Exact(2)
Since the Bayesian data-worth analysis involves a great deal of expectation estimation, the cost saving of the MLMC in the assessment can be outstanding.
In the product-shift-experiment [ R n, (left.,;left {widetilde {P}^{times n}_{mu },muu in Rright }right ]), expectation estimation and testing may be done as in Sections 2 and 3, respectively, where g 1=B ′′′/(B ′′3/2 and g 2 allows a similar representation.
Similar(58)
First, the stimulus design is flexible and need not be a frequency progression, thereby reducing biases due to habituation, expectation, and estimation artifacts, as well as reducing the effects of spatio-temporal BOLD nonlinearities.
These items were subjected to Expectation Maximisation Estimation using SPSS Missing Values procedure [ 17]. Figure 1 reports the instrument structure and results of the SEM analysis.
Thus, they were estimated using the expectation-maximization estimation method.
In addition, missing HRQoL outcomes were handled through the Expectation-Maximization estimation method (SPSS 16.0).
The method relies upon a hierarchical CPM with hyperparameters estimated using an expectation maximization MAP estimation procedure.
The theory only utilizes the expectation of reward estimation; however, in many cases, the estimation contains uncertainty (Rushworth & Behrens, 2008).
A one-dimensional bell model is developed providing an approximate theoretical expectation to which estimation results may be compared.
These models are based upon principles of mean-square error minimization, conditional expectations and stochastic estimation.
Recently, a Space-Alternating Generalized Expectation-maximization (SAGE) estimation approach was introduced in [13] which is derived based on a parametric model characterizing the SC's output, allowing the estimation of multipath parameters by using higher-frequency components.
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