| Portability | portable |
|---|---|
| Stability | experimental |
| Maintainer | felipe.lessa@gmail.com |
| Safe Haskell | Safe-Infered |
Math.Statistics.Dirichlet.Density
Description
- newtype DirichletDensity = DD {}
- empty :: Int -> Double -> DirichletDensity
- fromList :: [Double] -> DirichletDensity
- toList :: DirichletDensity -> [Double]
- derive :: DirichletDensity -> Predicate -> StepSize -> TrainingVectors -> Result DirichletDensity
- cost :: TrainingVectors -> DirichletDensity -> Double
Documentation
newtype DirichletDensity Source
A Dirichlet density.
empty :: Int -> Double -> DirichletDensitySource
empty n x is an "empty" Dirichlet density with size
n and all alphas set to x.
fromList :: [Double] -> DirichletDensitySource
fromList xs constructs a Dirichlet density from a list of
alpha values.
toList :: DirichletDensity -> [Double]Source
toList d deconstructs a Dirichlet density to a list of
alpha values.
derive :: DirichletDensity -> Predicate -> StepSize -> TrainingVectors -> Result DirichletDensitySource
Derive a Dirichlet density using a maximum likelihood method as described by Karplus et al (equation 26). All training vectors should have the same length, however this is not verified.
cost :: TrainingVectors -> DirichletDensity -> DoubleSource
Cost function for deriving a Dirichlet density (equation
18). This function is minimized by derive.