An approximate likelihood method reveals ancient gene flow between human, chimpanzee and gorilla by Galtier, Nicolas

“…I introduce Aphid, an approximate maximum-likelihood method aimed at quantifying the sources of phylogenetic conflict via topology and branch length analysis of three-species gene trees. …”
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Flood Susceptibility Mapping in Punjab, Pakistan: A Hybrid Approach Integrating Remote Sensing and Analytical Hierarchy Process by Rana Muhammad Amir Latif, Jinliao He

“…We developed a robust Flood Susceptibility Model (FSM) utilizing the Maximum Likelihood Classification (MLC) model and Analytical Hierarchy Process (AHP) incorporating 11 flood-influencing factors, including “Topographic Wetness Index (TWI), elevation, slope, precipitation (rain, snow, hail, sleet), rainfall, distance to rivers and roads, soil type, drainage density, Land Use/Land Cover (LULC), and the Normalized Difference Vegetation Index (NDVI)”. …”
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Analysis of competing risks model using the generalized progressive hybrid censored data from the generalized Lomax distribution by Amal Hassan, Sudhansu Maiti, Rana Mousa, Najwan Alsadat, Mahmoued Abu-Moussa

“…This study focused on parameter estimation of the generalized Lomax distribution under a generalized progressive hybrid censoring scheme in the presence of CR when the cause of failure for each item was known and independent. Both maximum likelihood (ML) and Bayesian approaches were used to estimate the unknown parameters, reliability characteristics, and relative risks due to two causes. …”
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Assessing the Structure of the Ways of Coping Questionnaire in Fibromyalgia Patients Using Common Factor Analytic Approaches by Charles Van Liew, Maya S. Santoro, Larissa Edwards, Jeremy Kang, Terry A. Cronan

“…Foundational factoring approaches were performed on the data (i.e., maximum likelihood factoring [MLF], iterative principal factoring [IPF], principal axis factoring (PAF), and principal components factoring [PCF]) with oblique oblimin rotation. …”
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A Low Computational Complexity SML Estimation Algorithm of DOA for Wireless Sensor Networks by Faming Gong, Haihua Chen, Shibao Li, Jianhang Liu, Zhaozhi Gu, Masakiyo Suzuki

“…The Stochastic Maximum Likelihood (SML) algorithm is adopted in this paper. …”
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Molecular Characterization of Wild and Cultivated Strawberry (Fragaria × ananassa) through DNA Barcode Markers by Awais Qarni, Khushi Muhammad, Abdul Wahab, Amir Ali, Chandni Khizar, Izhar Ullah, Abeer Kazmi, Tahira Sultana, Asma Hameed, Muhammad Younas, Mehdi Rahimi

“…The phylogenetic tree was constructed by using Fragaria current species sequences and reference sequences through the neighbor-joining method or maximum likelihood method. Results. Among eight DNA barcode markers, only two (ITS2 and rbclC) were amplified, and sequences were obtained. …”
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Methodology for Using Multi-Temporal Landsat Images to Monitor Urban Growth of Kirkuk Governorate by Tabark Y. Gehad, Nejat Q. Omer, Nada S. Abdulmajeed

“…The Supervised Maximum Likelihood algorithm was utilized to categorize images into urban and non-urban areas, with accuracy rates ranging from 91.25% to 96.66% between 1990 and 2020. …”
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getphylo: rapid and automatic generation of multi-locus phylogenetic trees by T. J. Booth, S. Shaw, P. Cruz-Morales, T. Weber

“…Orthologues are identified heuristically by searching for singletons (single copy genes) across all input genomes and the phylogeny is inferred from a concatenated alignment of all coding sequences by maximum likelihood. We performed a thorough benchmarking of getphylo against two existing tools, autoMLST and GTDB-tk, to show that it can produce trees of comparable quality in a fraction of the time. …”
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Accuracy Evaluation of Standardized Precipitation Index (SPI) Estimation under Conventional Assumption in Yeşilırmak, Kızılırmak, and Konya Closed Basins, Turkey by Mehmet Ali Hinis, Mehmet Selim Geyikli

“…In terms of parameter estimation methods, L-moments for 3-month series and maximum likelihood approaches for 12-month series were most dominant.…”
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CKF-Based Visual Inertial Odometry for Long-Term Trajectory Operations by Trung Nguyen, George K. I. Mann, Andrew Vardy, Raymond G. Gosine

“…The optimization process is terminated using the maximum likelihood estimate based criteria. For comparison, this paper also develops a second solution to integrate VIO estimation with ranging measurements. …”
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Using Futures Prices and Analysts’ Forecasts to Estimate Agricultural Commodity Risk Premiums by Gonzalo Cortazar, Hector Ortega, José Antonio Pérez

