Theoretical analysis reveals rough ideal statistical convergence criteria for complex double sequences, highlighting structural relationships across uncertainty modes.
In this paper, we introduce the notion of rough ℐ 2 {I₂} -statistical convergence (denoted as r - 𝒮 ( ℐ 2 ) {r-S(I₂)} -convergence) of complex uncertain double sequences in four fundamental aspects of uncertainty, namely almost sure, measure, mean, and distribution. This framework extends the existing notion of rough ℐ {I} -convergence for complex uncertain sequences to the broader setting of double sequences. In addition, we investigate r - 𝒮 ( ℐ 2 ) {r-S(I₂)} -convergence in p -distance and r - 𝒮 ( ℐ 2 ) {r-S(I₂)} -convergence in metric for complex uncertain double sequences. Overall, this study provides a comprehensive diagrammatic illustration of the interrelationships among the various r - 𝒮 ( ℐ 2 ) {r-S(I₂)} -convergence concepts and offers some significant observations highlighting their distinctions, supported by illustrative examples.
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Hossain et al. (2026) studied this question.
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