Statistical convergence of complex uncertain sequences defined by Orlicz function
Pankaj Kumar Nath, Binod Chandra Tripathy
Abstract
Complex uncertain variables are measurable functions from an uncertainty space to the set of complex numbers and are used to model complex uncertain quantities. This paper introduces the statistical convergence concepts of complex uncertain sequences: statistical convergence almost surely(a.s.), statistical convergence in measure, statistical convergence in mean, statistical convergence in distribution and statistical convergence uniformly almost surely sequences of complex uncertain sequences defined by Orlicz function. In addition, Decomposition Theorems and relationships among them are discussed.
Topics & Concepts
Convergence (economics)MathematicsNormal convergenceFunction (biology)Convergence testsModes of convergence (annotated index)Compact convergenceStatistical modelSet (abstract data type)Weak convergenceMeasure (data warehouse)Applied mathematicsRate of convergenceComputer scienceDiscrete mathematicsStatisticsTopological spaceKey (lock)Data miningTopological vector spaceBiologyEconomic growthProgramming languageIsolated pointEvolutionary biologyAsset (computer security)EconomicsComputer securityApproximation Theory and Sequence SpacesMathematical Approximation and IntegrationHolomorphic and Operator Theory