Process Monitoring for Gamma Distributed Product under Neutrosophic Statistics Using Resampling Scheme by Abdullah M. Almarashi, Muhammad Aslam

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Revealing Traces of Image Resampling and Resampling Antiforensics by Anjie Peng, Yadong Wu, Xiangui Kang

“…We find that the interpolation operation used in the resampling and forged resampling makes these two kinds of image show different statistical behaviors from the unaltered images, especially in the high frequency domain. …”
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Unsupervised data imputation with multiple importance sampling variational autoencoders by Shenfen Kuang, Yewen Huang, Jie Song

“…In the imputation step, missing data is estimated using conditional expectation through multiple importance resampling. We propose an efficient imputation algorithm that broadens the scope of Missing data Importance Weighted Auto-Encoder (MIWAE) by incorporating multiple proposal probability distributions and the resampling schema. …”
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Explore the factors related to the death of offspring under age five and appraise the hazard of child mortality using machine learning techniques in Bangladesh by Ashikur Rahman, Md. Habibur Rahman

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Some Experiments in Extreme‐Value Statistical Modeling of Magnetic Superstorm Intensities by Jeffrey J. Love

“…Comparisons of the statistical significance and goodness of fits of the various models give no clear indication as to which model is best. …”
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Bootstrap Statistical Model of Tooth Surface Deviation of Heat Treatment Deformation of Batch Spiral Bevel Gears by Weihao Sun, Jubo Li, Tianxing Li, Chuang Jiang, Songlin Wang, Jianxin Su

“…Aiming at the same batch of spiral bevel gears with the same gear material， NC milling method and heat treatment specification， a bootstrap resampling is carried out on a small number of tooth surface deviation sample data based on the bootstrap method， a large number of sample data are obtained and a bootstrap statistical model of batch spiral bevel gear tooth surface deviation is established； the probability characteristic value of the sequential points of tooth surface measurement is calculated， and whether they conform to the normal distribution is tested by <italic>k</italic>-<italic>s</italic>； the estimated true value， estimated interval and other parameters are selected to describe their statistical laws and results； through the cubic NURBS surface fitting method， the variation law of the tooth surface deviation of the whole batch is obtained， and the effective evaluation of the tooth surface accuracy of the whole batch is realized. …”
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Developing clinical prognostic models to predict graft survival after renal transplantation: comparison of statistical and machine learning models by Getahun Mulugeta, Temesgen Zewotir, Awoke Seyoum Tegegne, Mahteme Bekele Muleta, Leja Hamza Juhar

“…Prognostic predictors were selected based on statistical significance and variable importance. Results The median graft survival time was 33 months, and the mean hazard of graft failure was 0.0755. …”
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Unit-Chen distribution and its quantile regression model with applications by Ammar M. Sarhan

“…The need for new statistical distributions that can effectively fit real datasets on the unit interval is crucial in data analysis. …”
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How many people in the Netherlands live with a hip, knee, or shoulder replacement?: prevalence estimates using data from the Dutch Arthroplasty Register (LROI) and Statistics Nethe... by Mirthe H. W. van Veghel, Liza N. van Steenbergen, Maaike G. J. Gademan, Wilbert B. van den Hout, B. W. Schreurs, Gerjon Hannink

“…Data on the size of the Dutch population were obtained from Statistics Netherlands. Annual incidences and deaths from hip and knee arthroplasty since 2010, and shoulder arthroplasty since 2015, were observed from the LROI. …”
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Robust predictive framework for diabetes classification using optimized machine learning on imbalanced datasets by Inam Abousaber, Haitham F. Abdallah, Hany El-Ghaish

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The dynamics of lowland river sections of Danube and Tisza in the Carpathian basin by Imre M. Jánosi, Imre M. Jánosi, István Zsuffa, István Zsuffa, Tibor Bíró, Boglárka O. Lakatos, Boglárka O. Lakatos, András Szöllősi-Nagy, Zsolt Hetesi, Zsolt Hetesi

