On the Convergence and Law of Large Numbers for the Non-Euclidean Lp -Means
Space Science and Engineering, Southwest Research Institute, San Antonio, TX 78238, USA
Academic Editors: Antonio Maria Scarfone and Kevin Knuth
Received: 18 January 2017 / Revised: 13 April 2017 / Accepted: 9 May 2017 / Published: 11 May 2017
This paper describes and proves two important theorems that compose the Law of Large Numbers for the non-Euclidean
-means, known to be true for the Euclidean
-means: Let the
-mean estimator, which constitutes the specific functional that estimates the
-mean of N
independent and identically distributed random variables; then, (i) the expectation value of the
-mean estimator equals the mean of the distributions of the random variables; and (ii) the limit
-mean estimator also equals the mean of the distributions.
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MDPI and ACS Style
Livadiotis, G. On the Convergence and Law of Large Numbers for the Non-Euclidean Lp -Means. Entropy 2017, 19, 217.
Livadiotis G. On the Convergence and Law of Large Numbers for the Non-Euclidean Lp -Means. Entropy. 2017; 19(5):217.
Livadiotis, George. 2017. "On the Convergence and Law of Large Numbers for the Non-Euclidean Lp -Means." Entropy 19, no. 5: 217.
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