Enumeration Types

This section lists the enumeration types defined in the Extreme Optimization Numerical Libraries for .NET.

AnovaRowType

Enumerates the possible types of rows in an AnovaTable.

Member Name

Description

Model

The data in the row refers to model effects.

Error

The data in the row refers to the residual error in the model.

Total

The data in the row refers to the total of model effects and residuals.

BoundaryIntervalBehavior

Enumerates how segments at the boundaries of subdivided series are handled.

Member Name

Description

Exclude

The entire interval is excluded.

Include

The interval is included.

CompleteAndIncludel

The interval is extended to a full larger interval and the extended interval is included.

DateTimeUnit

Enumerates the time units used in the construction of time scales.

Member Name

Description

Unknown

The time unit is unknown.

Hour

The time unit is one hour

Day

The time unit is one day.

Week

The time unit is one week.

Month

The time unit is one month.

Quarter

The time unit is one quarter.

Year

The time unit is one year.

MissingValueAction

Enumerates the possible actions to be taken when a calculation encounters a missing value.

Member Name

Description

Default

Use the default action: The value or row containing the missing value is discarded.

Discard

The value or row containing the missing value is discarded.

Ignore

The value is ignored. Most operations on numerical variables will give NaN as a result.

ReplaceWithPrevious

Any missing values are replaced with the value of the previous observation. If the first observation is missing, it is replaced with a user-specified value, or 0.

ReplaceWithNext

Any missing values are replaced with the value of the next observation. If the last observation is missing, it is replaced with a user-specified value, or 0.

ReplaceWithValue

Any missing values are replaced with a user-specified value.

Fail

A MissingValueException is thrown.

SortOrder

Enumerates the ways data can be sorted.

Member Name

Description

None

The data is not sorted.

Ascending

The data is sorted in ascending order.

Descending

The data is sorted in descending order.

SpecialBins

Enumerates the possible special bins to be included in a Histogram.

Member Name

Description

None

No special bins are included.

BelowMinimum

There is a special bin for values below the scale's minimum value.

AboveMaximum

There is a special bin for values above the scale's maximum value.

OutOfRange

There is a special bin for values that are outside the scale's range.

Missing

There is a special bin for missing values.

TestOfHomogeneityOfVariances

Enumerates the choices when testing whether a number of samples have the same variance.

Member Name

Description

Levene

Use LeveneTest.

Bartlett

Use BartlettTest.

TestOfNormality

Enumerates the choices when testing whether a sample follows a normal distribution.

Member Name

Description

AndersonDarling

Use the AndersonDarlingTest.

ChiSquared

Use the ChiSquareGoodnessOfFitTest.

RanLuxLuxuryLevel

Enumerates possible values for the luxury level of a RanLux random number generator.

Member Name

Description

Default

The default (low) level.

Better

A medium value providing better randomness at a reasonable cost.

Best

Highest possible value, providing best possible randomness at greatest cost.

HypothesisTestType

Enumerates the possible values for a hypothesis test.

Member Name

Description

TwoTailed

The null hypothesis is rejected if the test statistic lies too far on either side of the mean of the test distribution.

OneTailedLower

The null hypothesis is rejected if the test statistic lies in the left (lower) tail of the test distribution.

OneTailedUpper

The null hypothesis is rejected if the test statistic lies in the right (upper) tail of the test distribution.

LeveneTestLocationMeasure

Enumerates the ways the central tendency of a sample is calculated in LeveneTest.

Levene's test for homogeneity of variances assumes that the underlying populations of the samples have a normal distribution. A specific choice of measure for central tendency can make the test more robust when the data is not normal.

Member Name

Description

Mean

The mean is used. This works best for normal data.

Median

The median is used. This is the default, and gives better results when the data is skewed.

TrimmedMean

The 10% trimmed mean is used. This gives better results when the data is heavy-tailed.

SamplePairing

Enumerates the possible ways to relate two samples in a two sample hypothesis test.

Member Name

Description

Unpaired

The two samples are independent.

Paired

The two samples are paired. Each observation in the first sample has a corresponding observation in the second sample.

VarianceAssumption

Enumerates the possible assumptions made about the variances in a multi-sample hypothesis test.

Member Name

Description

None

No assumption is made about the variances of the samples.

AssumeEqual

The variances of the samples are assumed to be equal.