QuantileOutlier
Detect outliers in the vector by treating anything that falls outside 1-st or 99-th percentile. Common percentiles that may be passed in factor are .0035, .005, .01, .02, and .05. Note, extreme 2% as discussed in textbook corresponds to 1% in left tail and 1% in right tail.
Attributes
- Graph
-
- Supertypes
- Self type
-
QuantileOutlier.type
Members list
Value members
Concrete methods
Calculate the lower and upper bound for acceptable values for vector y. Treat anything that falls below the factor percentile or above the (1 - factor) percentile as an outlier.
Calculate the lower and upper bound for acceptable values for vector y. Treat anything that falls below the factor percentile or above the (1 - factor) percentile as an outlier.
Value parameters
- factor
-
the factor used in computing the bound (percentile)
- y
-
the vector with the possible outlier values
Attributes
Inherited methods
Find/detect all outliers in vector y outside the bounds and return their element indices.
Find/detect all outliers in vector y outside the bounds and return their element indices.
Value parameters
- bounds
-
the acceptable lower and upper bounds for element values
- y
-
the vector with the possible outlier values
Attributes
- Inherited from:
- Outlier
Remove all outliers from matrix x and vector y specified by indices in toRemove.
Remove all outliers from matrix x and vector y specified by indices in toRemove.
Value parameters
- toRemove
-
the indices of elements to be removed
- x
-
the predictor matrix: y = f(x)
- y
-
the vector with the possible outlier values
Attributes
- Inherited from:
- Outlier
Remove all outliers from vector y specified by indices in toRemove.
Remove all outliers from vector y specified by indices in toRemove.
Value parameters
- toRemove
-
the indices of elements to be removed
- y
-
the vector with the possible outlier values
Attributes
- Inherited from:
- Outlier