# 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. |