Results 271 to 280 of about 139,835 (302)
Some of the next articles are maybe not open access.
2017
This chapter gives the basic theory of almost sure convergence and Kolmogorov’s strong law of large numbers (1933) according to which the empirical mean of an iid sequence of integrable random variables converges almost surely to the probabilistic mean (the expectation).
openaire +1 more source
This chapter gives the basic theory of almost sure convergence and Kolmogorov’s strong law of large numbers (1933) according to which the empirical mean of an iid sequence of integrable random variables converges almost surely to the probabilistic mean (the expectation).
openaire +1 more source
Regularity and almost sure convergence
1995Summary: We give a sufficient condition for almost sure convergence in the sense of \textit{E. Hensz} and \textit{R. Jajte} [Math. Z. 193, 413-429 (1986; Zbl 0613.46056)] to be equivalent to almost uniform convergence.
openaire +1 more source
An almost convergence and its applications
1978Artykuł w: Annales Universitatis Mariae Curie-Skłodowska. Sectio A, Mathematica. Vol. 32 (1978), s. 79-88 ; streszcz. pol., ros. ; Artykuł w: Annales Universitatis Mariae Curie-Skłodowska. Sectio A, Mathematica. Vol. 32 (1978), s. 79-88 ; streszcz. pol., ros.
openaire +1 more source
2016
We have seen in Part II the importance of a.e. convergence in integration theory. The purpose of this last chapter of our book is to clarify its relationship to other convergence notions.
openaire +1 more source
We have seen in Part II the importance of a.e. convergence in integration theory. The purpose of this last chapter of our book is to clarify its relationship to other convergence notions.
openaire +1 more source
Strongly almost convergence in sequences of complex uncertain variables
Communications in Statistics - Theory and Methods, 2023Binod Chandra Tripathy +2 more
exaly
2012
This chapter studies essentially Strong Laws of Large Numbers (SLLN) for associated variables and their applications to the characterization of asymptotics of statistical estimators under associated sampling. It is possible to prove SLLN under fairly general assumptions, but, in order to prove characterizations of convergence rates, a closer care on ...
openaire +1 more source
This chapter studies essentially Strong Laws of Large Numbers (SLLN) for associated variables and their applications to the characterization of asymptotics of statistical estimators under associated sampling. It is possible to prove SLLN under fairly general assumptions, but, in order to prove characterizations of convergence rates, a closer care on ...
openaire +1 more source
Tauberian Conditions for Almost Convergence in a Geodesic Metric Space
Results in Mathematics, 2020Hadi Pouladi +2 more
exaly
Nörlund Means and Almost Convergence
Journal of the London Mathematical Society, 1978openaire +2 more sources