inv.rho.transform
(Package: GMCM) :
Transformation of the correlation to real line and its inverse
A transformation of the correlation coefficient into the real line and the corresponding inverse. The transform is a translation and scaling of rho from the interval (-1/(d-1), 1) to (0, 1) followed by a logit transformation to the whole real line.
● Data Source:
CranContrib
● Keywords: internal
● Alias: inv.rho.transform, rho.transform
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full2meta
(Package: GMCM) :
Convert between parameter formats
These functions converts the parameters between the general Gaussian mixture (copula) model and the special GMCM. Most functions of the GMCM packages use the theta format described in rtheta.
● Data Source:
CranContrib
● Keywords:
● Alias: full2meta, meta2full
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dgmcm.loglik
(Package: GMCM) :
Probability, density, and likelihood functions of the Gaussian mixture
Marginal and simultaneous cumulative distribution, log probability density, and log-likelihood functions of the Gaussian mixture model (GMM) and Gaussian mixture copula model (GMCM) and the relevant inverse marginal quantile functions.
● Data Source:
CranContrib
● Keywords: internal
● Alias: dgmcm.loglik, dgmm.loglik, dgmm.loglik.marginal, pgmm.marginal, qgmm.marginal
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GMCM-package
(Package: GMCM) :
Fast optimization of Gaussian Mixture Copula Models
Gaussian mixture copula models (GMCM) can be used for unsupervised clustering and meta analysis. In meta analysis, GMCMs can be used to quantify and identify which features which have been reproduce across multiple experiments. This package provides a fast and general implementation of GMCM cluster analysis and serves as an extension of the features available in the idr package.
● Data Source:
CranContrib
● Keywords:
● Alias: GMCM, GMCM-package
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inv.tt
(Package: GMCM) :
Reparametrization of GMCM parameters
These functions map the four GMCM parameters in the model of Li et. al. (2011) and Tewari et. al. (2011) onto the real line and back. The mixture proportion is logit transformed. The mean and standard deviation are log transformed. The correlation is translated and scaled to the interval (0,1) and logit transformed by rho.transform.
● Data Source:
CranContrib
● Keywords: internal
● Alias: inv.tt, tt
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rtheta
(Package: GMCM) :
Get random parameters for the Gaussian mixture (copula) model
Generate a random set parameters for the Gaussian mixture model (GMM) and Gaussian mixture copula model (GMCM). Primarily, it provides an easy prototype of the theta-format used in GMCM.
● Data Source:
CranContrib
● Keywords:
● Alias: rtheta
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colSds
(Package: GMCM) :
Row and column standard deviations
The rowSds and colSds respectively computes the standard deviations of each rows and columns of the given matrix.
● Data Source:
CranContrib
● Keywords: internal
● Alias: colSds, rowSds
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fit.meta.GMCM
(Package: GMCM) :
Reproducibility/meta analysis using GMCMs
This function performs reproducibility (or meta) analysis using GMCMs. It features various optimization routines to identify the maximum likelihood estimate of the special Gaussian mixture copula model proposed by Li et. al. (2011).
● Data Source:
CranContrib
● Keywords:
● Alias: fit.meta.GMCM
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1 images
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EMAlgorithm
(Package: GMCM) :
EM algorithm for Gaussian mixture models
The regular expectation-maximization algorithm for general multivariate Gaussian mixture models.
● Data Source:
CranContrib
● Keywords:
● Alias: EMAlgorithm
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1 images
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cummean
(Package: GMCM) :
Cumulative mean values
Returns a vector whose i'th element is the cumulative mean (arithmetic mean) of the i'th first elements of the argument.
● Data Source:
CranContrib
● Keywords: internal
● Alias: cummean
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