Explore related knowledge and questions →

Question 585: One Fixed Parameter-Independent Tie Order Produces a Total Finite Estimator

On this page
  1. Original question and givens
  2. Definition and scope
  3. Step-by-step derivation
  4. Reverse checks
  5. Result
  6. This question review and source binding

Return to catalogue page 3

← Question derivation index · Original question batch

P1000-0585 · q-20261015-advance-20261116-r04-finite-maximum-likelihood-estimator-0060

Original question and givens

Use complete theta labels=[a9, b9], observations=[x9, y9] and aligned exact probability rows=[[[3, 4], [1, 4]], [[1, 4], [3, 4]]]. Each theta row is nonnegative and sums to1. Sort labels with their associated rows/columns, never independently. Tie order=[a9, b9] is one complete parameter permutation, fixed independently of the unknown theta. Give (tie_order, estimator_rows, total_estimator, certificate).

  • G001 — Use complete theta labels=[a9, b9], observations=[x9, y9] and aligned exact probability rows=[[[3, 4], [1, 4]], [[1, 4], [3, 4]]]. Each theta row is nonnegative and sums to1. Sort labels with their associated rows/columns, never independently. Tie order=[a9, b9] is one complete parameter permutation, fixed independently of the unknown theta. Give (tie_order, estimator_rows, total_estimator, certificate).

Definition and scope

Keep each observation's complete argmax, then pick the first member in one fixed parameter-independent tie order, giving a total estimator.

Step-by-step derivation

S001 · implies

Before

Θ=[a9, b9]; Ω=[x9, y9]

After

[[3/4, 1/4], [1/4, 3/4]]

Conditions: none

Each row is one parameter law and each column an outcome; reorder probabilities together with labels.

Step identifiers and dependencies

Rule: full_parametric_model · Uses: G001

S002 · calculation

Before

P_a9(Ω) := sum(3/4, 1/4)

After

P_a9(Ω) = 1

Conditions: none

Check this law's complete total mass first.

Step identifiers and dependencies

Rule: exact_rational_arithmetic · Uses: G001, S001

S003 · calculation

Before

P_b9(Ω) := sum(1/4, 3/4)

After

P_b9(Ω) = 1

Conditions: none

Check this law's complete total mass first.

Step identifiers and dependencies

Rule: exact_rational_arithmetic · Uses: G001, S002

S004 · implies

Before

tie priority=[a9, b9]

After

one fixed ordering, independent of the observed outcome

Conditions: none

Declare one fixed tie order, then choose its first member within each complete argmax.

Step identifiers and dependencies

Rule: fixed_tie_rule · Uses: G001, S003

S005 · implies

Before

parameter=a9; observed=x9

After

L(a9;x9)=3/4

Conditions: none

Fix the observation and compare its column across parameters, without introducing a prior.

Step identifiers and dependencies

Rule: fixed_likelihood_lookup · Uses: G001, S004

S006 · implies

Before

parameter=b9; observed=x9

After

L(b9;x9)=1/4

Conditions: none

Fix the observation and compare its column across parameters, without introducing a prior.

Step identifiers and dependencies

Rule: fixed_likelihood_lookup · Uses: G001, S005

S007 · implies

Before

[[a9, 3/4], [b9, 1/4]]

After

maximum=3/4; all argmax=[a9]

Conditions: none

Retain every maximizer; for an all-zero column the complete argmax is still all parameters.

Step identifiers and dependencies

Rule: complete_argmax · Uses: G001, S006

S008 · implies

Before

argmax(x9)=[a9]; priority=[a9, b9]

After

estimator(x9)=a9

Conditions: none

The selector is single-valued; the original argmax need not be a singleton.

Step identifiers and dependencies

Rule: deterministic_tie_selection · Uses: G001, S007

S009 · implies

Before

parameter=a9; observed=y9

After

L(a9;y9)=1/4

Conditions: none

Fix the observation and compare its column across parameters, without introducing a prior.

