src/stat-models/model-fit.lisp

   1 ;;; -*- mode: lisp -*-
   2 ;;; Copyright (c) 2005--2007, by A.J. Rossini <blindglobe@gmail.com>
   3 ;;; See COPYRIGHT file for any additional restrictions (BSD license).
   4 ;;; Since 1991, ANSI was finally finished.  Edited for ANSI Common Lisp.
   5
   6 ;;; File:       model-fit.lisp
   7 ;;; Author:     AJ Rossini <blindglobe@gmail.com>
   8 ;;; Copyright:  (c)2007, AJ Rossini.  BSD, LLGPL, or GPLv2, depending
   9 ;;;             on how it arrives.
  10 ;;; Purpose:    models as a data summarization tools.
  11 ;;; Time-stamp: <2006-05-19 12:33:41 rossini>
  12 ;;; Creation:   <2006-05-17 21:34:07 rossini>
  13
  14 ;;; What is this talk of 'release'? Klingons do not make software
  15 ;;; 'releases'.  Our software 'escapes', leaving a bloody trail of
  16 ;;; designers and quality assurance people in its wake.
  17
  18 ;;; The model class is used to map a partial or complete model
  19 ;;; specification (partial specification made complete by assumptions
  20 ;;; inherent in the type of model used, i.e. linear regression assumes
  21 ;;; mean-zero and homoskedasticity) and the model-fit class is used to
  22 ;;; complete the model specification into how the model instance and
  23 ;;; type will then get computed.  The approach tken is that we
  24 ;;; definitiely want to be able to see how we can explicitly try to
  25 ;;; characterize the work that we are trying to infere about the data.
  26
  27 (in-package :cl-user)
  28
  29 (defpackage :lisp-stat-model-fit
  30   (:documentation "Model fitting theory.")
  31   (:nicknames :ls-model-fit)
  32   (:use :common-lisp
  33         :lisp-stat-config
  34         :lisp-stat-object-system
  35         :lisp-stat-types
  36         :lisp-stat-compound-data
  37 #|
  38         :lisp-stat-matrix
  39         :lisp-stat-linalg
  40 |#
  41         )
  42   (:shadowing-import-from :lisp-stat-object-system
  43                           slot-value call-method call-next-method)
  44   (:export fit))
  45
  46 (in-package :lisp-stat-model)
  47
  48 (defclass fit ()
  49   ((criteria-functin-name :initform nil
  50          :initarg :name
  51          :accessor name
  52          :reader model-name)
  53    (criteria-function :initform nil
  54          :initarg :formula
  55          :accessor function
  56          :reader fit-criteria)
  57    (parameter-vars :initform nil
  58                    :initarg :parameter-vars
  59                    :accessor param-vars
  60                    :reader model-formula)
  61    (data-vars :initform nil
  62               :initarg :data-vars
  63               :accessor data-vars
  64               :reader model-formula)
  65    (fixed-vars :initform nil
  66                :initarg :fixed-vars
  67                :accessor fixed-vars
  68                :reader model-formula)
  69
  70   (:documentation "Mathematical Model Fit approach"))
  71
  72 (defclass optimization (model-fit))
  73
  74
  75 (defclass least-squares (optimization))
  76 (defclass weighted-least-squares (least-squares))
  77
  78 (defclass maximum-likelihood (optimization))
  79 (defclass minimax (optimization))
  80 (defclass maximin (optimization))
  81
  82 (defclass minimum-entropy (optimization))
  83 (defclass lq-norm (optimization))
  84
  85 (defclass root-finding (model-fit))
  86
  87 (defclass method-of-moments (root-finding))
  88 (defclass marginal-models (method-of-moments))
  89 (defclass gee (marginal-models))
  90 (defclass gee2 (marginal-models))
  91
  92
  93
  94 ;;; How would this be used?
  95
  96 (setf my-regr-model-1
  97       (new 'least-squares  '(- y (+ (* beta1 x1) (* beta2 x2)))))
  98
  99 ;; and there should be an approach which could provide a mapping to this, i.e.
 100
 101 (regression-model (list y) (list x1 x2))
 102
 103 ;; could map to the above via macros.