Nonresponse weighting adjustment using the response propensity score is a popular tool for handling unit nonresponse. Statistical inference after the nonresponse weighting adjustment is an important ...

Approximate Bayesian Computation (ABC) is a likelihood‐free inference methodology that has revolutionised the way researchers tackle complex problems where the likelihood function is difficult or ...

Figure 1: Models of the owl's behavior. Figure 2: Predicted behavior under varying levels of interaural correlation. The s.d. of the prior in the model was 23.3 degrees. This causes the estimator to ...

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...

The Helsinki Probabilistic Machine Learning Lab encompasses seven at the Department of Computer Science of the University of Helsinki, all specializing in probabilistic machine learning methods and ...