“…Calibration is achieved using a Kalman filter and maximum likelihood, with data from futures markets and analysts’ forecasts. …”
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High-energy Neutrino Source Cross-correlations with Nearest-neighbor Distributions by Zhuoyang Zhou, Jessi Cisewski-Kehe, Ke Fang, Arka Banerjee

“…In this paper, we investigate a framework for identifying and statistically evaluating the cross-correlations between IceCube data and an astrophysical source catalog based on the k -nearest-neighbor cumulative distribution functions ( k NN-CDFs). We propose a maximum likelihood estimation procedure for inferring the true proportions of astrophysical neutrinos in the point-source data. …”
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A Review of the Psyllid Genus <i>Epipsylla</i> (Hemiptera, Psyllidae) from the Chinese Mainland with Phylogenetic Considerations and the Description of a New Species by Zhixin He, Daniel Burckhardt, Xinyu Luo, Rongzhen Xu, Wanzhi Cai, Fan Song

“…The results of the molecular phylogenetic analysis using the maximum likelihood method support the assignment to Ciriacreminae.…”
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Change Detection Analysis and Deforestation Rates in Oluwa Forest Reserve, Ondo State, Nigeria by J.O. Mephors, O.S. Afolabi, O.M. Ogoliegbune, I.S. Adamu, A.R. Orunkoyi

“…This study examined the use of GIS and remote sensing techniques to gain a quantitative understanding of the spatiotemporal dynamics of LULC. Maximum likelihood classifier approach was used to detect LULC changes in the study area of 1989 to 2019 using three Landsat images from 1989, 2004 and 2019. …”
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Evaluating the accuracy of hyperspectral and multispectral images in wetland cover classification using data mining models (Case study: Shadegan wetland) by Hamid Bagheri, Rahime Rostami

“…Due to the spectral similarity between different plant species of wetlands and plants along the wetlands and agricultural lands, this is faced with problems using multispectral data and hyperspectral data can be very useful in this regard. in this study power of hyperspectral and multispectral sensors in identifying the characteristics of the wetland and the ability of ETM + (2011), Hyperion (2011) and ALI (2011) sensors to study the characteristics of Shadegan wetland during 1390 and different spectral indices with a suitable combination of The satellite imagery bands of these sensors were compared as input to a variety of classification methods including maximum likelihood, minimum distance, neural network and support vector machine. …”
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Screening of multi deep learning-based de novo molecular generation models and their application for specific target molecular generation by Yishu Wang, Mengyao Guo, Xiaomin Chen, Dongmei Ai

“…Moreover, we propose an integrated end-to-end neural network learning framework based on one complete encoder-decoder architecture transformer model: Transfer Text-to-Text Transformer (T5), by learning the embedding vector representation space of conditional molecular properties to encode and guide the vector representation of SMILES sequences, resulting in the output of the final decoder block with a softmax output (maximum likelihood objective). Moreover, we evaluated the performance of these NLP-based generation models and another new model architecture based on a selective state space and selected the best approach jointing a transfer learning strategy for de novo drug discovery to target L858R/T790M/C797S-mutant EGFR in non-small cell lung cancer.…”
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Technical and cost efficiency analysis of irrigated onion production insight from smallholders irrigated onion farmers in north East Amhara National Regional State, Ethiopia by Kindye Ayen, Tariku Kidane, Adane Wubet

“…A single-step Cobb–Douglas stochastic frontier model was used to estimate both the technical and cost efficiency of irrigated onion production.ResultsThe results from the maximum likelihood stochastic frontier model result indicated that the technical efficiency in onions was influenced by the age of the household head, slope of the land, number of extension contacts with development agents, distance from the sampled respondent’s residence to the office of the kebele agriculture office, and the number of oxen owned by the sampled households. …”
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An Overview of Composite Standard Elastic-Net Distribution Based on Complex Wavelet Coefficients by Tahani A. Aloafi, Hassan M. Aljohani

“…Statistical tools have changed significantly in the past decade; when the maximum likelihood method is usually applied, it provides an inaccurate solution due to its unsuitable properties and causes problems in fit. …”
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Assessing Landsat Processing Levels and Support Vector Machine Classification by Nehad Al-Salmany, Taghreed A. Naji

“…Conversely, when using the maximum-likelihood classifier, the highest accuracy (83.06%) was achieved with FLAASH. …”
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Statistical analysis of stress–strength in a newly inverted Chen model from adaptive progressive type-Ⅱ censoring and modelling on light-emitting diodes and pump motors by Refah Alotaibi, Mazen Nassar, Zareen A. Khan, Ahmed Elshahhat

“…The inferences are based on two estimation approaches: maximum likelihood and Bayesian. The Bayes estimates are obtained with the Markov Chain Monte Carlo sampling process leveraging the squared error and LINEX loss functions. …”
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