Retracted: Process Monitoring for Gamma Distributed Product under Neutrosophic Statistics Using Resampling Scheme by Journal of Mathematics

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Improving the accuracy of remotely sensed TSS and turbidity using quality enhanced water reflectance by a statistical resampling technique by Kunwar Abhishek Singh, Dongryeol Ryu, Meenakshi Arora, Manoj Kumar Tiwari, Bhabagrahi Sahoo

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A robust and statistical analyzed predictive model for drug toxicity using machine learning by Deepak Rawat, Rohit Bajaj, Rachit Manchanda, Ankush Mehta, Prabhu Paramasivam, Suraj Kumar Bhagat, Abinet Gosaye Ayanie

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Multivariate response directional regression: a projective resampling approach by Ahreum Lee, Kyongwon Kim

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mlr3spatiotempcv: Spatiotemporal Resampling Methods for Machine Learning in R by Patrick Schratz, Marc Becker, Michel Lang, Alexander Brenning

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Comparisons between Resampling Techniques in Linear Regression: A Simulation Study by Anwar Fitrianto, Punitha Linganathan

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COMPARISON OF RESAMPLING EFFICIENCY LEVELS OF JACKKNIFE AND DOUBLE JACKKNIFE IN PATH ANALYSIS by M. Fikar Papalia, Solimun Solimun, Nurjannah Nurjannah

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A New System of Skip-Lot Sampling Plans including Resampling by Saminathan Balamurali, Muhammad Aslam, Chi-Hyuck Jun

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ENSEMBLE RESAMPLING SUPPORT VECTOR MACHINE, MULTINOMIAL REGRESSION TO MULTICLASS IMBALANCED DATA by Laila Qadrini, Hikmah Hikmah, Elviani Tande, Ignasius Presda, Aulia Atika Maghfirah, Nilawati Nilawati, Handayani Handayani

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PATH ANALYSIS OF FACTORS INFLUENCING CASHLESS SOCIETY DEVELOPMENT USING BOOTSTRAP RESAMPLING by Dea Saraswati Pramaningrum, Adji Achmad Rinaldo Fernandes, Atiek Iriany, Solimun Solimun

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How to Count Parrots: Comparing the Performance of Point and Transect Counts for Surveying Tasman Parakeets (<i>Cyanoramphus cookii</i>) by Michael John Adam Skirrow, Luis Ortiz-Catedral, Adam N. H. Smith

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Landslide susceptibility analysis using random forest model with SMOTE-ENN resampling algorithm by Mingxi Lu, Lea Tien Tay, Junita Mohamad-Saleh

“…The results indicated that the differences between the methods were statistically significant; RF combined with the synthetic minority oversampling technique-edited nearest neighbour (SMOTE-ENN) resampling method proposed in this paper has positive effect in LSA as compared with the other resampling methods. …”
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Analysis of sparse data in pharmacokinetic studies by I. I. Miroshnichenko, A. N. Simonov, I. I. Kuzmin, A. I. Platova

“…Using the example of the pharmacokinetic (PK) study of resveratrol in mice, the resampling method was allowed us to obtain individual PK-parameters and perform full-fledged statistical tests.…”
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Enhancing fraud detection in imbalanced motor insurance datasets using CP-SMOTE and Random Under-Sampling by Pornpawee Komsrimorakot, Thitirat Siriborvornratanakul

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Coordinate Transformation between Global and Local Datums Based on Artificial Neural Network with K-Fold Cross-Validation: A Case Study, Ghana by Yao Yevenyo Ziggah, Hu Youjian, Alfonso Rodrigo Tierra, Prosper Basommi Laari

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A High-Dimensional Cramér–von Mises Test by Danna Zhang, Mengyu Xu

Subjects: “…Cramér–von Mises statistic…”
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Linear B-cell epitope prediction for SARS and COVID-19 vaccine design: Integrating balanced ensemble learning models and resampling strategies by Fatih Gurcan

“…The implemented resampling methods were designed to improve class balance and enhance model training. …”
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A Comprehensive Comparative Analysis of Deep Learning Models for Student Performance Prediction in Virtual Learning Environments: Leveraging the OULA Dataset and Advanced Resamplin... by Bayan A. Alnasyan, Mohammed Basheri, Madini O. Alassafi

“…Moreover, it examines the role of resampling techniques, including SMOTE, ROS, ADASYN, RUS, and Tomek Links, in addressing class imbalance. …”
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Statistical Uncertainty in Hydrometeorological Trend Analyses by Charles Onyutha

“…To assess data-related uncertainty, a resampling procedure was applied. It was shown that at a selected significance level, the null hypothesis H0 (no trend) can be rejected for trend direction while the evidence to reject H0 (zero trend magnitude) is statistically insufficient. …”
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An Analytical Prior Selection Procedure for Empirical Bayesian Analysis Using Resampling Techniques: A Simulation-Based Approach Using the Pancreatic Adenocarcinoma Data from the S... by Aditya Chakraborty, Mohan D. Pant

“…In the Bayesian framework, empirical resampling methods, such as bootstrapping and jackknifing, can offer valuable insights into the significance of prior selection, thus improving the consistency of statistical inferences. …”
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