96 Results Found

The conditioning theory of the generalized inverse $C_A^{‡}$ is considered in this article. First, we introduce three kinds of condition numbers for the generalized inverse $C_A^{‡}$, i.e., normwise, mixed and componentwise ones, and present their...

The conditioning theory of the $\mathcal{ML}$-weighted least squares and $\mathcal{ML}$-weighted pseudoinverse problems is explored in this article. We begin by introducing three types of condition numbers for the $\mathcal{ML}$-weighted pseudoinverse problem: normwise, mixed, and comp...

This study addresses the instability of statistical modeling for small-sample maximum friction torque data under multiple temperature conditions. Within the Weibull distribution framework, a sample-aggregation method is proposed, and a unified modeli...

High-voltage oil-immersed transformers operating in windblown sand and alpine regions are exposed to multiple environmental and operational stresses that may affect their degradation and reliability. To address limitations associated with single-dist...

Accurate engine fault classification with limited labeled data is critical for the safety and reliability of rotating machinery. This task is challenging because operating regimes are time-varying, and key variables must satisfy physical constraints,...

This study investigates the relationship between renewable energy (RE) expansion and economic diversification in Egypt over 1990–2023 using a nonlinear autoregressive distributed lag (NARDL) framework. Egypt’s fossil fuel share stands at...

This study investigates the nonlinear relationship between sectoral loan diversification and credit risk in Vietnamese commercial banks. Using a balanced panel of 14 banks over 2012–2025, comprising 196 bank-year observations, the study measure...

Accurate soil salinity estimation under small-sample agricultural conditions continues to pose a formidable challenge, attributed to the scarcity of labeled data, inherent representational limitations of single-backbone neural networks, and the heigh...

Meta-analysis of proportions requires a rigorous transformation model due to the inherent mathematical constraints of proportional data (boundedness and non-constant variance). This study compared four proportions (Untransformed, Freeman–Tukey,...

This paper investigates how renewable electricity production, energy consumption, and economic openness influence economic growth in the Gulf Cooperation Council (GCC) countries from 2008 to 2023. Using annual panel data for six countries—Saudi...

Existing top-down carbon emission estimation studies often rely on single models or conventional ensemble approaches, which may limit their ability to capture complex nonlinear relationships under small-sample conditions. To address this limitation,...

Ensuring the stability of coal mine roofs is a critical technical prerequisite for safe underground operations and the structural stability of underground engineering systems in mining areas. However, roof instability is governed by the variability a...

The impact of nonnormality on parameter estimates and model-data fit has been extensively evaluated in confirmatory factor analysis models, but comparatively less attention has been given to path models, where nonnormality may occur in different comb...

Drought is one of the major disasters constraining crop production. The accurate identification of the dominant environmental factors that drive drought stress at different growth stages of maize is essential for developing stage-specific and precise...

The quality and safety supervision of agricultural products at the grassroots level has long faced the triple superposition dilemma of small-sample sampling, multi-source evidence conflict, and risk chain evolution. Although existing data-driven mode...

In this work, a mathematical model of the transfer process in a layer under the condition of given experimental data on a part of the layer boundary is presented and investigated. Such research is important for the mathematical description of the obj...

Small area estimation (SAE) methods can provide information that conventional direct survey estimation methods cannot. The use of small area estimates based on linear and generalized linear mixed models is still very limited, possibly because of the...

The main novelty of this paper consists of presenting a statistical artificial neural network (ANN)-based model for a robust prediction of the frequency-dependent aeroacoustic liner impedance using an aeroacoustic computational model (ACM) dataset of...

A methodology for the statistical modeling of boundary value problems of mathematical physics for parabolic equations used to describe transport processes in a layer with incomplete data at the boundary of a body has been developed and presented. The...

A new family of stochastic $\eta$-power log-logistic diffusion processes was introduced and defined based on the classical log-logistic diffusion model. The probabilistic characteristics of the proposed process were derived through an analysis of the...

In this paper, we present uncertainties of statistical quantities of direct numerical simulations (DNS) with small numerical errors. The uncertainties are analysed for channel flow and a flow separation case in a confined backward facing step (BFS) g...

Background: Whether financial deepening and trade integration support or hinder environmental sustainability in hydrocarbon-dependent economies remains contested. Methods: This study examines the relationships among financial inclusion, energy intens...

Accurate information on waste composition is essential for strategic planning in waste management and developing environmental technologies. However, detailed analyses of individual waste containers are both time- and cost-intensive, resulting in a l...

Maximum entropy methods of parameter estimation are appealing because they impose no additional structure on the data, other than that explicitly assumed by the analyst. In this paper we prove that the data constrained GME estimator of the general li...

