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Record W2127943740 · doi:10.1186/2193-1801-3-386

A characterization of Chover-type law of iterated logarithm

2014· article· en· W2127943740 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSpringerPlus · 2014
Typearticle
Languageen
FieldDecision Sciences
TopicProbability and Risk Models
Canadian institutionsLakehead University
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsLaw of the iterated logarithmIterated logarithmIterated functionCharacterization (materials science)Type (biology)CombinatoricsLogarithmRandom variableSequence (biology)MathematicsDiscrete mathematicsPhysicsStatisticsMathematical analysis

Abstract

fetched live from OpenAlex

ABSTRACT: Let 0 < α ≤ 2 and - ∞ <β <∞. Let {X n ;n ≥ 1} be a sequence of independent copies of a real-valued random variable X and set S n = X 1+⋯+X n , n ≥ 1. We say X satisfies the (α,β)-Chover-type law of the iterated logarithm (and write X∈C T L I L(α,β)) if [Formula: see text] almost surely. This paper is devoted to a characterization of X ∈C T L I L(α,β). We obtain sets of necessary and sufficient conditions for X∈C T L I L(α,β) for the five cases: α = 2 and 0 < β <∞, α = 2 and β = 0, 1<α<2 and -∞<β<∞, α = 1 and -∞ <β <∞, and 0 < α <1 and -∞ <β <∞. As for the case where α = 2 and -∞ <β <0, it is shown that X∉C T L I L(2,β) for any real-valued random variable X. As a special case of our results, a simple and precise characterization of the classical Chover law of the iterated logarithm (i.e., X∈C T L I L(α,1/α)) is given; that is, X∈C T L I L(α,1/α) if and only if [Formula: see text] where [Formula: see text] whenever 1< α ≤ 2. MATHEMATICS SUBJECT CLASSIFICATION 2000: Primary: 60F15; Secondary: 60G50.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.179
Threshold uncertainty score0.236

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.066
GPT teacher head0.333
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it