fastbayes 0.1.0.0 → 0.2.0.0
raw patch · 2 files changed
+10/−7 lines, 2 filesdep ~basePVP ok
version bump matches the API change (PVP)
Dependency ranges changed: base
API changes (from Hackage documentation)
- Statistics.FastBayes.Linear: numEffectiveParameters :: Fit -> Double
+ Statistics.FastBayes.Linear: effectiveNumParameters :: Fit -> Double
Files
fastbayes.cabal view
@@ -3,13 +3,13 @@ -- The name of the package. name: fastbayes-version: 0.1.0.0+version: 0.2.0.0 -- A short (one-line) description of the package. synopsis: Bayesian modeling algorithms accelerated for particular model structures -- A longer description of the package.-description: General-purpose sampling approaches like Gibbs sampling are very useful for models that have not been studied extensively. But for some cases, specialized algorithms are available because of the model's generality (/e.g./, linear regression) or niche popularity (/e.g./, Latent Dirichlet Allocation). This package is an effort to collect such algorithms in one place.+description: General-purpose sampling approaches like Gibbs sampling are very useful for models that have not been studied extensively. But for some cases, specialized algorithms are available because of the model's commonality (/e.g./, linear regression) or niche popularity (/e.g./, Latent Dirichlet Allocation). This package is an effort to collect such algorithms in one place. -- URL for the project homepage or repository. homepage: https://github.com/cscherrer/fastbayes@@ -36,11 +36,14 @@ other-extensions: UnicodeSyntax, BangPatterns -- Other library packages from which modules are imported.- build-depends: base >=4.7 && <4.8, vector >=0.10 && <0.11, hmatrix >=0.16 && <0.17+ build-depends: base >=4.6 && <4.8, vector >=0.10 && <0.11, hmatrix >=0.16 && <0.17 -- Directories containing source files. hs-source-dirs: src -- Base language which the package is written in. default-language: Haskell2010- ++source-repository head+ type: git+ location: git://github.com/cscherrer/fastbayes.git
src/Statistics/FastBayes/Linear.hs view
@@ -25,7 +25,7 @@ , response , priorPrecision , noisePrecision - , numEffectiveParameters+ , effectiveNumParameters , logEvidence , mapWeights , hessian@@ -41,9 +41,9 @@ , response :: Vector Double -- ^The response vector used for the fit , priorPrecision :: Double -- ^The precision (inverse variance) of the prior distribution, determined by maximizing the marginal likelihood , noisePrecision :: Double -- ^The precision (inverse variance) of the noise- , numEffectiveParameters :: Double -- ^The number of effective parameters in the model+ , effectiveNumParameters :: Double -- ^The effective number of parameters in the model , logEvidence :: Double -- ^The log of the evidence, which is useful for model comparison (different features, same response)- , mapWeights :: Vector Double -- ^The MAP (maximum a posteriori) values for the paramter weights+ , mapWeights :: Vector Double -- ^The MAP (maximum a posteriori) values for the parameter weights , hessian :: Matrix Double -- ^The Hessian (matrix of second derivatives) for the posterior distribution } deriving Show