Man pages for sgdGMF
Estimation of Generalized Matrix Factorization Models via Stochastic Gradient Descent
| biplot.initgmf | Biplot of an initialized GMF model |
| biplot.sgdgmf | Biplot of a GMF model |
| coefficients.initgmf | Extract the coefficient of an initialized GMF model |
| coefficients.sgdgmf | Extract the coefficient of a GMF model |
| cpp.airwls.glmfit | Fisher scoring algorithm for GLMs |
| cpp.airwls.glmstep | Compute one Fisher scoring step for GLMs |
| cpp.airwls.update | AIRWLS update for GMF models |
| cpp.fit.airwls | Fit a GMF model using the AIRWLS algorithm |
| cpp.fit.block.sgd | Fit a GMF model using the adaptive SGD with block-wise... |
| cpp.fit.coord.sgd | Fit a GMF model using the adaptive SGD with coordinate-wise... |
| cpp.fit.newton | Fit a GMF model using the diagonal quasi-Newton algorithm |
| cpp.fit.random.block.sgd | Fit a GMF model using the adaptive SGD with block-wise... |
| deviance.initgmf | Compute deviance, AIC and BIC of an initialized GMF model |
| deviance.sgdgmf | Compute deviance, AIC and BIC of a GMF model |
| eigengap.act | Rank selection via adjust correlation thresholding |
| eigengap.oht | Rank selection via optimal hard thresholding |
| eigengap.onatski | Rank selection via the Onatski method |
| 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 |
| make.pos.diag | Fix sign ambiguity of eigen-vectors |
| matrix.deviance | Model deviance of a GMF model |
| matrix.penalty | Frobenius penalty for the parameters of a GMF model |
| normalize.uv | Normalize the matrices U and V |
| norm.procrustes | Procrustes distance |
| ols.fit.coef | Estimate the coefficients of a multivariate linear model |
| omp.check | Check if OpenMP is enabled |
| partition | Split the data matrix in train and test sets |
| plot.initgmf | Plot diagnostics for an initialized GMF model |
| plot.sgdgmf | Plot diagnostics for a GMF model |
| pointwise.deviance | Pointwise deviance of 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 |
| procrustes | Procrustes rotation of two configurations |
| reexports | Objects exported from other packages |
| refit.sgdgmf | Refine the final estimate 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... |
| set.control.block.sgd | Check and set the control parameters for the blockwise-SGD... |
| set.control.coord.sgd | Check and set the control parameters for the coordinate-SGD... |
| 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 |
| set.family | Check and set the model family |
| set.mat.offset | Check and set the offset matrix |
| set.mat.weights | Check and set the weighting matrix |
| set.mat.X | Check and set the covariate matrix X |
| set.mat.Y | Check and set the response matrix Y |
| set.mat.Z | Check and set the covariate matrix X |
| set.penalty | Check and set the penalty parameters |
| sgdgmf.cv | Model selection via cross-validation for generalized matrix... |
| sgdgmf.cv.step | Single step of cross-validation for generalized matrix... |
| sgdgmf.fit | Factorize a matrix of non-Gaussian observations using GMF |
| sgdgmf.init | Initialize the parameters of a generalized matrix... |
| sgdGMF-package | sgdGMF: Estimation of Generalized Matrix Factorization Models... |
| 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 |
| vglm.fit.coef | Estimate the coefficients of a vector generalized linear... |
| whitening.matrix | Compute the whitening matrix from a given covariance matrix |
