| delayed_initialization | Initialize the parameters of a Negative Binomial regression... |
| delayed_optimization | Optimize the parameters of a Negative Binomial regression... |
| initialization | Initialize the parameters of a Negative Binomial regression... |
| nb.loglik.matrix | Log-likelihood of the negative binomial model for each entry... |
| newAIC | Compute the AIC of a model given some data |
| newAlpha | Returns the matrix of paramters alpha |
| newBeta | Returns the matrix of paramters beta |
| newBIC | Compute the BIC of a model given some data |
| newEpsilon_alpha | Returns the vector of regularization parameter for alpha |
| newEpsilon_beta | Returns the vector of regularization parameter for beta |
| newEpsilon_gamma | Returns the vector of regularization parameter for gamma |
| newEpsilon_W | Returns the vector of regularization parameter for W |
| newEpsilon_zeta | Returns the regularization parameter for the dispersion... |
| newFit | Fit a nb regression model |
| newGamma | Returns the matrix of paramters gamma |
| newloglik | Compute the log-likelihood of a model given some data |
| newLogMu | Returns the matrix of logarithm of mean parameters |
| newmodel | Initialize an object of class newmodel |
| newmodel-class | Class newmodel |
| newMu | Returns the matrix of mean parameters |
| newpenalty | Compute the penalty of a model |
| newPhi | Returns the vector of dispersion parameters |
| newSim | Simulate counts from a negative binomial model |
| newTheta | Returns the vector of inverse dispersion parameters |
| newV | Returns the gene-level design matrix for mu |
| newW | Returns the low-dimensional matrix of inferred sample-level... |
| newWave | Perform dimensionality reduction using a nb regression model... |
| newX | Returns the sample-level design matrix for mu |
| newZeta | Returns the vector of log of inverse dispersion parameters |
| numberFactors | Generic function that returns the number of latent factors |
| numberFeatures | Generic function that returns the number of features |
| numberParams | Generic function that returns the total number of parameters... |
| numberSamples | Generic function that returns the number of samples |
| optimization | Optimize the parameters of a Negative Binomial regression... |
| setup | Setup the parameters of a Negative Binomial regression model... |