“…The paper presents a detailed statistical analysis of data from 41 hydrometric stations along the Danube (section in the Carpathian Basin) and its longest tributary, the Tisza River. …”
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The effect of resizing on the natural appearance of scintigraphic images: an image similarity analysis by Siraj Ghassel, Amir Jabbarpour, Jochen Lang, Eric Moulton, Eric Moulton, Ran Klein, Ran Klein, Ran Klein, Ran Klein

“…Background and objectiveThis study aimed to assess the impact of upsampling and downsampling techniques on the noise characteristics and similarity metrics of scintigraphic images in nuclear medical imaging.MethodsA physical phantom study using dynamic imaging was used to generate reproducible static images of varying count statistics. Naïve upsampling and downsampling with linear interpolation were compared against alternative methods based on the preservation of Poisson count statistics and principles of nuclear scintigraphic imaging; namely, linear interpolation with a Poisson resampling correction (upsampling) and a sliding window summation method (downsampling). …”
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The proper application of logistic regression model in complex survey data: a systematic review by Devjit Dey, Md. Samio Haque, Md. Mojahedul Islam, Umme Iffat Aishi, Sajida Sultana Shammy, Md. Sabbir Ahmed Mayen, Syed Toukir Ahmed Noor, Md. Jamal Uddin

“…Abstract Background Logistic regression is a useful statistical technique commonly used in many fields like healthcare, marketing, or finance to generate insights from binary outcomes (e.g., sick vs. not sick). …”
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Comparing the Linear and Quadratic Discriminant Analysis of Diabetes Disease Classification Based on Data Multicollinearity by Autcha Araveeporn

“…However, the MVE and t-distribution methods focus on the resampling algorithm, a reliable tool for high resistance. …”
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Predicting Time in Range Without Hypoglycaemia Using a Risk Calculator for Intermittently Scanned CGM in Type 1 Diabetes by Fernando Sebastian‐Valles, Jose Alfonso Arranz Martin, Julia Martínez‐Alfonso, Jessica Jiménez‐Díaz, Iñigo Hernando Alday, Victor Navas‐Moreno, Teresa Armenta Joya, Maria del Mar delFandiño García, Gisela Liz Román Gómez, Jon Garai Hierro, Luis Eduardo Lander Lobariñas, Carmen González‐Ávila, Purificación deMartinez de Icaya, Vicente Martínez‐Vizcaíno, Miguel Antonio Sampedro‐Nuñez, Mónica Marazuela

“…Logistic regression models to predict OGC were developed in one of the samples, and the best model was selected using the Akaike information criterion and adjusted for Pearson's and Hosmer–Lemeshow's statistics. Model reliability was assessed via external validation in the second sample and internal validation using bootstrap resampling. …”
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Identifying the Roadway Infrastructure Factors Affecting Road Accidents Using Interpretable Machine Learning and Data Augmentation by Jonghak Lee, Sangyoup Kim, Tae-Young Heo, Dongwoo Lee

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Antiviral therapy can effectively suppress irAEs in HBV positive hepatocellular carcinoma treated with ICIs: validation based on multi machine learning by Shuxian Pan, Zibing Wang

“…Models were established using Lasso, RSF (RandomForest), and xgBoost, with ten-fold cross-validation and resampling methods used to ensure model reliability. …”
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Diagnostic prediction model for screening of elevated low-density and non-high-density lipoproteins in young Thai adults between 20 and 40 years of age by Phichayut Phinyo, Wuttipat Kiratipaisarl, Vithawat Surawattanasakul, Wachiranun Sirikul

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Class imbalance learning–driven Alzheimer’s detection using hybrid features by Ran Baik

“…Fisher linear discriminant analysis is used for dimensionality reduction and the resampling method is used to handle the class imbalance problem. …”
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Exploring entry-exit correlation coefficient (EEC) as new quantitative social activities performance measurement of public space: The case of Dilworth Park, Philadelphia by Jae Min Lee

“…Findings reveal a statistically significant negative relationship between EEC and social activities, with a coefficient of −0.2. …”
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