Targeted maximum likelihood based estimation for longitudinal mediation analysis by Wang Zeyi, Laan Lars van der, Petersen Maya, Gerds Thomas, Kvist Kajsa, Laan Mark van der

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MULTILEVEL REGRESSION WITH MAXIMUM LIKELIHOOD AND RESTRICTED MAXIMUM LIKELIHOOD METHOD IN ANALYZING INDONESIAN READING LITERACY SCORES by Vera Maya Santi, Rifa Kamilia, Faroh Ladayya

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A Maximum Likelihood Estimation Method for Underwater Radiated Noise Power by Guoqing Jiang, Mingyang Li, Zhuoran Liu, Linchuan Sun, Qingcui Wang

“…The method establishes the probability density function of the hydrophones array received data and derives the minimum variance unbiased estimation of the power through theoretical analysis under the maximum likelihood criterion. Numerical simulations and experimental data demonstrate that this method can significantly reduce the influence of ambient noise on estimation results and improve the estimation accuracy under low signal-to-noise ratio conditions, outperforming commonly used beamforming-based estimation methods. …”
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Analysis of influence of the item total scores on the levels of ability of respondents in the dichotomous Rasch model based on the weighted maximum likelihood method by E. B. Belov, M. V. Alekseev, N. P. Kitaev, A. I. Kuchumov

“…The purpose of the research is to analyze the influence of the difficulties of the items on the levels of abilities of the respondents based on the weighted maximum likelihood method (WML). …”
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Eccentricity Parameters Identification for a Motorized Spindle System Based on Improved Maximum Likelihood Method by Wengui Mao, Chaoliang Hu, Jianhua Li, Zhonghua Huang, Guiping Liu

“…The recognition results under the three kinds of measurement errors show that the improved maximum likelihood method improves the recognition effect of the maximum likelihood method and can reduce the influence of uncertainty factors on the recognition results, and the robustness is satisfactory.…”
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Research on distributed time synchronization methods for LEO communication constellations based on maximum likelihood estimation by YAN Bing, ZHAO Yafei, FANG Yiming, PENG Mugen, LIN Guangrong

“…The simulation results show that the synchronization error of the time synchronization method based on maximum likelihood estimation is less than 5 ns under the dynamic scenario and topology of LEO satellites.…”
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Research on distributed time synchronization methods for LEO communication constellations based on maximum likelihood estimation by YAN Bing, ZHAO Yafei, FANG Yiming, PENG Mugen, LIN Guangrong

“…The simulation results show that the synchronization error of the time synchronization method based on maximum likelihood estimation is less than 5 ns under the dynamic scenario and topology of LEO satellites.…”
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RESTRICTED MAXIMUM LIKELIHOOD ESTIMATION FOR MULTIVARIATE LINEAR MIXED MODEL IN ANALYZING PISA DATA FOR INDONESIAN STUDENTS by Vera Maya Santi, Khairil Anwar Notodiputro, Indahwati Indahwati, Bagus Sartono

“…Estimation of variance and random effect parameters was performed using the restricted maximum likelihood (REML) method. Based on the estimator of the variance of random effects for the response variables of mathematics, science, and reading literacy, it was obtained 1548.12, 1359.39, and 1082.48, respectively, which explains the significant effect of each school as a random effect on the three response variables.…”
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Spatial Autoregressive Model of Tuberculosis Cases in Central Java Province 2019 by Hasrat Ifolala Zebua, I Gede Nyoman Mindra Jaya

“…The estimation method usually used in SAR model is maximum likelihood. The value of Moran's I on the number of tuberculosis cases in Central Java is 0.499 and is significant, which means that there is a positive spatial autocorrelation. …”
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Enhancing the Accuracy of Land Use/Cover Map Using Some Spectral Indices in Sarab County–East Azerbaijan by A. Sarabchi, H. Rezaei, F. Shahbazi

“…Additionally, the study assessed the impact of various spectral indices on enhancing the results from the classification of Landsat 8 imagery, while also evaluating the efficacy of support vector machine (SVM) and maximum likelihood algorithms in producing maps with satisfactory accuracy and precision.   …”
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PERBANDINGAN PRINCIPAL AXIS FACTORING DAN MAXIMUM LIKELIHOOD DALAM MENENTUKAN FAKTOR DOMINAN YANG MEMPENGARUHI PEMBELAJARAN NAHWU SHOROF (STUDI KASUS PONDOK PESANTREN ROUDLOTUL MU... by Tanwirotul Khusna, Rachmadania Akbarita, Risang Narendra

