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;;; -*- mode: lisp -*-
;;; Time-stamp: <2009-10-09 12:17:47 tony>
;;; Creation: <2009-03-12 17:14:56 tony>
;;; File: procedures.lisp
;;; Author: AJ Rossini <blindglobe@gmail.com>
;;; Copyright: (c)2009--, AJ Rossini. Currently licensed under MIT
;;; license. See file LICENSE.mit in top-level directory
;;; for information.
;;; Purpose: Classes for statistical procedures, and generics
;;; supporting use of such procedures.
;;; What is this talk of 'release'? Klingons do not make software
;;; 'releases'. Our software 'escapes', leaving a bloody trail of
;;; designers and quality assurance people in its wake.
;;; This organization and structure is new to the 21st Century
;;; version.. Think, "21st Century Schizoid Man".
(in-package :cls-statproc)
;;; Statistical procedures can consist of one or more of:
;;; - mathematical forms: linear predictors, splines, functional
;;; forms) which get spliced together.
;;; - criteria functions (likelihoods, sum-of-squares, information), params and data.
;;; - optimization algorithmsfunctions
;;; - root functions (score functions, influence functions), params and data
;;; - zero-finding algorithms
;;; - point estimate: special case of...
;;; - interval estimation (with uncertainty criteria to support range or point)
;;; - hypothesis test -- which can be thought of as a point estimator
;;; for a coarsened problem, or as a simple interval-based decision with
;;; uncertanty criteria.
;;; Estimators are reaasonably straightforward. Either we are
;;; providing a point estimate, or we provide an interval estimate.
;;; But shouldn't these be characterized in the same manner?
;;; We are currently building up an ontology (ADG/DAG) or
;;; knowledge-base whose leaves are described by the path to them.
(defvar *statistical-procedure-components*
'((interval-estimation
(hypothesis-testing ; coarsened interval
(frequentist
(fisherian
(neyman-pearson
(wald-test
t-test
likelihood-ratio-test
score-test))))))
(point-estimation
maximum-likelihood-estimation)
()
optimization
root-finding
criteria-functions
mathematical-forms
))
(defclass statistical-ontology-class ()
()
(:documentation "container class for manipulation of structural components."))
(defclass statistical-decision ()
((ontology-classification :initform nil
:initarg :ontology-classification
:type statistical-ontology-class
))
(:documentation "instance describing the end result, if it is an
interval/range/region, or point estimate, or a conclusion from a
test (i.e. hypothesis(es) selected, strength of conclusion)"))
(defclass statistical-dataset (dataframe-like)
(:documentation "a particular dataset, usually the subset from a
larger set, which is used as the input to the procedure."))
(defclass statistical-metadata (dataframe-like)
(:documentation "the description of the dataset's statistical
properties which are required for the procedure to work or meet
assumptions."))
(defclass statistical-procedure ()
((ontological-spec :initform nil
:initarg :ontology-def
:type list
:accessor ontology
:documentation "list of symbols describing
ontological classification")
(how-to-fit)
(how-to-simulate)
(instance-data)))
;;;
(defgeneric proc-consistents-data-p (metadata data)
(:documentation "verify that the metadata required for a procedure
is present in a particular dataset. The dataset will usually be a
subset of the full working dataset."))
(defgeneric process-data (proc data)
(:documentation "Run the statistical procedure on the dataset and
report the decision."))
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