A New Efficient Expression for the Conditional Expectation of the Blind Adaptive Deconvolution Problem Valid for the Entire Range ofSignal-to-Noise Ratio [PDF]
Entropy, 2019 In the literature, we can find several blind adaptive deconvolution algorithms based on closed-form approximated expressions for the conditional expectation (the expectation of the source input given the equalized or deconvolutional output), involving ...
Monika Pinchas
doaj +3 more sources
Copula conditional tail expectation for multivariate financial risks
Arab Journal of Mathematical Sciences, 2018 Our goal in this paper is to propose an alternative risk measure which takes into account the fluctuations of losses and possible correlations between random variables.
Brahimi Brahim +2 more
doaj +3 more sources
NONLINEAR GLOBAL FRÉCHET REGRESSION FOR RANDOM OBJECTS VIA WEAK CONDITIONAL EXPECTATION. [PDF]
Ann Stat, 2023 Random objects are complex non-Euclidean data taking values in general metric spaces, possibly devoid of any underlying vector space structure. Such data are becoming increasingly abundant with the rapid advancement in technology.
Bhattacharjee S, Li B, Xue L.
europepmc +3 more sources
Operational meanings of a generalized conditional expectation in quantum metrology [PDF]
Quantum, 2023 A unifying formalism of generalized conditional expectations (GCEs) for quantum mechanics has recently emerged, but its physical implications regarding the retrodiction of a quantum observable remain controversial.
Mankei Tsang
doaj +3 more sources
Estimating the tail conditional expectation of Walmart stock data
Croatian Operational Research Review, 2020 Stable distribution, also known as Lévy stable distribution, which is a rich class of heavy-tailed distributions can capture asymmetry and heavy tails observed in financial data.
Hakim Ouadjed, Tawfiq Fawzi Mami
doaj +2 more sources
Conditional Tail Expectation and Premium Calculation under Asymmetric Loss [PDF]
Axioms, 2023 In this paper, we calculate premiums that are based on the Conditional Tail Expectation (CTE) and asymmetric loss functions to account for the risk of both underestimation and overestimation losses.
Enrique Calderín-Ojeda +2 more
doaj +2 more sources
Specification of the Conditional Expectation by Simple Linear Regression Model For Binomial Distribution Conditioned with Varying Sample Size. [PDF]
المجلة العراقية للعلوم الاحصائية, 2009 In this research, we consider the study of conditional expectation and it's relationship with regression model. The conditional expectation has a linear form which is specified as a simple linear regression model. The power transformation was used on the
هيثم طه اليوسف
doaj +3 more sources
Parameter estimation via conditional expectation: a Bayesian inversion [PDF]
Advanced Modeling and Simulation in Engineering Sciences, 2016 When a mathematical or computational model is used to analyse some system, it is usual that some parameters resp. functions or fields in the model are not known, and hence uncertain.
Hermann G. Matthies +3 more
openalex +3 more sources
Reduced-Order Models and Conditional Expectation: Analysing Parametric Low-Order Approximations
ComputationSystems may depend on parameters that can be controlled, serve to optimise the system, are imposed externally, or are uncertain. This last case is taken as the “Leitmotiv” for the following discussion.A reduced-order model is produced from the full-order
Hermann G. Matthies
doaj +2 more sources
Pricing Vulnerable Options Using Conditional Expectation Transform Methods
Discrete Dynamics in Nature and SocietyIn this study, a conditional expectation transform (CET) method was developed for solving high-dimensional systems arising in vulnerable options pricing.
Han Wang
doaj +2 more sources