p(t | x) t x x x = 0.8 = 0.5 = 0.2 Figure 7: Plot of the conditional probability densities of the target data, for various values of x, obtained by taking vertical slices through the contours in Figure 6, for x = 0:2, x = 0:5 and x = 0:8. It is clear that the Mixture Density Network is able to capture correctly the multimodal nature of the target data density function at intermediate values of ...

Abstract We present a method for measuring the weak phase γ using isospin analysis of three body B decays into Kππ channels. Differential decay widths and time dependent asymmetry in Bd → KSπ π mode needs to be measured into even isospin ππ states. The method can be used to extract γ, as well as, the size of the electroweak penguin contributions. The technique is free from assumptions like SU(3...

The discriminating variable (DIVA) test and the selectivity ratio (SR) plot are developed as quantitative tools for revealing the variables in spectral or chromatographic profiles discriminating best between two groups of samples. The SR plot is visually similar to a spectrum or a chromatogram, but with the most intense regions corresponding to the most discriminating variables. Thus, the varia...

The validity of the normal distribution as an error model is commonly tested with a (half) normal probability plot. Real data often contain outliers. The use of t-distributions in a probability plot to model such data more realistically is described. It is shown how a suitable value of the parameter nu of the t-distribution can be determined from the data. The results suggest that even data tha...

A new algorithm for the estimation of probability density functions has been considered in the paper. This founds a large number of applications in the context of statistical signal processing problems, such as detection, estimation, filtering or pattern recognition and classification. The proposed approach relies on the QQ-plot technique. The estimates of the first and second order statistics ...