Packages

o

scalation.analytics

ImputeNormalWin

object ImputeNormalWin extends Imputation

The ImputeNormalWin object imputes the missing values in the vector using Normal Distribution for a sliding window.

Linear Supertypes
Imputation, AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. ImputeNormalWin
  2. Imputation
  3. AnyRef
  4. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. Protected

Value Members

  1. def impute(x: MatriD): MatriD

    Replace all missing values in matrix 'x' with imputed values.

    Replace all missing values in matrix 'x' with imputed values. Will change the values in matrix 'x'. Make a copy to preserve values 'x.copy'.

    x

    the matrix with missing values

    Definition Classes
    Imputation
  2. def impute(x: VectoD, i: Int = 0): (Int, Double)

    Impute a value for the first missing value in vector 'x' from index 'i'.

    Impute a value for the first missing value in vector 'x' from index 'i'. The type (Int, Double) returns (vector index for imputation, imputed value). Does not modify the vector.

    x

    the vector with missing values

    i

    the starting index to look for missing values

    Definition Classes
    Imputation
  3. def imputeAll(x: VectoD): VectoD

    Impute all the missing values in vector 'x' using Normal Distribution for a sliding window.

    Impute all the missing values in vector 'x' using Normal Distribution for a sliding window.

    x

    the vector with missing values@param q size of the sliding window

    Definition Classes
    ImputeNormalWinImputation
  4. def imputeAt(x: VectoD, i: Int): Double

    Impute a value for vector 'x' at index 'i'.

    Impute a value for vector 'x' at index 'i'. Does not modify the vector.

    x

    the vector with missing values

    i

    the index position for which to impute a value

    Definition Classes
    ImputeNormalWinImputation
  5. def imputeCol(c: Vec, i: Int = 0): (Int, Any)

    Impute a value for the first missing value in column 'c' from index 'i'.

    Impute a value for the first missing value in column 'c' from index 'i'. The type (Int, Double) returns (vector index for imputation, imputed value). Does not modify the column.

    c

    the column with missing values

    i

    the starting index to look for missing values

    Definition Classes
    Imputation
  6. def setDist(dist_: Int): Unit

    Set the distance 'dist' to the new value 'dist_'.

    Set the distance 'dist' to the new value 'dist_'.

    dist_

    the new value for the distance

    Definition Classes
    Imputation
  7. def setMissVal(missVal_: Double): Unit

    Set the missing value 'missVal' to the new missing value indicator 'missVal_'.

    Set the missing value 'missVal' to the new missing value indicator 'missVal_'.

    missVal_

    the new missing value indicator

    Definition Classes
    Imputation