A dataset consists of three matrices / vectors: covariates,
bases, and variance weights. Both the basis vector and variance
weights are optional.
Public fields
data_ptrExternal pointer to a C++ ForestDataset class
Methods
Method new()
Create a new ForestDataset object.
Usage
ForestDataset$new(covariates, basis = NULL, variance_weights = NULL)
Arguments
covariatesMatrix of covariates
basis(Optional) Matrix of bases used to define a leaf regression
variance_weights(Optional) Vector of observation-specific variance weights
Returns
A new ForestDataset object.
Method update_basis()
Update basis matrix in a dataset
Usage
ForestDataset$update_basis(basis)
Arguments
basisUpdated matrix of bases used to define a leaf regression
Method update_variance_weights()
Update variance_weights in a dataset
Usage
ForestDataset$update_variance_weights(variance_weights, exponentiate = F)
Arguments
variance_weightsUpdated vector of variance weights used to define individual variance / case weights
exponentiateWhether or not input vector should be exponentiated before being written to the Dataset's variance weights. Default: F.
Method num_observations()
Return number of observations in a ForestDataset object
Usage
ForestDataset$num_observations()
Returns
Observation count
Method num_covariates()
Return number of covariates in a ForestDataset object
Usage
ForestDataset$num_covariates()
Method num_basis()
Return number of bases in a ForestDataset object
Usage
ForestDataset$num_basis()
Method get_covariates()
Return covariates as an R matrix
Usage
ForestDataset$get_covariates()
Method get_basis()
Return bases as an R matrix
Usage
ForestDataset$get_basis()
Method get_variance_weights()
Return variance weights as an R vector
Usage
ForestDataset$get_variance_weights()
Returns
Variance weight data
Method has_basis()
Whether or not a dataset has a basis matrix
Usage
ForestDataset$has_basis()
Returns
True if basis matrix is loaded, false otherwise
Method has_variance_weights()
Whether or not a dataset has variance weights
Usage
ForestDataset$has_variance_weights()
Returns
True if variance weights are loaded, false otherwise