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. |