trait Imputation extends AnyRef
The Imputation trait specifies an imputation operation called 'impute' to be defined
by the objects implementing it, i.e.,
ImputeRegression - impute missing values using SimpleRegression
ImputeForward - impute missing values using previous values and slopes
ImputeBackward - impute missing values using subsequent values and slopes
ImputeMean - impute missing values usind the filtered mean
ImputeNormal - impute missing values using the median of Normal random variates
ImputeMovingAvg - impute missing values using the moving average
ImputeNormalWin - impute missing values using the median of Normal random variates for a window
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abstract
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
Concrete Value Members
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!=(arg0: Any): Boolean
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##(): Int
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val
DAMPEN: Double
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val
DEBUG: Boolean
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asInstanceOf[T0]: T0
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dist: Int
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eq(arg0: AnyRef): Boolean
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equals(arg0: Any): Boolean
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def
findLastMissing(x: VectoD, i: Int = -1): (Int, Double)
Return the index of last missing value in vector 'x' from index 'i' and the new imputed value.
Return the index of last missing value in vector 'x' from index 'i' and the new imputed value.
- x
the vector with missing values
- i
the starting index to look for missing value
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def
findMissing(x: VectoD, i: Int = 0): (Int, Double)
Return the index of first missing value in vector 'x' from index 'i' and the new imputed value.
Return the index of first missing value in vector 'x' from index 'i' and the new imputed value.
- x
the vector with missing values
- i
the starting index to look for missing value
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def
getClass(): Class[_]
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def
hashCode(): Int
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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
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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
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def
imputeAll(x: VectoD): VectoD
Replace all missing values in vector 'x' with imputed values.
Replace all missing values in vector 'x' with imputed values. Will change the values in vector 'x'. Make a copy to preserve values 'x.copy ()'.
- x
the vector with missing values
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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
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final
def
isInstanceOf[T0]: Boolean
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val
missVal: Double
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def
ne(arg0: AnyRef): Boolean
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def
nextVal(x: VectoD, i: Int): Double
Return the next non-missing value in vector 'x' from index 'i'.
Return the next non-missing value in vector 'x' from index 'i'.
- x
the vector to be searched for a non-missing value
- i
the starting index to look for non-missing value
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def
normalMedian(mu: Double, sig2: Double): Double
Return the median of three normally distributed random numbers.
Return the median of three normally distributed random numbers.
- mu
the mean
- sig2
the variance
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def
notify(): Unit
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def
notifyAll(): Unit
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def
prevVal(x: VectoD, i: Int): Double
Return the previous non-missing value in vector 'x' from index 'i'.
Return the previous non-missing value in vector 'x' from index 'i'.
- x
the vector to be searched (backwards) for a non-missing value
- i
the starting index to look for non-missing value
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val
q: Int
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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
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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
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