Paper VI visual guide · Visual 34 of 42 · FIXED LIKELIHOODS / JOINT PROFILES

Several observations determine one sufficient partition

Traditional Part II: Theorem E9.3. A finite family of strictly positive likelihoods.

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On four states, consider two likelihoods

\[ \lambda^{(1)}=(2,2,1,1),\qquad \lambda^{(2)}=(1,1,3,1). \]

Two states may share a packet in the coarsest partition on which every listed likelihood is constant exactly when their entire likelihood profiles agree. The profiles are

\[ (2,1),\ (2,1),\ (1,3),\ (1,1), \]

so the partition is \(\{0,1\},\{2\},\{3\}\).

Four states are grouped by two-coordinate likelihood profiles.
Original drawing. Read the description below; expand the labels and data for selectable text.

Reading the drawing

The first two states share their displayed profile and are joined by a brace. The remaining states have separate profiles and are labelled as separate packets. The bottom formula identifies the joint profile being compared.

Drawing labels and data 8 labels

Read the original labels as selectable text. Tables preserve grid relationships; other short labels are grouped compactly.

state 0
\((2,1)\)

state 1
\((2,1)\)

state 2
\((1,3)\)

state 3
\((1,1)\)

  • one packet
  • separate packet
  • separate packet

Joint likelihood profile \(=(\lambda^{(1)}_i,\lambda^{(2)}_i)\)

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Evidence note from the source edition

The first observation alone allows the last two states to be merged. The second observation distinguishes them. The shared partition must respect both likelihoods.

A complete two-stage calculation

Start from the uniform prior. The coarse prior is \((1/2,1/4,1/4)\). After the first likelihood, it becomes \((2/3,1/6,1/6)\); after the second, it is

\[ (1/2,3/8,1/8). \]

The direct fine update multiplies the likelihoods componentwise, giving weights \((2,2,3,1)\) and posterior \((2,2,3,1)/8\). Its packet masses are precisely the displayed coarse posterior.

The individual evidences are \(Z_1=3/2\) and \(Z_2=4/3\), and their product is \(2\), the direct evidence of the product likelihood. These are relative likelihood weights, so evidence larger than one is allowed.

This partition supplies fixed coarse likelihoods that work for every prior. A single-packet aggregation always gives posterior \((1)\); that mass-only commutation does not identify likelihood profiles. A prior-dependent conditional average can summarize one update on a coarser partition, but requires the within-packet information that a fixed sufficient rule avoids.

Read this as

Equal full likelihood profiles determine the coarsest partition on which every listed likelihood is constant. This partition admits fixed sufficient update rules.

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