Results 271 to 280 of about 163,760 (356)

Avoiding subtraction and division of stochastic signals using normalizing flows: NFdeconvolve. [PDF]

iScience
Pessoa P, Schweiger M, Xu LWQ, Manha T, Saurabh A, Camarena JA, Pressé S.   +6 more
europepmc   +1 more source

Machine learning analysis of Iran's wildfire landscape and anthropogenic influences. [PDF]

Sci Rep
Sadra N, Nikoo MR, Nazari R, Karimi M, Uddin MG, Gandomi AH.   +5 more
europepmc   +1 more source

Utility of ¹⁸F-Florzolotau PET as a prognostic and monitoring biomarker in a memory clinic cohort. [PDF]

Alzheimers Res Ther
Lu J, Wang J, Zhang H, Wu J, Yang Y, Wang M, Ma X, Bao W, Xiao Z, Lin H, Zhou X, Ju Z, Yan S, Jiao F, Liang X, Liu Y, Zheng L, Li M, Ge J, Ding D, Yen TC, Guan Y, Zuo C, Zhao Q.   +23 more
europepmc   +1 more source

Runtime Monitoring of Static Fairness Properties

Henzinger TA, Karimi M, Kueffner K, Mallik K.   +3 more
europepmc   +1 more source

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Sums of Independent Random Variables

2010
The classical large-sample theory is about the sum of independent random variables. Even though large-sample techniques have expanded well beyond the classical theory, the foundation set up by the latter remains the best way to understand and further explore elements of large-sample theory.
Jiming Jiang
semanticscholar   +3 more sources

Sum of Independent Random Variables

2016
Masashi Sugiyama
openaire   +2 more sources

Recurrence relations for the joint distribution of the sum and maximum of independent random variables

Journal of Applied Analysis, 2023
In this paper, the joint distribution of the sum and maximum of independent, not necessarily identically distributed, nonnegative random variables is studied for two cases: (i) continuous and (ii) discrete random variables.
Christos N. Efrem
semanticscholar   +1 more source

Conditional expectations given the sum of independent random variables with regularly varying densities

ASTIN Bulletin: The Journal of the International Actuarial Association
The conditional expectation $m_{X}(s)=\mathrm{E}[X|S=s]$ , where X and Y are two independent random variables with $S=X+Y$ , plays a key role in various actuarial applications. For instance, considering the conditional mean risk-sharing rule, $m_X(s)
Michel Denuit, P. Ortega-Jiménez, Christian Y. Robert   +2 more
semanticscholar   +1 more source

Sums of Independent Random Variables

1991
Sums of independent random variables already appeared in the preceding chapters in some concrete situations (Gaussian and Rademacher averages, representation of stable random variables). On the intuitive basis of central limit theorems which approximate normalized sums of independent random variables by smooth limiting distributions (Gaussian, stable),
Michel Ledoux, Michel Talagrand
openaire   +2 more sources