scalation
API
Generated with
scalation/scalation/scalation.modeling/QuantileReg

QuantileReg

scalation.modeling.QuantileReg
See theQuantileReg companion class
object QuantileReg

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 = ...)(col: Int = ...): QuantileReg

Create a QuantileReg object from a combined data-response matrix.

Create a QuantileReg object from a combined data-response matrix.

Value parameters

col

the designated response column (defaults to the last column)

fname

the feature/variable names (defaults to null)

hparam

the hyper-parameters (defaults to hp)

xy

the combined data-response matrix (predictors and response)

Attributes

def predInterval(xy: MatrixD, fname: Array[String] = ..., α: Double = ..., hparam: HyperParameter = ...)(col: Int = ...): (QuantileReg, QuantileReg)

Create two QuantileReg objects from a combined data-response matrix, at lower and upper quantiles to enable prediction intervals.

Create two QuantileReg objects from a combined data-response matrix, at lower and upper quantiles to enable prediction intervals.

Value parameters

col

the designated response column (defaults to the last column)

fname

the feature/variable names (defaults to null)

hparam

the hyper-parameters (defaults to hp)

xy

the combined data-response matrix (predictors and response)

α

the significance level (e.g., .1 => 2 .05 tails: .05 [ .9 ] .05

Attributes

Concrete fields

val hp: HyperParameter

Base hyper-parameter specification for Regression

Base hyper-parameter specification for Regression

Attributes

Generated with