0000000001267967
AUTHOR
V Muggeo
Non-crossing quantile regression via monotone B-spline varying coefficients
Quantile regression can be used to obtain a nonparametric estimate of a conditional quantile function. The presence of quantile crossing, however, leads to an invalid distribution of the response and makes it dicult to use the tted model for prediction. In this work, we show that crossing can be alleviated or completely eliminated by explicit modeling of the regression coecients as a function of the percentile values in (0,1). We illustrate the approach via a wellknown dataset by emphasizing dierences with respect to the competitors.
A new tuning parameter selector in lasso regression
Penalized regression models are popularly used in high-dimensional data analysis to carry out variable selction and model fitting simultaneously. Whereas success has been widely reported in literature, their performance largely depend on the tuning parameter that balances the trade-off between model fitting and sparsity. In this work we introduce a new tuning parameter selction criterion based on the maximization of the signal-to-noise ratio. To prove its effectiveness we applied it to a real data on prostate cancer disease.
References growth charts: a new practical tool for comparing Posidonia oceanic growth patterns accounting for age and depth
Over the past three decades an increasing amount of dating records dealing with Posidonia oceanica growth performance was incorporated into a variety of studies, from which a dualistic nature of the factors influencing seagrass growth arose. A large amount of literature focused on the role of exogenous factors in explaining rhizome growth variations, while only few studies invoked the importance of endogenous factors in driving growth. A particular attention was paid on the confounding role of shoot age, as endogenous factor, when the effect of exogenous variables on growth performance is analyzed. Shoot age confounding implies serious interpretation problems, since it is difficult to disti…