Results 71 to 80 of about 121 (117)
, 2020 . We estimate density and regression functions for weak dependant datas. Using an exponential inequality obtained in [DeP] and in [Mau2], we control the deviation between the estimator and the function itself.
-Véronique Maume-Deschamps +1 more
core
Bounds For A Class Of Stochastic Recursive Equations
, 1999 In this note we develop a framework for computing upper and lower bounds of an exponential form for a class of stochastic recursive equations with uniformly recurrent Markov modulated inputs.
Don Towsley, Zhen Liu, Philippe Nain
core
Error analysis for l q -coefficient regularized moving least-square regression. [PDF]
J Inequal Appl, 2018 Guo Q, Ye P.
europepmc +1 more source
Let X_i be nonnegative independent random variables with finite expectations and X^*_n = max {X_1, ..., X_n}. The value EX^*_n is what can be obtained by a ``prophet".
David Assaf, Ester Samuel-Cahn
core
Convergence rate for the moving least-squares learning with dependent sampling. [PDF]
J Inequal Appl, 2018 Guo Q, Ye P.
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The almost sure local central limit theorem for products of partial sums under negative association. [PDF]
J Inequal Appl, 2018 Jiang Y, Wu Q.
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A Probabilistic Characterization of Negative Definite Functions. [PDF]
High Dimens Probab, 2019 Gao F.
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Let X1,...,Xn be independent exponential random variables with respective hazard rates [lambda]1,...,[lambda]n, and let Y1,...,Yn be independent exponential random variables with common hazard rate [lambda].
Balakrishnan, N., Li, Xiaohu, Zhao, Peng
core
Complete convergence of randomly weighted END sequences and its application. [PDF]
J Inequal Appl, 2017 Li P, Li X, Wu K.
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