Enum Class MissingValueSupport
- All Implemented Interfaces:
Serializable, Comparable<MissingValueSupport>, Constable
A capability declaration for scores and independence tests, stating what the component itself can do with data
containing missing values. Callers (search wrappers, the GUI, py-tetrad) can consult this before running, instead
of discovering behavior--or silent misbehavior--at runtime.
This describes what the component can do natively; it does not preclude handling missingness upstream, e.g., by imputing completed datasets or by supplying an EM-estimated covariance matrix to a covariance-consuming component.
- Version:
- $Id: $Id
- Author:
- josephramsey
- See Also:
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Nested Class Summary
Nested classes/interfaces inherited from class Enum
Enum.EnumDesc<E> -
Enum Constant Summary
Enum ConstantsEnum ConstantDescriptionThe component handles missing values natively in a manner valid under MAR, e.g., a full-information maximum likelihood score that computes row-wise likelihood contributions over the observed entries of each row.The component has no support for missing values.The component performs test-wise (pairwise/local) deletion: each local calculation uses the rows complete on the variables involved in that calculation.The component consumes a covariance matrix (or can be constructed from one), so missingness can be handled by supplying a covariance matrix estimated under MAR, e.g., byEmCovarianceEstimator. -
Method Summary
Modifier and TypeMethodDescriptionstatic MissingValueSupportReturns the enum constant of this class with the specified name.static MissingValueSupport[]values()Returns an array containing the constants of this enum class, in the order they are declared.Methods inherited from class Enum
compareTo, describeConstable, equals, getDeclaringClass, hashCode, name, ordinal, toString, valueOf
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Enum Constant Details
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NONE
The component has no support for missing values. Passing it raw data containing missing values will produce an exception at best and silently incorrect results (e.g., NaN propagation into likelihoods) at worst. Missingness must be handled upstream. -
TESTWISE
The component performs test-wise (pairwise/local) deletion: each local calculation uses the rows complete on the variables involved in that calculation. Unbiased only under MCAR. -
VIA_COVARIANCE
The component consumes a covariance matrix (or can be constructed from one), so missingness can be handled by supplying a covariance matrix estimated under MAR, e.g., byEmCovarianceEstimator. -
NATIVE_MAR
The component handles missing values natively in a manner valid under MAR, e.g., a full-information maximum likelihood score that computes row-wise likelihood contributions over the observed entries of each row.
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Method Details
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values
Returns an array containing the constants of this enum class, in the order they are declared.- Returns:
- an array containing the constants of this enum class, in the order they are declared
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valueOf
Returns the enum constant of this class with the specified name. The string must match exactly an identifier used to declare an enum constant in this class. (Extraneous whitespace characters are not permitted.)- Parameters:
name- the name of the enum constant to be returned.- Returns:
- the enum constant with the specified name
- Throws:
IllegalArgumentException- if this enum class has no constant with the specified nameNullPointerException- if the argument is null
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