An individual’s acceptance of novelty depends on their emotions. We previously developed mathematical models emotional dimensions associated with novelty, such as arousal (i.e., surprise) and valence positivity negativity). The based Bayesian theorem have three parameters: prediction error, uncertainty external noise. Based Berlyne’s potential, we formulated an inverse U shape function arousal....

Abstract Bayesian fused lasso is one of the sparse methods, which shrinks both regression coefficients and their successive differences simultaneously. In this paper, we propose a modeling via horseshoe prior. By assuming prior on difference coefficients, proposed method enables us to prevent over-shrinkage those differences. We also nearly hexagonal operator for with shrinkage equality selecti...