Record Class FTest
java.lang.Object
java.lang.Record
smile.stat.hypothesis.FTest
- Record Components:
f- the F-statistic.df1- the first degree of freedom of F-statistic.df2- the second degree of freedom of F-statistic.pvalue- the p-value.
F test of the hypothesis that two independent samples come from normal
distributions with the same variance, against the alternative that they
come from normal distributions with different variances. Note that the F-test
is extremely non-robust to non-normality. That is, even if the data displays
only modest departures from the normal distribution, the test is unreliable
and should not be used.
-
Constructor Summary
ConstructorsConstructorDescriptionFTest(double f, int df1, int df2, double pvalue) Creates an instance of aFTestrecord class. -
Method Summary
Modifier and TypeMethodDescriptionintdf1()Returns the value of thedf1record component.intdf2()Returns the value of thedf2record component.final booleanIndicates whether some other object is "equal to" this one.doublef()Returns the value of thefrecord component.final inthashCode()Returns a hash code value for this object.doublepvalue()Returns the value of thepvaluerecord component.static FTesttest(double[] x, double[] y) Test if the arrays x and y have significantly different variances.static FTesttest(int[] x, double[] y) One-way analysis of variance (ANOVA) between a categorical independent variable (with two or more categories) and a normally distributed interval dependent variable to test for differences in the means of the dependent variable broken down by the levels of the independent variable.toString()Returns a string representation of this record class.
-
Constructor Details
-
FTest
-
-
Method Details
-
toString
-
test
Test if the arrays x and y have significantly different variances. Small values of p-value indicate that the two arrays have significantly different variances.- Parameters:
x- the sample values.y- the sample values.- Returns:
- the test results.
-
test
One-way analysis of variance (ANOVA) between a categorical independent variable (with two or more categories) and a normally distributed interval dependent variable to test for differences in the means of the dependent variable broken down by the levels of the independent variable. Treat the variances in the samples as equal.- Parameters:
x- the categorical independent variable.y- the normally distributed interval dependent variable.- Returns:
- the test results.
-
hashCode
-
equals
Indicates whether some other object is "equal to" this one. The objects are equal if the other object is of the same class and if all the record components are equal. All components in this record class are compared with thecomparemethod from their corresponding wrapper classes. -
f
-
df1
-
df2
-
pvalue
-