PostHoc (FSharp.Stats) | FSharp.Stats

FSharp.Stats

PostHoc Module

Namespace: FSharp.Stats.Testing
Assembly: FSharp.Stats.dll

Types

Type	Description
Contrast
CriticalValueContrast

Functions and values

Function or value	Description
`createContrast index l degreesOfFreedom meanSquares significance statistic sumOfSquares` Full Usage: `createContrast index l degreesOfFreedom meanSquares significance statistic sumOfSquares` Parameters: index : `int` l : `float` degreesOfFreedom : `float` meanSquares : `float` significance : `float` statistic : `float` sumOfSquares : `float` Returns: `Contrast`	index : `int` l : `float` degreesOfFreedom : `float` meanSquares : `float` significance : `float` statistic : `float` sumOfSquares : `float` Returns: `Contrast`
`dunnetts contrastMatrix data criticalTable` Full Usage: `dunnetts contrastMatrix data criticalTable` Parameters: contrastMatrix : `float[][]` data : `float[][]` criticalTable : `Matrix<float>` Returns: `CriticalValueContrast array`	Dunnetts post hoc test compares groups to one control group (multiple-to-one comparison). Returns if the groups defined in the contrast differ significantly (already multi comparison corrected for FWER < a) Critical value tables can be found in Testing.Tables contrastMatrix : `float[][]` data : `float[][]` criticalTable : `Matrix<float>` Returns: `CriticalValueContrast array`
`fishersLSD contrastMatrix data` Full Usage: `fishersLSD contrastMatrix data` Parameters: contrastMatrix : `float[][]` data : `float[][]` Returns: `Contrast array`	Fisher's LSD. Sequential t tests with the variance estimated from all samples instead of the individual groups. FishersLSD requires ANOVA protection (apply ANOVA first). Not multiple testing corrected! Apply e.g. Benjamini-Hochberg method afterwards. contrastMatrix : `float[][]` data : `float[][]` Returns: `Contrast array`
`hays contrastMatrix data` Full Usage: `hays contrastMatrix data` Parameters: contrastMatrix : `float[][]` data : `float[][]` Returns: `Contrast array`	contrastMatrix : `float[][]` data : `float[][]` Returns: `Contrast array`
`tukeyHSD contrastMatrix data` Full Usage: `tukeyHSD contrastMatrix data` Parameters: contrastMatrix : `float[][]` data : `float[][]` Returns: `Contrast array`	Tukey-Kramer approach contrastMatrix : `float[][]` data : `float[][]` Returns: `Contrast array`