One of the more difficult challenges for modeling is deciding how (or if) to deal with extreme data points. It’s a common problem in economic and financial numbers. Fat tailed distributions are ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of neural network quantile regression. The goal of a quantile regression problem is to predict a single numeric ...

The goal of a machine learning regression problem is to predict a single numeric value. Quantile regression is a variation where you are concerned with under-prediction or over-prediction. I'll phrase ...

Bayesian quantile regression and statistical modelling represent a growing paradigm in contemporary data analysis, extending conventional regression by estimating various conditional quantiles rather ...

Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 80, No. 5 (2018), pp. 975-993 (19 pages) Estimating conditional quantiles of financial time series is essential for ...

The association between two event times is of scientific importance in various fields. Due to population heterogeneity, it is desirable to examine the degree to which local association depends on ...

Immunotherapy has been approved to treat many tumor types. However, one characteristic of this therapeutic class is that survival benefit is due to late immune response, which leads to a delayed ...