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It is not the case that Regularity can be preserved for uncountable sample spaces by using hyperreal-valued probability functions
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Reasons For
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Reason for 1 of 2
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1.
Hyperreal-valued probability functions fail to satisfy countable additivity, undermining their status as genuine probability measures.
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2.
Without countable additivity, hyperreal probabilities cannot ground standard probabilistic reasoning about infinite sequences of events.
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3.
Kolmogorov's axioms, which require countable additivity, remain the only fully rigorous foundation for probability theory with empirical applicability.
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Reason for 2 of 2
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1.
Assigning infinitesimal probabilities requires adopting non-standard analysis, which depends on the axiom of choice and yields non-constructive, unverifiable probability values.
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2.
Non-uniqueness of hyperreal extensions means infinitely many incompatible regular hyperreal probability functions exist for the same sample space, making regularity indeterminate rather than preserved.
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Reasons Against
1 perspective
Reason against
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1.
There exists a regular hyperreal-valued probability function for the dart throw at [0, 1]
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2.
Each landing point in a hyperreal-valued assignment receives infinitesimal probability rather than 0
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