A trenchant and passionate dispute over the use of parametric versus non-parametric methods for the analysis of Likert scale ordinal data has raged for the past eight decades. The answer is not a simple “yes” or “no” but is related to hypotheses, obj...
Accurate drought identification is important for both scientists and decision-makers to be able to make informative decisions. In this study, parametric and non-parametric approaches for analyzing meteorological drought are compared, aiming at simpli...
In this paper, we consider a non-parametric regression model relying on Riesz estimators. This linear regression model is similar to the usual linear regression model since they both rely on projection operators. We indicate that Riesz estimator regr...
In selection and ranking, the partitioning of treatments by comparing them to a control treatment is an important statistical problem. For over eighty years, this problem has been investigated by a number of researchers via various statistical design...
Restricted Mean Survival Time (
The methodology carried out in this work is based on non-parametric inference. The problem is framed as a regression analysis, and the solution is derived using the permutation approach. The proposed test does not rely on the assumption that the dist...
This paper describes the non-parametric shape optimization process for a football boot bottom plate. The non-parametric shape optimization process changes the nodes’ location of a model and outputs an optimum shape, which satisfies an optimizat...
Recently, there is a renewed interest from the scientific community in the study of the electrical signal generated by plants due to its wide range of applications in agriculture, for example, environmental monitoring, detection of pests, diseases in...
The degradation of biopolymers such as polylactic acid (PLA) has been studied for several years; however, the results regarding the mechanism of degradation are not completely understood yet. PLA is easily processed by traditional techniques includin...
In this paper, the spatial dynamic panel data (SDPD) model with fixed effects is extended to a non-parametric form by relaxing the linear or nonlinear parameter structure of explanatory variables. The non-parametric spatial dynamic panel data (NSDPD)...
This article is devoted to methods of processing random processes. This task becomes particularly relevant in cases where the random process is broadband and non-stationary; then, the measurement of a random process can be associated with an assessme...
In this paper, we propose a non-parametric clustering method to recognize the number of human motions using features which are obtained from a single microelectromechanical system (MEMS) accelerometer. Since the number of human motions under consider...
This paper proposes a genetic algorithm-based Markov Chain approach that can be used for non-parametric estimation of regression coefficients and their statistical confidence bounds. The proposed approach can generate samples from an unknown probabil...
The leaf area index (LAI) is a key biophysical variable for agroecosystem monitoring, as well as a relevant state variable in crop modelling. For this reason, temporal and spatial determination of LAI are required to improve the understanding of seve...
We develop goodness-of-fit (GOF) procedures rooted in Tsallis entropy, with a particular emphasis on multivariate exponential-power (generalized Gaussian) and q-Gaussian models. The GOF statistic compares a closed-form Tsallis entropy under the null...
This paper features an analysis of the relationship between the S&P 500 Index and the VIX using daily data obtained from the CBOE website and SIRCA (The Securities Industry Research Centre of the Asia Pacific). We explore the relationship between...
In quantum and quantum-inspired machine learning, a key step is to embed the data in the quantum space known as Hilbert space. Studying quantum kernel function, which defines the distances among the samples in the Hilbert space, belongs to the fundam...
Height estimation of scatterers in complex environments via the Tomographic Synthetic Aperture Radar (TomoSAR) technique is still a valuable research field. The parametric spectral estimation approach constitutes a powerful tool to identify the super...
Increases in the cost of research, specialization and reductions in public expenditure in health are changing the economic environment for the pharmaceutical industry. Gains in productivity and efficiency are increasingly important in order for firms...
The COVID-19 pandemic has had a significant impact on hospitals and healthcare systems around the world. The cost of business disruption combined with lingering COVID-19 costs has placed many public hospitals on a course to insolvency. To quickly ret...
Statistical process control (SPC) tools are used for the investigation and identification of unnatural variations in the manufacturing, industrial, and service processes. The control chart, the basic and the most famous tool of SPC, is used for proce...
Previous studies have demonstrated that non-parametric hedging models using temperature derivatives are highly effective in hedging profit/loss fluctuation risks for electric utilities. Aiming for the practical applications of these methods, this stu...
In biomedical research, identifying genes associated with diseases is of paramount importance. However, only a small fraction of genes are related to specific diseases among the multitude of genes. Therefore, gene selection and estimation are necessa...
The non-parametric (N-P) method expresses evapotranspiration as a function of net radiation, ground heat flux, air temperature, and surface temperature (Ts). This method is relatively new and attractive for estimating evapotranspiration, especially f...
In low-voltage distribution networks, distributed energy storage systems (DESSs) are widely used to manage load uncertainty and voltage stability. Accurate modeling and estimation of voltage fluctuations are crucial to informed DESS dispatch decision...
