NonlinearRegression

scalation.modeling.NonlinearRegression
See theNonlinearRegression companion class

The NonlinearRegression companion object provides factory methods for buidling Nonlinear 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, f: FunctionP2S, b_init: VectorD, fname: Array[String], hparam: HyperParameter)(col: Int): NonlinearRegression

Create a NonlinearRegression with automatic rescaling from a combined data matrix.

Create a NonlinearRegression with automatic rescaling from a combined data matrix.

Value parameters

b_init

the initial guess for the parameter vector b

col

the designated response column (defaults to the last column)

f

the nonlinear function f(x, b) to fit

fname

the feature/variable names (defaults to null)

hparam

the hyper-parameters (currently has none)

xy

the combined data/input and response/output matrix

Attributes

def rescale(x: MatrixD, y: VectorD, f: FunctionP2S, b_init: VectorD, fname: Array[String], hparam: HyperParameter): NonlinearRegression

Create a NonlinearRegression with automatic rescaling from a data matrix and response vector.

Create a NonlinearRegression with automatic rescaling from a data matrix and response vector.

Value parameters

b_init

the initial guess for the parameter vector b

f

the nonlinear function f(x, b) to fit

fname

the feature/variable names (defaults to null)

hparam

the hyper-parameters (currently has none)

x

the data/input matrix

y

the response/output vector

Attributes