of the profile.
Usage
1 2 3 4 5 | gaussian_aic(coefs, chromatogram)
gaussian_aicc(coefs, chromatogram)
gaussian_bic(coefs, chromatogram)
|
Arguments
coefs |
the coefficients of the Gaussian mixture model, output by
|
chromatogram |
the raw elution profile |
Value
the AIC, corrected AIC, or BIC of the fit model
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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