Conditional expectations – the expected values of random variables given a set of conditions – have all sorts of applications, ranging from the pricing of exotic and out-of-the-money options to the ...

This talk investigates the general properties of general Bayesian learning, where “general Bayesian learning” means inferring a probability measure from another that is regarded as (uncertain) ...

See the relationship between conditional and independent events in a statistical experiment. Calculate the expectation and variance of several random variables and develop ... we’ll introduce the CLT ...

Gaussian mixture model dynamically controlled kernel estimation (GMM-DCKE), a purely data-driven and model-agnostic method to compute conditional expectations, is introduced. Joerg Kienitz applies it ...

Probabilistic Outcomes Are Valued Less in Expectation, Even Conditional on Their Realization Published:11/10/2024 11/10/2024 Most theories of decision making under risk assume that payoffs and ...