In this paper, we conduct a theoretical examination of a low-rank matrix single-index model. This model has recently been introduced in the field of biostatistics, but its theoretical properties for jointly estimating the link function and the coeffi...
As applied sciences grow by leaps and bounds, semiparametric regression analyses have broad applications in various fields, such as engineering, finance, medicine, and public health. Single-index varying-coefficient model is a common class of semipar...
We study the non-parametric estimation of partially linear generalized single-index functional models, where the systematic component of the model has a flexible functional semi-parametric form with a general link function. We suggest an efficient an...
Model checking methods based on non-parametric estimation are widely used because of their tractable limiting null distributions and being sensitive to high-frequency oscillation alternative models. However, this kind of test suffers from the curse o...
As spatial correlation and heterogeneity often coincide in the data, we propose a spatial single-index varying-coefficient model. For the model, in this paper, a robust variable selection method based on spline estimation and exponential squared loss...
In this paper, we introduce two semiparametric single-index models for spatially and temporally correlated data. Our first model has spatially and temporally correlated random effects that are additive to the nonparametric function, which we refer to...
In this paper, the spatial dynamic panel data (SDPD) model is extended to the single-index spatial dynamic panel data (Si-SDPD) model by introducing a nonlinear connection function to reflect the interaction between explanatory variables. The Si-SDPD...
In this study, we propose a novel penalized empirical likelihood approach that simultaneously performs parameter estimation and variable selection in heteroscedastic partially linear single-index models with a diverging number of parameters. It is ri...
To better fit the actual data, this paper will consider both spatio-temporal correlation and heterogeneity to build the model. In order to overcome the “curse of dimensionality” problem in the nonparametric method, we improve the estimati...
The single-index model is an intuitive extension of the linear regression model. It has been increasingly popular due to its flexibility in modeling. In this work, we focus on the estimators of the parameters and the unknown link function for the sin...
Complex diseases such as type 2 diabetes are influenced by both environmental and genetic risk factors, leading to a growing interest in identifying gene–environment (G × E) interactions. A three-step variable selection method for single-...
Single-index models are potentially important tools for multivariate non-parametric regression analysis. They generalize linear regression models by replacing the linear combination
We propose a robust procedure to estimate the conditional mode of a univariate outcome O given a Hilbertian explanatory variable I, under the assumption that
For portfolios with a large number of assets, the single index model allows for expressing the large number of covariances between individual asset returns through a significantly smaller number of parameters. This avoids the constraint of having ver...
The variable selection problem is studied in the sparse semi-functional partial linear model, with single-index type influence of the functional covariate in the response. The penalized least squares procedure is employed for this task. Some properti...
A new sparse semiparametric functional model is proposed, which tries to incorporate the influence of two functional variables in a scalar response in a quite simple and interpretable way. One of the functional variables is included trough a single-i...
This research uses Sharpe’s single-index model to analyze voting results in corporate meetings, thus assessing whether voting results at the corporate level are influenced by aggregated voting results at the industry level. We use a sample of v...
Precision medicine tailored to individual patient characteristics is crucial for improving long-term health outcomes. In survival analysis, a significant challenge for learning an optimal treatment regimen is to handle censoring, which is ubiquitous...
In this paper, we develop kernel-based estimators for regression functions under a functional single-index model, applied to censored time series data. By capitalizing on the single-index structure, we reduce the dimensionality of the covariate-respo...
Parametric regression methods are efficient when correctly specified but are sensitive to model misspecification and outliers. Nonparametric regression offers greater flexibility at the cost of reduced interpretability and susceptibility to the curse...
A new predictor in functional time series (FTS ) is considered. It is based on the asymmetric weighting function of quantile regression. More precisely, we assume that FTS is generated from a single-index model that permits the observation of endogen...
There has been a lot of interest in sufficient dimension reduction (SDR) methodologies, as well as nonlinear extensions in the statistics literature. The SDR methodology has previously been motivated by several considerations: (a) finding data-driven...
This paper develops a unified asymptotic theory for conditional single-index U-statistics and the associated conditional U-processes in the setting of locally stationary functional time series subject to missing-at-random response mechanisms. The pro...
We study bias-corrected empirical-likelihood inference for single-index expectile regression when responses are missing at random. Local-linear expectile estimation is combined with conditional centering to construct three procedures based on complet...
It is widely recognised that air pollutants including sulphur dioxide (SO2), respirable suspended particulates (PM10), nitrogen oxides (NOx), nitrogen dioxide (NO2), and ozone (O3), as well as weather conditions such as temperature (Temp) and relativ...
Air pollution is a hotspot of wide concern in Chinese cities. With the worsening of air pollution, urban agglomerations face an increasingly complex environment for air quality monitoring, hindering sustainable and high-quality development in China....
