Conditional expectations – the expected values of random variables given a set of conditions – have all sorts of applications ... This can also be inferred from the data. Kienitz started with five to ...

and where the inference is conditionalizing the evidence using the conditional expectation determined by a reference probability measure representing the background subjective degrees of belief (prior ...

See the relationship between conditional and independent events in a statistical experiment. Calculate the expectation and variance of several ... the distribution of the mean of a large data set.

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 ...

The Conditional ... expectation of effectiveness in addressing an unmet medical need, but require complex and difficult studies to complete collection of definitive effectiveness data.