From 88b057b4986cff105c66a1c5db8b01cd7ab28863 Mon Sep 17 00:00:00 2001
From: AJ Rossini <blindglobe@gmail.com>
Date: Fri, 12 Oct 2012 10:51:36 +0200
Subject: [PATCH] using the t-test, walk through possible inferential APIs,
 considering whether it is possible to have a simple language to characterise
 procedures.

Note that there could be MULTIPLE ALGORITHMS which implement procedures.   Recall conversations about RG's confusion about convex minorants and the EM-style algorithms.

Signed-off-by: AJ Rossini <blindglobe@gmail.com>
---
 examples/50-TTestExample.lisp | 51 ++++++++++++++++++++++++++++++++++++++++++-
 1 file changed, 50 insertions(+), 1 deletion(-)

diff --git a/examples/50-TTestExample.lisp b/examples/50-TTestExample.lisp
index 7a9544f..79ac427 100644
--- a/examples/50-TTestExample.lisp
+++ b/examples/50-TTestExample.lisp
@@ -1,6 +1,6 @@
 ;;; -*- mode: lisp -*-
 
-;;; Time-stamp: <2012-10-12 08:55:28 tony>
+;;; Time-stamp: <2012-10-12 10:44:00 tony>
 ;;; Creation:   <2009-04-19 09:41:09 tony>
 ;;; File:       t-test-example.lisp
 ;;; Author:     AJ Rossini <blindglobe@gmail.com>
@@ -25,3 +25,52 @@
   "Initial read-in of data.")
 
 
+;;;; possible APIs...
+
+#|
+
+summarize what how send-to
+
+what: df, stat-proc
+how:  numerically, visually, all, default
+send-to: output, file, visual, all, default
+ 
+
+compare in-model parameters framework philosophy assumptions
+
+in-model: regression two-group 
+parameters: means, "explicit choices", variances, means-and-variances, rates, proportions, hazards
+framework: fisherian, neyman-pearson, empirical-bayes
+philosophy: frequentist, bayesian, fiducial, decision-theoretic,
+assumptions: (list 'apply 'ignore 'explore) ; any or all of list entries
+
+
+FIXME: where would empirical bayes go?  part is a model, part is a philosophy.  framework?
+FIXME: decision-theoretic adds risk to the decision, making 
+
+the in-model objects need to be able to reflect their own assumptions and preferences, 
+
+|# 
+
+
+;;; The traditional intro-stat variant
+
+(summarize
+ (compare :parameter 'mean
+	  :comparison 'two-groups
+	  :group1 datapackage:variable1
+	  :group2 datapackage:variable2
+	  :assumptions (list 'apply 'ignore 'explore) ; any or all of list entries
+	  ) 
+ :resulttype (list 'numerical 'visual) 
+ )  ; any or all of list entries
+
+;;; the "know-your-dataset" variant
+
+(summarize
+ (compare :parameter 'mean
+	  :resulttype (list 'numerical 'visual)
+	  :comparison 'two-groups
+	  :variable datapackage:comparing-variable ; or response-variable
+	  :group-by datapackage:grouping-variable))
+
-- 
2.11.4.GIT