scalaglm
Type members
Classlikes
Generalised linear regression modelling
Generalised linear regression modelling
- Value Params
- Xmat
Covariate matrix
- addIntercept
Add an intercept term to the covariate matrix?
- colNames
List of covariate names
- fam
Observation model. eg. LogisticGlm or PoissonGlm
- its
Max iterations for the IRLS algorithm (default 50)
- y
Vector of responses
- Returns
An object of type Glm with many useful methods providing information about the regression fit, including .coefficients, .p and .summary
- Companion
- object
Trait for simple one-parameter exponential family observation models.
Trait for simple one-parameter exponential family observation models.
Linear regression modelling
Linear regression modelling
- Value Params
- Xmat
Covariate matrix
- addIntercept
Add an intercept term to the covariate matrix?
- colNames
List of covariate names
- y
Vector of responses
- Returns
An object of type Lm with many useful attributes providing information about the regression fit
- Companion
- object
Principal components analysis
Principal components analysis
Computed using SVD of the centred data matrix rather than from the spectral decomposition of the covariance matrix. eg. More like the R function "prcomp" than the R function "princomp".
NOTE: .loadings are transposed relative to the PCA function in Breeze
- Value Params
- colNames
Sequence of column names of mat
- mat
Data matrix with rows corresponding to observations and columns corresponding to variables
- Returns
An object of type Pca with methods such as .loadings, .scores, .sdev and .summary
- Companion
- object
Prediction from a fitted linear (Glm) model
Prediction from a fitted linear (Glm) model
- Value Params
- mod
fitted generalised linear model
- newX
covariate matrix for predictions
- response
predictions on the response scale?
- Returns
An object of type PredictGlm with several useful attributes, including .fitted and .se