“…The result of this study is the Maximum Likelihood method which is more appropriate than the Principal Axis Factoring method, because it has a smaller RMSE (Root Mean Squared Error) value.…”
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Water Depth Correction-Based Classification Combination Method for Extracting Shallow Sea Reef Geomorphological Information: A Case Study of Xisha Chau and Zhaoshu Island by Zhigang Lu, Weidong Zhu, Daxing Lei, Yi Zhu, Yifan Chen, Zilin Yue, Zhongqiang Wu

“…Satellite imagery, after preprocessing, is subjected to water depth correction to mitigate the influence of water depth on reflectance. A maximum likelihood classification model is then used for geomorphological classification, followed by refinement through a decision tree classification model, forming the WBMD scheme. …”
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Comparative Study of Multiple Supervised Classification Methods to Map Land Use in Local and Regional Scales (Case Study:Kan and Karaj Rivers Basin) by Maryam Alizadeh, Rooholah Mirzaee, Saedhosain Kiya

“…They have acceptable Kappa coefficient 3- Results and Discussion: The findings from accuracy assessment of classification at the Anderson Level 1 and 2 showed that the Maximum Likelihood method with Kappa coefficient of 0.77 and 0.76 and overall accuracy of 84.94 and 80.70 percent were identified as the optimum method to map the land cover/use of the Kan and Karaj Rivers basin at the local and regional scales respectively. …”
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An Enhanced ZigBee-Based Indoor Localization Method Using Multi-Stage RSSI Filtering and LQI-Aware MLE by Jianming Li, Shuyan Yu, Zhe Wei, Zhanpeng Zhou

“…This study presents a ZigBee-based localization approach that integrates multi-stage preprocessing of received signal strength indicator (RSSI) data with a reliability-aware extension of the maximum likelihood estimation (MLE) algorithm. To improve measurement stability, a hybrid filtering framework combining Kalman filtering, Dixon’s Q test, Gaussian smoothing, and mean averaging is applied to reduce the influence of noise and outliers. …”
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PEMETAAN PENGGUNAAN LAHAN SAWAH BERDASARKAN PENDEKATAN EKOLOGI BENTANG LAHANMENGGUNAKAN CITRA PEREKAMAN TUNGGAL by Algi Variski Hasibuan, Projo Danoedoro, Sigit Heru Murti

“…The landscape ecology approach assumed the influence of landforms on land-use. The use of ten optical bands in multispectral classification using the maximum likelihood algorithm and convolutional neural network algorithm resulted in twelve land cover classes. …”
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A statistical framework for modelling migration corridors by Tristan A. Nuñez, Mark A. Hurley, Tabitha A. Graves, Anna C. Ortega, Hall Sawyer, Julien Fattebert, Jerod A. Merkle, Matthew J. Kauffman

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Estimation of performance measures in a novel M/M/1 queueing model with reverse balking: A simulation-based approach by Asmita Tamuli, Dhruba Das, V. Deepthi, Amit Choudhury, Dibyajyoti Bora, Bhushita Patowari, Supahi Mahanta

“…In the classical approach, we used the Maximum Likelihood (ML) Estimation procedure to estimate the parameters using the Metropolis-Hastings (MH) algorithm. …”
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Comparing Frequentist and Bayesian Methods for Factorial Invariance with Latent Distribution Heterogeneity by Xinya Liang, Ji Li, Mauricio Garnier-Villarreal, Jihong Zhang

“…This simulation study examined how changes in latent means and variances between groups influence the detection of noninvariance, comparing Bayesian and maximum likelihood fit measures. …”
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A discrete extension of the Lindley distribution for health and sustainability data: Theoretical insights and decision-making applications by Mahmoud El-Morshedy, Mohamed S. Eliwa, Abhishek Tyagi, Hend S. Shahen

“…Furthermore, its capacity to handle zero-inflated and over- or under-dispersed data, commonly seen in health research, enables a more refined public health analysis crucial for SDG 3. With maximum likelihood estimation for parameter fitting, the model has been validated in practical sustainability contexts, such as monitoring patient follow-ups, evaluating device reliability, and examining disease progression, offering valuable insights for sustainable health interventions and effective resource use.…”
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Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms by Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi, Mehrdad Kargari

“…This study investigates and predicts the likelihood of operational risk occurrence in the banking industry using machine learning algorithms. …”
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