The evolution of some epidemics, such as influenza, demonstrates common patterns both in different regions and from year to year. On the contrary, epidemics such as the novel COVID-19 show quite heterogeneous dynamics and are extremely susceptible to...
A rapid decline in mortality and fertility has become major issues in many developed countries over the past few decades. An accurate model for forecasting demographic movements is important for decision making in social welfare policies and resource...
Agricultural reservoirs play such a central role in supplying water to rural areas that it is essential to properly estimate the design flood for agricultural reservoirs under climate change. The objective of this study was to estimate the inflow des...
The management of modern water supply systems requires a detailed analysis of consumption patterns in order to optimize pump operation schedules, reduce energy costs, and support the development of intelligent management systems. Traditional clusteri...
Loop shaping the controller for high-order systems, especially in the presence of flexible transmission components such as elastic shafts, gearboxes, and belts commonly found in servo systems, poses significant challenges. Therefore, developing a non...
Over the last few decades, the statisticians and reliability analysts have looked at putting exponentiality to the test using the Laplace transform technique. The non-parametric statistical test used in this study, which is based on this technique, e...
With the aim of understanding the impact of air pollution on human health and ecosystems in the tropical Andes region (TAR), we aim to couple the Weather Research and Forecasting Model (WRF) with the chemical transport models (CTM) Long-Term Ozone Si...
The non-parametric Gaussian mixture of regressions (NPGMRs) model serves as a flexible approach for the determination of latent heterogeneous regression relationships. This model assumes that the component means, variances and mixing proportions are...
The energy management system (EMS) of hybridization and electrification plays a pivotal role in improving the stability and cost-effectiveness of future vehicles. Existing efforts mainly concentrate on specific optimization targets, like fuel consump...
The present study analyzes experimental data using qualitative and quantitative methods to identify significant statistical changes. These methods were employed to evaluate the results from the structural characterization of annealed TiWN and TiWC co...
Temporal network diffusion models play a crucial role in healthcare, information technology, and machine learning, enabling the analysis of dynamic event-based processes such as disease spread, information propagation, and behavioral diffusion. This...
Motorcycle emissions are a growing environmental and public health concern in many low- and middle-income countries. While several studies have examined the emission profiles from larger vehicles in urban areas, very few have analyzed motorcycle emis...
Forests play a significant role in terrestrial ecosystems by sequestering carbon, and forest biomass is a crucial indicator of carbon storage potential. However, the single-frequency SAR estimation of forest biomass often leads to saturation issues....
This paper reviews key signal processing techniques in structural health monitoring (SHM), focusing on non-parametric time–frequency analysis, adaptive decomposition, and deconvolution methods. It examines the short-time Fourier transform (STFT...
Understanding how drought propagates from meteorological to agricultural drought requires further research into the combined effects of soil moisture, evapotranspiration, and precipitation, especially through the analysis of long-term data. To this e...
In modern survey sampling, particularly when using stratified random sampling (StRS), the existence of outliers and model mis-specifications is a daunting challenge to the conventional parametric and nonparametric methods of estimating parameters. Th...
This study investigates the effectiveness of blast furnace slags (BFSs) as catalysts in the ozonation process to degrade complex contaminants such as bezafibrate (BFZ) at different pH levels. The findings reveal that the presence of BFS enhances degr...
A prevailing assumption in many behavioral studies is the underlying normal distribution of the data under investigation. In this regard, although it appears plausible to presume a certain degree of similarity among individuals, this presumption does...
Accurate drought monitoring depends on selecting an appropriate cumulative distribution function (CDF) to model the original data, resulting in the standardized drought indices. In the numerous research studies, while rigorous validation was not made...
The selection of superior maize genotypes is complex due to the quantitative and intercorrelated nature of agronomic traits and their strong environmental influence, which limits the efficiency of direct selection and requires multivariate approaches...
We consider a constructive definition of the multivariate Pareto that factorizes the random vector into a radial component and an independent angular component. The former follows a univariate Pareto distribution, and the latter is defined on the sur...
In this paper, we propose a new statistic to test the monotonicity of uncertainty based on derivative criteria and the histogram method. We test the null hypothesis that residual entropy is constant against the fact that it decreases over time. Hence...
The majority of the widely used scan statistics are based on distributional assumptions. Contrary to the existing methods, with a new perspective in clustering, the Mann-Whitney Scan Statistic was introduced to detect clusters in continuous data inde...
This study demonstrates that compressive strength in cement-stabilized rammed earth is governed by conditional, threshold-controlled interactions rather than by intrinsic mineralogical effects. A B + K (beidellite + kaolinite) content exceeding 15% d...
Last decades have witnessed that exposure to business activities, through family and direct experience, positively influences students’ entrepreneurial intention (EI). The paper aims to present and analyze the relationship between business experience...
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