Step identifiers and dependencies

Rule: fixed_likelihood_lookup · Uses: G001, S008

S010 · implies

Before

parameter=b9; observed=y9

After

L(b9;y9)=3/4

Conditions: none

Fix the observation and compare its column across parameters, without introducing a prior.

Step identifiers and dependencies

Rule: fixed_likelihood_lookup · Uses: G001, S009

S011 · implies

Before

[[a9, 1/4], [b9, 3/4]]

After

maximum=3/4; all argmax=[b9]

Conditions: none

Retain every maximizer; for an all-zero column the complete argmax is still all parameters.

Step identifiers and dependencies

Rule: complete_argmax · Uses: G001, S010

S012 · implies

Before

argmax(y9)=[b9]; priority=[a9, b9]

After

estimator(y9)=b9

Conditions: none

The selector is single-valued; the original argmax need not be a singleton.

Step identifiers and dependencies

Rule: deterministic_tie_selection · Uses: G001, S011

S013 · implies

Before

defined on 2 outcomes

After

total on all 2 listed outcomes

Conditions: none

Every listed outcome has an output, including an outcome null under all laws.

Step identifiers and dependencies

Rule: total_estimator · Uses: G001, S012

Reverse checks

  • S013 · premise_and_result_audit — Retain every parameter and sample label; distinguish null, empty tables, zero distributions and tied optima.
  • S012 · premise_and_result_audit — Retain every parameter and sample label; distinguish null, empty tables, zero distributions and tied optima.
  • S011 · premise_and_result_audit — Retain every parameter and sample label; distinguish null, empty tables, zero distributions and tied optima.
  • S010 · premise_and_result_audit — Retain every parameter and sample label; distinguish null, empty tables, zero distributions and tied optima.
  • S009 · premise_and_result_audit — Retain every parameter and sample label; distinguish null, empty tables, zero distributions and tied optima.
  • S008 · premise_and_result_audit — Retain every parameter and sample label; distinguish null, empty tables, zero distributions and tied optima.
  • S007 · premise_and_result_audit — Retain every parameter and sample label; distinguish null, empty tables, zero distributions and tied optima.
  • S006 · premise_and_result_audit — Retain every parameter and sample label; distinguish null, empty tables, zero distributions and tied optima.
  • S005 · premise_and_result_audit — Retain every parameter and sample label; distinguish null, empty tables, zero distributions and tied optima.
  • S004 · premise_and_result_audit — Retain every parameter and sample label; distinguish null, empty tables, zero distributions and tied optima.
  • S003 · premise_and_result_audit — Recompute P_b9(Ω) with exact rational arithmetic, not rounded decimals.
  • S002 · premise_and_result_audit — Recompute P_a9(Ω) with exact rational arithmetic, not rounded decimals.
  • S001 · premise_and_result_audit — Retain every parameter and sample label; distinguish null, empty tables, zero distributions and tied optima.

Result

([a9, b9], [[x9, [a9], a9], [y9, [b9], b9]], Yes, theta_independent_tie_rule_makes_a_total_estimator)

The full substitutions and premise audits recover the original answer, retaining its field order and verdict meanings.

This question review and source binding

Review date: 2026-10-26

Original questions, answers, step expressions, numeric ASTs and historical records are retained. Source candidate labels remain historical and are not overwritten as formal proof.

Source hashes and review receipts
  • input commit: 0f7be61e2c22317a4075561dc822c87d881a50db
  • original question SHA-256: 1c7792ce0e3bdb24ace55a8b0120c64256802b0aa61c3fbfc4e58b59c9cf0eb9
  • candidate record SHA-256: 9099ca638ddf7b9fb9eabe3ecd09613b090501b438f939ad3703baced6f860ae
  • semantic review receipt SHA-256: 6c2c6d46aded7582a11ac41a8c0b3bdde2669a53bdb6e796eea2039994a02772
  • question-first witness SHA-256: 77e43898df9efdbf8094ad81fe4ab91cf4b4bd82f481eb9b4699b73cb4da612b
  • Lean: NOT_RUN · human review: NOT_PERFORMED
Same-source full JSON