Modern longitudinal data, for example from wearable devices, may consist of measurements
of biological signals on a fixed set of participants at a diverging number of time-points …

We in this paper propose a semiparametric partially linear varying coefficient (SPLVC)
modal regression, in which the conditional mode function of the response variable given …

In this work, we propose a deep learning-based method to perform semiparametric
regression analysis for spatially dependent data. To be specific, we use a sparsely …

Health outcomes, such as body mass index and cholesterol levels, are known to be
dependent on age and exhibit varying effects with their associated risk factors. In this paper …

This paper empirically investigates how intensified competition in the Indian banking affects
the transmission of monetary policy through bank lending channel over the period 1997 …

The estimation and empirical likelihood (EL) of the parameters of interest in a partially linear
single-index varying-coefficient model are studied. A two-stage method is presented to …

Influential existing research has suggested that rather than being static, mortality declines
decelerate at young ages and accelerate at old ages. Without accounting for this feature, the …

Lack-of-fit testing is often essential in many applications of statistical/machine learning.
Despite the availability of large-scale datasets, the challenges associated with model …

In the article, we develop a quantile varying-coefficient structural equation model in which
the coefficients are allowed to vary as smooth functions of other variable at different …

The successful development and implementation of precision immuno-oncology therapies
requires a deeper understanding of the immune architecture at a patient level. T-cell …