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Adaptive setting of prior probability on HR frame.
The effect of vehicle velocity, bridge surface roughness, and choice of prior probability density parameters on the efficiency of the method is discussed.
(4) The initial wrong choice of parameters of prior probability density function does not eventually lead to wrong estimate, except that the convergence time would increase.
(ii) Adaptive setting of prior probability on HR frame In the proposed method, the prior probability is adaptively set for the target video sequence.
But the only prior probability assignment that is invariant in this way is the assignment of prior probability of 1/2 to each of the two possibilities (i.e., that the ball drawn is black or that it is red).
Bayesian inference has the advantage of formally incorporating prior beliefs about the effect of an intervention into analyses of treatment effect through the use of prior probability distributions or "priors".
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We ranked the variables in increasing order of prior probabilities.
Let P(x i ) denotes the value of prior probabilities of X.
In particular, we do not assume any knowledge of prior probabilities.
This theorem implies that for large samples the values of prior probabilities don't matter much.
A Bayes ensemble model is based on the concept of prior probabilities [41, 42].
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