hanalyze-models-0.2.0.1: hanalyze-models.cabal

cabal-version: 3.0
name:          hanalyze-models
version:       0.2.0.1
synopsis:      Model layer of hanalyze: regression, ML, survival, causal
description:
    The model layer of the hanalyze toolkit: a model zoo spanning
    classical regression (LM, GLM, GLMM, robust, quantile, splines, GAM),
    penalised regression with automatic lambda selection (Lasso / Ridge /
    Elastic Net / MCP / SCAD), the Formula DSL front-end, multivariate
    analysis (PCA, PLS, LDA / QDA, MDS, clustering), machine learning
    (random forest, gradient boosting, SVM, k-NN, neural networks),
    Gaussian processes and multi-output models, time series (VAR, GARCH,
    state space), survival and reliability (Kaplan-Meier, Cox, AFT,
    Weibull MLE, accelerated-life models), causal inference (LiNGAM,
    propensity score, IPW, doubly robust, CATE) and Bayesian optimisation.
    .
    Module names match the umbrella package hanalyze, which re-exports
    everything, so downstream imports stay identical. See README.md for the
    module map and a standalone usage example.
license:       BSD-3-Clause
author:        Toshiaki Honda
maintainer:    frenzieddoll@gmail.com
copyright:     2026 Aelysce Project (Toshiaki Honda)
category:      Math, Statistics, Numeric, Machine Learning
build-type:    Simple
tested-with:   GHC == 9.6.7
extra-source-files:
    README.md
    README.ja.md

common warnings
  ghc-options: -Wall -Wcompat -Widentities -Wredundant-constraints

-- -O2 は分割前と同一 (性能変更と構造変更を混ぜない、 層別 -O 調整は 106.5 後の別 Phase)
common opt
  ghc-options: -O2 -funbox-strict-fields

library
  import:           warnings, opt
  hs-source-dirs:   src
  default-language: GHC2021
  exposed-modules:
    Hanalyze.Model.AFT
    Hanalyze.Model.Cluster
    Hanalyze.Model.CompetingRisks
    Hanalyze.Model.DAG
    Hanalyze.Model.DecisionTree
    Hanalyze.Model.Discriminant
    Hanalyze.Model.FDA
    Hanalyze.Model.FitYByX
    Hanalyze.Model.Formula
    Hanalyze.Model.Formula.Design
    Hanalyze.Model.Formula.Frame
    Hanalyze.Model.Formula.Mixed
    Hanalyze.Model.Formula.Nonlinear
    Hanalyze.Model.Formula.RFormula
    Hanalyze.Model.GAM
    Hanalyze.Model.GARCH
    Hanalyze.Model.GLM
    Hanalyze.Model.GLMM
    Hanalyze.Model.GP
    Hanalyze.Model.GPRobust
    Hanalyze.Model.GradientBoosting
    Hanalyze.Model.HierarchicalCluster
    Hanalyze.Model.KNN
    Hanalyze.Model.Kernel
    Hanalyze.Model.KernelRegression
    Hanalyze.Model.LM
    Hanalyze.Model.LM.Diagnostics
    Hanalyze.Model.LatentClassAnalysis
    Hanalyze.Model.LiNGAM.Bootstrap
    Hanalyze.Model.LiNGAM.Direct
    Hanalyze.Model.LiNGAM.ICA
    Hanalyze.Model.LiNGAM.MultiGroup
    Hanalyze.Model.LiNGAM.Pairwise
    Hanalyze.Model.LiNGAM.Parce
    Hanalyze.Model.LiNGAM.VAR
    Hanalyze.Model.MDS
    Hanalyze.Model.MultiGP
    Hanalyze.Model.MultiLM
    Hanalyze.Model.MultiOutput
    Hanalyze.Model.Multivariate
    Hanalyze.Model.NaiveBayes
    Hanalyze.Model.NeuralNetwork
    Hanalyze.Model.PCA
    Hanalyze.Model.PLS
    Hanalyze.Model.PartialDependence
    Hanalyze.Model.Quantile
    Hanalyze.Model.RFF
    Hanalyze.Model.RandomForest
    Hanalyze.Model.RandomForestClassifier
    Hanalyze.Model.Regularized
    Hanalyze.Model.RegularizedAdvanced
    Hanalyze.Model.Reliability
    Hanalyze.Model.ReliabilityBlockDiagram
    Hanalyze.Model.Robust
    Hanalyze.Model.SVM
    Hanalyze.Model.Spline
    Hanalyze.Model.StateSpace
    Hanalyze.Model.Survival
    Hanalyze.Model.TimeSeries
    Hanalyze.Model.VAR
    Hanalyze.Model.Weibull
    Hanalyze.Optim.BayesOpt
    Hanalyze.Stat.Causal.CATE
    Hanalyze.Stat.Causal.DoublyRobust
    Hanalyze.Stat.Causal.IPW
    Hanalyze.Stat.Causal.PropensityScore
    Hanalyze.Stat.ModelSelect
  build-depends:
      base                 >= 4.14 && < 5
    , containers           >= 0.6  && < 0.8
    , hmatrix              >= 0.20 && < 0.22
    , mwc-random           >= 0.15 && < 0.16
    , primitive            >= 0.7  && < 0.10
    , statistics           >= 0.16 && < 0.17
    , text                 >= 1.2  && < 2.2
    , vector               >= 0.12 && < 0.14
    , dataframe-core        ^>= 1.1
    , vector-algorithms    >= 0.9  && < 0.10
    , megaparsec           >= 9.0  && < 9.7
    , parser-combinators   >= 1.3  && < 1.4
    , hanalyze-core == 0.2.0.1
    , hanalyze-frame == 0.2.0.1
    , hanalyze-bayes == 0.2.0.1