Temporal dynamics of uncertainty and prediction error in musical improvisation across different periods by Tatsuya Daikoku

“…Within the framework of human statistical learning and predictive processing, this study examined the temporal dynamics of uncertainty and surprise (prediction error) in a piece of musical improvisation. …”
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Mixed-Effects Tobit Joint Models for Longitudinal Data with Skewness, Detection Limits, and Measurement Errors by Getachew A. Dagne, Yangxin Huang

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Novel approaches in prediction of tensile strain capacity of engineered cementitious composites using interpretable approaches by Alahmari Turki S., Farooq Furqan

“…The result demonstrates that ANN and XGB perform well for train and test sets with R 2 > 0.96. Statistical measures show that all models give fewer errors with higher R 2, in which XGB and ANN depict robust performance. …”
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Statistical analysis of the formation mechanism of concepts-representations in organizational and technical systems by Alexander A. Solodov

“…Concept representation is a generalized sensual-visual image of the object or phenomenon and is characterized by a number of features, the number of which may vary in the course of the system operation.The method of Markov chains is used to study the statistical characteristics of the mechanism of formation of concepts-representations. …”
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Multiview Deep Autoencoder-Inspired Layerwise Error-Correcting Non-Negative Matrix Factorization by Yuan Liu, Yuan Wan, Zaili Yang, Huanhuan Li

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Improving seasonal precipitation forecasts in the Western United States through statistical downscaling by B Vernon, W Zhang, Y Chikamoto

“…This analysis indicates that downscaled products can capture localized features more accurately than the original coarse resolution forecasts, reducing forecast error across the western United States. …”
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Internal representations of temporal statistics and feedback calibrate motor-sensory interval timing. by Luigi Acerbi, Daniel M Wolpert, Sethu Vijayakumar

“…In particular, higher-order statistical features (kurtosis, multimodality) seem much harder to acquire. …”
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Environmental Data Analytics for Smart Cities: A Machine Learning and Statistical Approach by Ali Suliman AlSalehy, Mike Bailey

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Statistical Comparison between Pores and Sunspots during the Time Interval 2010–2023 by Yang Peng, Yu Fei, Nan-bin Xiang, Lin-hua Deng, Ting-ting Xu, Sheng Zheng, Shu-guang Zeng, Hai-yang Zhang, Shi-hu Liu

“…To reveal the physical properties of pores and sunspots varying with solar cycle, we carried out a statistical comparison among pores, transitional sunspots, and mature sunspots using Solar Dynamics Observatory/Helioseismic and Magnetic Imager from 2010 April to 2023 July. …”
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A statistical and machine learning approach for monthly precipitation forecasting in an Amazon city by Ewerton Cristhian Lima de Oliveira, Eduardo Costa de Carvalho, Edmir dos Santos Jesus, Rafael de Lima Rocha, Rafael de Lima Rocha, Helder Moreira Arruda, Ronnie Cley de Oliveira Alves, Ronnie Cley de Oliveira Alves, Renata Gonçalves Tedeschi

“…Besides the use of algorithms, another evaluation was conducted on Feature Composition based on statistical methods to investigate the impact of variables on the prediction.ResultsThe results obtained in our investigation indicate that the vector autoregressive moving average with exogenous regressors (VARMAX) model achieved the best performance in rainfall forecasting, with an average root mean square error (RMSE) of 9.1833 in time series cross-validation, outperforming the other models.DiscussionThe climate-driven patterns directly influenced the performance of the rainfall forecasting models evaluated in this study. …”
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Specificity Analysis of Genome Based on Statistically Identical K-Words With Same Base Combination by Hyein Seo, Yong-Joon Song, Kiho Cho, Dong-Ho Cho

“…The classification accuracy of the proposed algorithm was similar to that of conventional methods while using only a few features. <italic>Conclusions:</italic> We proposed a new method to investigate the genome-specific statistical specificity in the k-word profile which can be applied to find important properties of the genome and classify genome sequences.…”
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Modern features of benchmarking in the hotel business by E. L. Zadneprovskaya, T. N. Poddubnaya, E. A. Panina, T. A. Dzhum

“…The research methods used are method of competitive analysis, statistical method, generalization method, forecasting. …”
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Analysis of Geometric Errors of Throat Sizes of Last Stage Blades in a Mid-Size Steam Turbine by Petr Eret, Michal Hoznedl

“…This case study presents a statistical analysis of geometric errors of the throat sizes of the last stage blades in a mid-size steam turbine. …”
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Statistical analysis and machine learning of TMS-induced MEPs for predicting poststroke motor impairment and performance by Chun-Ren Phang, Shintaro Uehara, Sachiko Kodera, Akiko Yuasa, Shin Kitamura, Yohei Otaka, Akimasa Hirata

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Clinical Features of Juvenile Open-angle Glaucoma by A. V. Malyshev, A. S. Apostolova, A. A. Sergienko, A. F. Teshev, G. Yu. Karapetov, M. K. Ashhamahova, B. N. Hatsukova

“…Radius (IR), SP-A1, SSI. Statistical processing of the obtained results was carried out using the standard statistical analysis software package “SPSS 16.0 for Windows”. …”
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Is Seeing Believing? A Practitioner’s Perspective on High-Dimensional Statistical Inference in Cancer Genomics Studies by Kun Fan, Srijana Subedi, Gongshun Yang, Xi Lu, Jie Ren, Cen Wu

“…In particular, we advocate for robust Bayesian variable selection in cancer genomics studies due to its ability to accommodate disease heterogeneity in the form of heavy-tailed errors and structured sparsity while providing valid statistical inference. …”
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A Statistical Framework to Detect and Quantify Operator-Learning Curves in Medical Device Safety Evaluation by Ssemaganda HC, Davis SE, Govindarajulu US, Koola JD, Mao J, Westerman DM, Perkins AM, Speroff T, Ramsay CR, Sedrakyan A, Ohno-Machado L, Matheny ME, Resnic FS

“…Correctly attributing safety signals to learning or device effects allows for appropriate corrective actions and recommendations to improve patient safety.Objective: To develop and assess the statistical performance of an analytic framework to detect the presence of LE and quantify the learning curve (LC).Design and Setting: We generated synthetic datasets based on observed clinical distributions and complex feature correlations among patients hospitalized at US Department of Veterans Affairs facilities. …”
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Six-Dimensional Spatial Dimension Chain Modeling via Transfer Matrix Method with Coupled Form Error Distributions by Lu Liu, Xin Jin, Huan Guo, Chaojiang Li

“…., worst-case analysis, statistical tolerance analysis) face limitations from oversimplified assumptions—treating datum features as ideal geometries while ignoring manufacturing-induced spatial distribution of form errors and failing to characterize 3D coupled error constraints. …”
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Quantifying observer variance in expansive monitoring program indicator data with heterogeneous-variance mixed-effects models by Leah T. Dreesmann, Timothy R. Johnson, Jason W. Karl

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Functional Disability and Psychological Impact in Headache Patients: A Comparative Study Using Conventional Statistics and Machine Learning Analysis by Jong-Ho Kim, Hye-Sook Kim, Jong-Hee Sohn, Sung-Mi Hwang, Jae-Jun Lee, Young-Suk Kwon

“…Frequent analgesic medication emerged as a significant predictor of poorer life quality (Headache Impact Test-6, root mean squared error = 7.656) and increased depression (Patient Health Questionnaire-9, root mean squared error = 5.07) and anxiety (Generalized Anxiety Disorder-7, root mean squared error = 4.899) in the Random Forest model. …”
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