ExpRegression

scalation.modeling.ExpRegression
See theExpRegression companion class
object ExpRegression

The ExpRegression companion object provides factory methods for creating exponential regression models.

Attributes

Companion
class
Graph
Supertypes
class Object
trait Matchable
class Any
Self type

Members list

Value members

Concrete methods

def apply(xy: MatrixD, fname: Array[String], hparam: HyperParameter, nonneg: Boolean)(col: Int): ExpRegression

Create an ExpRegression object from a combined data-response matrix. The last column is assumed to be the response column.

Create an ExpRegression object from a combined data-response matrix. The last column is assumed to be the response column.

Value parameters

col

the designated response column (defaults to the last column)

fname

the feature/variable names (defaults to null)

hparam

the hyper-parameters (currently nome)

nonneg

whether to check that responses are nonnegative (defaults to true)

xy

the combined data-response matrix (predictors and response)

Attributes

def rescale(x: MatrixD, y: VectorD, fname: Array[String], hparam: HyperParameter, nonneg: Boolean): ExpRegression

Create an ExpRegression object from a data matrix and a response vector. This method provides data rescaling.

Create an ExpRegression object from a data matrix and a response vector. This method provides data rescaling.

Value parameters

fname

the feature/variable names (defaults to null)

hparam

the hyper-parameters (currently none)

nonneg

whether to check that responses are nonnegative (defaults to true)

x

the data/input m-by-n matrix (augment with a first column of ones to include intercept in model)

y

the response/output m-vector

Attributes