Fragile X disorders include two distinct conditions: fragile X syndrome (the most common single-gene cause of developmental ...

Compared with commonly-used point forecasting, probabilistic forecasting provides quantitative information on the uncertainty associated with wind power output. However, most studies focus on ...

We provide an algorithm to build quantile regression trees in O(N log N) time, where N is the number of instances in the training set. Quantile regression trees are regression trees that model ...

In this paper we study doubly robust estimators of various average and quantile treatment effects under unconfoundedness; we also consider an application to a setting with an instrumental variable. We ...

It then gives tables to five places of values of the six trigonometric functions mentioned, as well as a table of decimal equivalents. In addition to this material, the pamphlet has a section on ...

The quantile regression model is a good alternative when the distributional assumptions do not hold. The quantile regression does not require distributional assumptions. The quantile regression fits ...

By allowing conditional functions to be specified at any point across the selected quantiles, quantile regression helps describe the whole conditional distribution of the responsive variables with ...

The PS.Est.Depth () function in the PoissonSeq package was used for its estimation. 7.Quantile normalization (QN) was inspired by quantile-quantile plot. This regression-based approach was originally ...