# Estimation of Generalized Matrix Factorization Models via Stochastic Gradient Descent

## Documentation for package ‘sgdGMF’ version 1.0.1

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

AIC.initgmf | Compute deviance, AIC and BIC of an initialized GMF model
AIC.sgdgmf | Compute deviance, AIC and BIC of a GMF model
BIC.initgmf | Compute deviance, AIC and BIC of an initialized GMF model
BIC.sgdgmf | Compute deviance, AIC and BIC of a GMF model
biplot.initgmf | Biplot of an initialized GMF model
biplot.sgdgmf | Biplot of a GMF model
coef.initgmf | Extract the coefficient of an initialized GMF model
coef.sgdgmf | Extract the coefficient of a GMF model
coefficients.initgmf | Extract the coefficient of an initialized GMF model
coefficients.sgdgmf | Extract the coefficient of a GMF model
deviance.initgmf | Compute deviance, AIC and BIC of an initialized GMF model
deviance.sgdgmf | Compute deviance, AIC and BIC of a GMF model
fitted.initgmf | Extract the fitted values of an initialized GMF model
fitted.sgdgmf | Extract the fitted values of a GMF models
image.initgmf | Heatmap of an initialized GMF model
image.sgdgmf | Heatmap of a GMF model
plot.initgmf | Plot diagnostics for an initialized GMF model
plot.sgdgmf | Plot diagnostics for a GMF model
predict.sgdgmf | Predict method for GMF models
print.initgmf | Print the fundamental characteristics of an initialized GMF
print.sgdgmf | Print the fundamental characteristics of a GMF
refit.sgdgmf | Refine the final estimate of a GMF model
resid.initgmf | Extract the residuals of an initialized GMF model
resid.sgdgmf | Extract the residuals of a GMF model
residuals.initgmf | Extract the residuals of an initialized GMF model
residuals.sgdgmf | Extract the residuals of a GMF model
screeplot.initgmf | Screeplot for the residuals of an initialized GMF model
screeplot.sgdgmf | Screeplot for the residuals of a GMF model
set.control.airwls | Check and set the control parameters for the AIRWLS algorithm
set.control.alg | Check and set the control parameters for the select optimization algorithm
set.control.block.sgd | Check and set the control parameters for the blockwise-SGD algorithm
set.control.coord.sgd | Check and set the control parameters for the coordinate-SGD algorithm
set.control.cv | Check and set the cross-validation parameters
set.control.init | Check and set the initialization parameters for a GMF model
set.control.newton | Check and set the control parameters for the Newton algorithm
sgdgmf.cv | Model selection via cross-validation for generalized matrix factorization models
sgdgmf.fit | Factorize a matrix of non-Gaussian observations using GMF
sgdgmf.rank | Rank selection via eigenvalue-gap methods
sim.gmf.data | Simulate non-Gaussian data from a GMF model
simulate | Simulate new data
simulate.sgdgmf | Simulate method for GMF models