NMath Reference Guide

## One |

Class OneSampleKSTest performs a Kolmogorov-Smirnov test of the distribution of
one sample.

Inheritance Hierarchy

Syntax

The OneSampleKSTest type exposes the following members.

Constructors

Name | Description | |
---|---|---|

OneSampleKSTest | Default constructor. Constructs an empty OneSampleKSTest instance. | |

OneSampleKSTest(Double, ProbabilityDistribution) | Constructs a OneSampleKSTest from the given sample data and specified distribution. | |

OneSampleKSTest(Double, FuncDouble, Double) | Constructs a OneSampleKSTest from the given sample data and specified cumulative distribution function (CDF). | |

OneSampleKSTest(DoubleVector, ProbabilityDistribution) | Constructs a OneSampleKSTest from the given sample data and specified distribution. | |

OneSampleKSTest(DoubleVector, FuncDouble, Double) | Constructs a OneSampleKSTest from the given sample data and specified cumulative distribution function (CDF). | |

OneSampleKSTest(IDFColumn, ProbabilityDistribution) | Constructs a OneSampleKSTest from the given sample data and specified distribution. | |

OneSampleKSTest(IDFColumn, FuncDouble, Double) | Constructs a OneSampleKSTest from the given sample data and specified cumulative distribution function (CDF). | |

OneSampleKSTest(Int32, ProbabilityDistribution) | Constructs a OneSampleKSTest from the given sample data and specified distribution. | |

OneSampleKSTest(Int32, FuncDouble, Double) | ||

OneSampleKSTest(Double, ProbabilityDistribution, Double) | Constructs a OneSampleKSTest from the given sample data and specified distribution. | |

OneSampleKSTest(Double, FuncDouble, Double, Double) | ||

OneSampleKSTest(DoubleVector, ProbabilityDistribution, Double) | Constructs a OneSampleKSTest from the given sample data and specified distribution. | |

OneSampleKSTest(DoubleVector, FuncDouble, Double, Double) | ||

OneSampleKSTest(IDFColumn, ProbabilityDistribution, Double) | Constructs a OneSampleKSTest from the given sample data and specified distribution. | |

OneSampleKSTest(IDFColumn, FuncDouble, Double, Double) | ||

OneSampleKSTest(Int32, ProbabilityDistribution, Double) | Constructs a OneSampleKSTest from the given sample data and specified distribution. | |

OneSampleKSTest(Int32, FuncDouble, Double, Double) |

Properties

Name | Description | |
---|---|---|

Alpha | Gets and sets the alpha level associated with this hypothesis test. | |

CriticalValue | Gets the critical value based on the current alpha level associated with this hypothesis test. | |

DefaultAlpha | Gets and sets the default alpha level associated with OneSampleKSTests. | |

N | Gets the sample size. | |

P | Gets the p-value associated with the test statistic. | |

Reject | Tests whether the null hypothesis can be rejected, using the current alpha level. | |

Statistic | Gets the value of the test statistic associated with this hypothesis test. |

Methods

Name | Description | |
---|---|---|

Clone | Creates a deep copy of this OneSampleKSTest. | |

Update(Double, ProbabilityDistribution) | Updates this test with new sample data and a new distribution. | |

Update(Double, FuncDouble, Double) | Updates this test with new sample data and a new cumulative distribution function (CDF). | |

Update(DoubleVector, ProbabilityDistribution) | Updates this test with new sample data and a new distribution. | |

Update(DoubleVector, FuncDouble, Double) | Updates this test with new sample data and a new cumulative distribution function (CDF). | |

Update(IDFColumn, ProbabilityDistribution) | Updates this test with new sample data and a new distribution. | |

Update(IDFColumn, FuncDouble, Double) | Updates this test with new sample data and a new cumulative distribution function (CDF). | |

Update(Int32, ProbabilityDistribution) | Updates this test with new sample data and a new distribution. | |

Update(Int32, FuncDouble, Double) | Updates this test with new sample data and a new cumulative distribution function (CDF). |

Remarks

Class OneSampleKSTest compares the distribution of a given sample to the
hypothesized distribution defined by a specified cumulative distribution function
(CDF). For each potential value x, the Kolmogorov-Smirnov test compares the
proportion of values less than x with the expected number predicted by
the specified CDF. The null hypothesis is that the given sample data follow the
specified distribution. The alternative hypothesis that the data do not have
that distribution.

See Also