Background: The global burden of mental disorders continues to escalate, necessitating scalable, evidence-based interventions. Artificial intelligence (AI)-delivered health promotion programs represent a promising approach to addressing treatment gap...

China’s Green Financial Reform and Innovation Pilot Policy may help coordinate digital and green transformation. Using a panel of 284 Chinese cities from 2011 to 2021, this study treats the policy as a quasi-natural experiment and estimates its...

The amount and accuracy of nodule resources estimation in the Pacific Ocean are among the main factors conditioning the future exploitation. The estimates are based on the results of classical, direct seafloor sampling. Due to the large distance betw...

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...

The P-S-N curve is a vital tool for dealing with fatigue life analysis, and its fitting under the condition of small samples is always concerned. In the view that the three parameters of the P-S-N curve equation can better describe the relationship b...

Laboratory spectroscopy has proved its reliability for estimating soil organic carbon (SOC) by exploiting the relationship between electromagnetic radiation and key spectral features of organic carbon located in the VIS-NIR-SWIR (350–2500 nm) r...

In this paper we examine an Information-Theoretic method for solving noisy linear inverse estimation problems which encompasses under a single framework a whole class of estimation methods. Under this framework, the prior information about the unknow...

Constant-specified and exponential concentration inequalities play an essential role in the finite-sample theory of machine learning and high-dimensional statistics area. We obtain sharper and constants-specified concentration inequalities for the su...

Time-dependent reliability analysis (TRA) is essential for the life-cycle risk assessment of engineering systems. However, existing TRA methods often require extensive statistical data or computationally expensive surrogate models, which limit their...

Evaluating conditional time-series generation models remains challenging in battery research, where degradation data are often limited and experiments cover only a small number of operating conditions. The widely used Fréchet Inception Distanc...

Assessing whether datasets follow a normal distribution is essential for valid statistical inference, yet GNSS positioning errors often deviate from Gaussian assumptions under real conditions. Despite the widespread use of normality tests, their perf...

Mutual information (MI) quantifies the statistical dependency between a pair of random variables, and plays a central role in the analysis of engineering and biological systems. Estimation of MI is difficult due to its dependence on an entire joint d...

Climate change’s impact on water availability has been widely studied, including its impact on very rare values quantified by return levels using the statistical extreme value theory. However, the application of this theory to estimate extreme...

Background: Omega-3 fatty acids may be relevant to mental health, but evidence among university students remains limited. This small exploratory cross-sectional study examined associations between estimated dietary omega-3 intake and anxiety and depr...

Background: Caprine arthritis encephalitis (CAE) is a major viral disease of goats, caused by small ruminant lentivirus (SRLV), associated with chronic arthritis, mastitis, pneumonia, and encephalitis, leading to economic losses and reduced animal we...

Nonparametric inference for residual-life functionals is a fundamental problem in mathematical statistics, reliability theory, and survival analysis, particularly in studies with limited sample sizes where empirical plug-in estimators may exhibit sub...

This manuscript presents a novel scheme to achieve high-resolution laser-radar ranging with a small sample number under low signal-to-noise ratio (SNR) conditions. To reduce the sample number, the Restricted Isometry Property-based optimal multi-chan...

This study examines simulated mortgage-financed home-purchase opportunities across ten Italian cities from 2008 to 2024 in relation to tourism intensity, residential prices, local incomes and mortgage conditions. The unbalanced estimation sample incl...

Analytical biosimilarity assessment relies on two implicit conditions. First, the analytical method must meet a set of requirements known as fit for intended use related to trueness and precision. Second, the manufacture of the reference drug product...

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...

Background and objectives: Identification of cancer biomarkers that are differentially expressed (DE) between two biological conditions is an important task in many microarray studies. There exist several methods in the literature in this regards and...

Suppose that we have a statistical model with q unknown parameters w, and an estimate $\widehat{w}$, based on a sample of size n. A basic question is: what is the covariance of the estimate? The covariance is needed for the Central Limit Theorem (CLT). This giv...

The reliability of cutting tools is critical to machining precision and production efficiency. The conventional statistic-based reliability assessment method aims at providing a general and overall estimation of reliability for a large population of...

The stress and deformation sensitivity analysis of high earth-rock dams requires knowledge of the statistical mean and standard deviation of deformation parameters of dam materials. However, these parameters are typically determined through grouped t...

This study examines whether volatility in Brent crude oil prices spills over to the Bahrain Stock Market Index (BSMI), and whether that spillover differs by regime, over 2865 trading days from 25 May 2010 to 28 February 2025. Bahrain is a distinctive...

We study prediction intervals for the semi-functional partial linear model (SFPLM) under stationary, geometrically $\beta$-mixing dependence. We analyze a split conformal procedure based on a three way data partition with buffer gaps, a functional pri...