ImputeNormalWin
The ImputeNormalWin object imputes the missing values in the vector using Normal Distribution for a sliding window.
Attributes
- Graph
-
- Supertypes
- Self type
-
ImputeNormalWin.type
Members list
Value members
Concrete methods
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.
Value parameters
- q
-
size of the sliding window
Attributes
- Definition Classes
Inherited methods
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.
Value parameters
- i_
-
the starting index to look for missing value
- x
-
the vector with missing values
Attributes
- Inherited from:
- Imputation
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.
Value parameters
- i
-
the starting index to look for missing value
- x
-
the vector with missing values
Attributes
- Inherited from:
- Imputation
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.
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.
Value parameters
- x
-
the matrix with missing values
Attributes
- Inherited from:
- Imputation
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.
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.
Value parameters
- i
-
the starting index to look for missing values
- x
-
the vector with missing values
Attributes
- Inherited from:
- Imputation
Return the next non-missing value in vector x from index i. If none, return missVal.
Return the next non-missing value in vector x from index i. If none, return missVal.
Value parameters
- i
-
the starting index to look for non-missing value
- x
-
the vector to be searched for a non-missing value
Attributes
- Inherited from:
- Imputation
Return the median of three normally distributed random numbers.
Return the median of three normally distributed random numbers.
Value parameters
- mu
-
the mean
- sig2
-
the variance
Attributes
- Inherited from:
- Imputation
Return the previous non-missing value in vector x from index i. If none, return missVal.
Return the previous non-missing value in vector x from index i. If none, return missVal.
Value parameters
- i
-
the starting index to look for non-missing value
- x
-
the vector to be searched (backwards) for a non-missing value
Attributes
- Inherited from:
- Imputation
Set the distance dist to the new value dist_.
Set the distance dist to the new value dist_.
Value parameters
- dist_
-
the new value for the distance
Attributes
- Inherited from:
- Imputation
Set the missing value missVal to the new missing value indicator missVal_.
Set the missing value missVal to the new missing value indicator missVal_.
Value parameters
- missVal_
-
the new missing value indicator
Attributes
- Inherited from:
- Imputation
Inherited fields
Attributes
- Inherited from:
- Imputation
Attributes
- Inherited from:
- Imputation
Attributes
- Inherited from:
- Imputation
Attributes
- Inherited from:
- Imputation
Attributes
- Inherited from:
- Imputation