FTest Class |
Namespace: Accord.Statistics.Testing
The FTest type exposes the following members.
Name | Description | |
---|---|---|
FTest |
Creates a new F-Test.
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FTest(Double, Int32, Int32, TwoSampleHypothesis) |
Creates a new F-Test for a given statistic with given degrees of freedom.
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FTest(Double, Double, Int32, Int32, TwoSampleHypothesis) |
Creates a new F-Test for a given statistic with given degrees of freedom.
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Name | Description | |
---|---|---|
CriticalValue |
Gets the critical value for the current significance level.
(Inherited from HypothesisTestTDistribution.) | |
DegreesOfFreedom1 |
Gets the degrees of freedom for the
numerator in the test distribution.
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DegreesOfFreedom2 |
Gets the degrees of freedom for the
denominator in the test distribution.
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Hypothesis |
Gets the alternative hypothesis under test. If the test is
Significant, the null hypothesis can be rejected
in favor of this alternative hypothesis.
| |
PValue |
Gets the P-value associated with this test.
(Inherited from HypothesisTestTDistribution.) | |
Significant |
Gets whether the null hypothesis should be rejected.
(Inherited from HypothesisTestTDistribution.) | |
Size |
Gets the significance level for the
test. Default value is 0.05 (5%).
(Inherited from HypothesisTestTDistribution.) | |
Statistic |
Gets the test statistic.
(Inherited from HypothesisTestTDistribution.) | |
StatisticDistribution |
Gets the distribution associated
with the test statistic.
(Inherited from HypothesisTestTDistribution.) | |
Tail |
Gets the test type.
(Inherited from HypothesisTestTDistribution.) |
Name | Description | |
---|---|---|
Compute |
Computes the F-test.
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Equals | Determines whether the specified object is equal to the current object. (Inherited from Object.) | |
Finalize | Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.) | |
GetHashCode | Serves as the default hash function. (Inherited from Object.) | |
GetType | Gets the Type of the current instance. (Inherited from Object.) | |
MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object.) | |
OnSizeChanged |
Called whenever the test significance level changes.
(Inherited from HypothesisTestTDistribution.) | |
PValueToStatistic |
Converts a given p-value to a test statistic.
(Overrides HypothesisTestTDistributionPValueToStatistic(Double).) | |
StatisticToPValue |
Converts a given test statistic to a p-value.
(Overrides HypothesisTestTDistributionStatisticToPValue(Double).) | |
ToString |
Converts the numeric P-Value of this test to its equivalent string representation.
(Inherited from HypothesisTestTDistribution.) | |
ToString(String, IFormatProvider) |
Converts the numeric P-Value of this test to its equivalent string representation.
(Inherited from HypothesisTestTDistribution.) |
Name | Description | |
---|---|---|
HasMethod |
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.) | |
IsEqual |
Compares two objects for equality, performing an elementwise
comparison if the elements are vectors or matrices.
(Defined by Matrix.) | |
To(Type) | Overloaded.
Converts an object into another type, irrespective of whether
the conversion can be done at compile time or not. This can be
used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.) | |
ToT | Overloaded.
Converts an object into another type, irrespective of whether
the conversion can be done at compile time or not. This can be
used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.) |
A F-test is any statistical test in which the test statistic has an F-distribution under the null hypothesis. It is most often used when comparing statistical models that have been fit to a data set, in order to identify the model that best fits the population from which the data were sampled.
References:
// The following example has been based on the page "F-Test for Equality // of Two Variances", from NIST/SEMATECH e-Handbook of Statistical Methods: // // http://www.itl.nist.gov/div898/handbook/eda/section3/eda359.htm // // Consider a data set containing 480 ceramic strength // measurements for two batches of material. The summary // statistics for each batch are shown below: // Batch 1: int numberOfObservations1 = 240; // double mean1 = 688.9987; double stdDev1 = 65.54909; double var1 = stdDev1 * stdDev1; // Batch 2: int numberOfObservations2 = 240; // double mean2 = 611.1559; double stdDev2 = 61.85425; double var2 = stdDev2 * stdDev2; // Here, we will be testing the null hypothesis that // the variances for the two batches are equal. int degreesOfFreedom1 = numberOfObservations1 - 1; int degreesOfFreedom2 = numberOfObservations2 - 1; // Now we can create a F-Test to test the difference between variances var ftest = new FTest(var1, var2, degreesOfFreedom1, degreesOfFreedom2); double statistic = ftest.Statistic; // 1.123037 double pvalue = ftest.PValue; // 0.185191 bool significant = ftest.Significant; // false // The F test indicates that there is not enough evidence // to reject the null hypothesis that the two batch variances // are equal at the 0.05 significance level.