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It is not the case that The conditions required for maximum likelihood estimation to be provably consistent do not apply to estimating tree topology
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Reasons For
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Reason for
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1.
Wald's (1949) consistency conditions apply to continuous parameters
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2.
Tree topologies are discrete, not continuous, parameters
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Reasons Against
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Reason against 1 of 2
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1.
Steel and Matsen (2007) demonstrated that maximum likelihood can favor the wrong tree topology with probability approaching 1 under certain substitution models.
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2.
A consistent estimator cannot systematically converge on incorrect values as data increases, so topology estimation fails the formal definition of consistency in the frequentist sense.
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3.
The discreteness objection conflates the domain of parameters with the convergence properties that define consistency, leaving the core inapplicability claim intact.
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Reason against 2 of 2
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1.
Wald's consistency proof requires the parameter space to be compact, but the space of tree topologies grows super-exponentially with taxa count.
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2.
Non-compact discrete spaces violate identifiability conditions that Wald's framework presupposes, making consistency proofs inapplicable regardless of continuity distinctions.
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