Variable selectionThis paper is concerned with identifying important features in high dimensional data analysis, especially when there are complex relationships among predictors. Without any specication of an actual model, we rst introduce a multiple testing procedure based on the quantile correlation to ...
The number of iterations of the Sequential MCMC sampler at each time \(m_{t}\) is determined based on the cross-chain correlation (see Guhaniyogi et al., 2018). Specifically, we set the number of iterations at time t, denoted as \(m_{t}\), to be the smallest integer s such that...
We attribute the excellent modelling capabilities, especially the very high coefficients of determination and cross- validation correlations to the models' ability to avoid the curse of dimensionality while retaining great flexibility in the regression function9. In addition,12 concurred w ith...
On the other hand, as a direct application, based on the new communication-efficient distributed CQR and the smooth-threshold estimating equations (Ueki 2009), we further propose a variable selection procedure for the massive data, which can also be realized on the first machine. Theoretically, ...
which is based on the quantile check function (Koenker and Bassett Jr1978). This has been extended to more flexible regression functions such as the quantile regression forest (Meinshausen2006) and the gradient forest (Athey et al.2019), which both build on the original random forest (Breiman20...
It produces a graphical map based on the forgoing statistical metrics that present the distance between the forecasting models and the observed river flow data set. From the Taylor diagrams, all the methods have similar correlation levels for Mary River and Lockyer Valley. On the other hand, ...
3, while the greatest correlation coefficient is about 0.87 for τ=0.4 and τ=0.9. If anything, there is weak evidence of a relative stronger correlation between In-degree and Out-degree for higher quantiles than for lower quantiles. 15 A firm might purchase allowances even when it ...
Specifying a correlation matrix is challenging in Fu,Liya,Wang,... - 《Journal of Multivariate Analysis An International Journal》 被引量: 1发表: 2016年 A two-part finite mixture quantile regression model for semi-continuous longitudinal data This paper develops a two-part finite mixture quantile...
Quantile regression models have become a widely used statistical tool in genetics and in the omics fields because they can provide a rich description of th
This result implies that for different quantile values q(w∗)≡q(w∗,τ) indexed by τ∈(0,1), the mean value of the random variable Z characterized by the density function fZ(z) in (9) is in the 45% degree line such that (x∗,y∗)=(E[Z],E[Z]). Second, we prove ...