The three-dimensional geometry of a micromixer with an asymmetrical split-and-recombine mechanism was optimized to enhance the fluid-mixing capability at a Reynolds number of 20. Single and multi-objective optimizations were carried out by using part...
In order to improve the working quality of wet clutch switching in an agricultural tractor, in this paper, we took a power shift system composed of multiple wet clutches as the research object for full-factorial performance measurement, multi-factor...
This work presents a technique for the chirality (n, m) assignment of semiconducting single wall carbon nanotubes by solving a set of empirical equations of the tight binding model parameters. The empirical equations of the nearest neighbor hopping p...
It is of great importance to quantitatively characterize feed fouling potential for the effective and efficient prevention and control of reverse osmosis membrane fouling. A gradient filtration method with microfiltration (MF 0.45 μm) → ultra...
In this paper, we have introduced a functional approach for approximating nonparametric functions and coefficients in the presence of multivariate and functional predictors. By utilizing the Fisher scoring algorithm and the cross-validation technique...
The sources of potentially toxic elements (PTEs) in the lower reaches of the Yellow River (LYR) remain poorly understood due to intensive human activities in this region. To elucidate the spatiotemporal distribution characteristics and sources of PTE...
In unveiling the non-parametric estimation of the conditional hazard function through the local linear method, our study yields key insights into the method’s behavior. We present rigorous analyses demonstrating the mean square convergence of t...
18 February 2026
Prostate cancer (PrCa), the second most common cancer diagnosed in men globally, remains a critical challenge in precision oncology. While PrCa can be deadly, it is highly treatable if detected early. Identifying associative factors influencing disea...
Climate change has several negative effects on health, including cardiovascular disease. Many studies have considered the effect of temperature on cardiovascular disease and found that there is an association between extreme levels of temperature, co...
Extreme weather events have strong impacts on agriculture and crop insurance. In France, drought (2003, 2011, 2017, and 2018) and excess of water (2016) are considered the most significant events in terms of economic losses. The crop (re)insurance in...
Aftershocks often occur after strong earthquakes and aggravate structural damage. Commonly, the incremental dynamic analysis (IDA) considering the main aftershocks only used a single index such as the maximum or the residual inter-story drift ratio....
Voltage sags resulting from symmetrical or asymmetrical faults pose a significant threat to power quality. In response to this challenge, a voltage sag loss assessment method based on a two-stage Taguchi quality perspective approach is proposed to ad...
In this paper, we explore the connection between a single index model under the real-world probability measure and martingale pricing via minimal relative entropy or Esscher transform, within the context of a one-period market model, possibly incompl...
The continuous static contraction of the upper limb during overhead work often leads to progressive muscle fatigue, which is the main cause of work-related musculoskeletal disorders (WMSDs) and reduced operational safety. Traditional fatigue detectio...
We develop a design-conditional limit theory for kernel estimators of conditional U-functionals based on locally stationary functional random fields observed at irregular random locations and under incomplete response observation. The covariates take...
In his work published in (Ann. Probab. 19, No. 2 (1991), 812–825), W. Stute introduced the notion of conditional U-statistics, expanding upon the Nadaraya–Watson estimates used for regression functions. Stute illustrated the pointwise con...
Soybean is a key global crop for food and oil production, playing a vital role in ensuring food security and supplying plant-based proteins and oils. Accurate information on soybean distribution is essential for yield forecasting, agricultural manage...
Assessing the risk of water leakage within urban water distribution networks (UWDN) is crucial prior to implementing any control measures. Conducting a risk assessment facilitates the development of effective water leakage management plans. By compre...
To overcome the inability of single life-based indices to represent the nonlinear degradation of asphalt-mixture bearing capacity, this study proposes a multi-index framework for splitting-fatigue damage characterization and residual-life estimation....
Drought remains a phenomenal disaster of critical concerns in West Africa, particularly within the Niger River Basin, due to its insidious, multifaceted, and long-lasting nature. Its continuous severe impacts on communities, combined with the limitat...
Deep learning models have been widely used for vegetation destruction detection, but their performance depends on input features in addition to sample size and model architecture. Using Sentinel-2 imagery, we constructed multiple feature combinations...
A covariance matrix is an important parameter in many computational applications, such as quantitative trading. Recently, a global minimum variance portfolio received great attention due to its performance after the 2007–2008 financial crisis,...
Fractional calculus-based differential equations were found by previous studies to be promising tools in simulating local-scale anomalous diffusion for pollutants transport in natural geological media (geomedia), but efficient models are still needed...
The refractive index of solids gauges their transparency to incident light, while the energy gap determines the threshold for light absorption. This paper provides a mathematical formulation for the relationship between the refractive index and the e...
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