Classical and Bayesian Approach in Estimation of Scale Parameter of Nakagami Distribution by Kaisar Ahmad, S. P. Ahmad, A. Ahmed

“…Nakagami distribution is considered. The classical maximum likelihood estimator has been obtained. Bayesian method of estimation is employed in order to estimate the scale parameter of Nakagami distribution by using Jeffreys’, Extension of Jeffreys’, and Quasi priors under three different loss functions. …”
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Nonparametric spatio-temporal modeling: Contruction of a geographically and temporally weighted spline regression by Sifriyani, Syaripuddin, M. Fathurahman, Nariza Wanti Wulan Sari, Meirinda Fauziyah, Andrea Tri Rian Dani, Raudhatul Jannah, S. Dwi Juriani, Ratna Kusuma

“…The research aims to develop the GTWSNR model to overcome these challenges and uses the Maximum Likelihood Estimator (MLE) to estimate the model. …”
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Comparison of Phase Estimation Methods for Quantitative Susceptibility Mapping Using a Rotating-Tube Phantom by Kathryn E. Keenan, Ben P. Berman, Slávka Rýger, Stephen E. Russek, Wen-Tung Wang, John A. Butman, Dzung L. Pham, Joseph Dagher

“…For multiecho sequences, a maximum-likelihood method was most reliable with Pr (relative error <0.1) = 0.97. …”
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Mixture of Lindley and Lognormal Distributions: Properties, Estimation, and Application by A. S. Al-Moisheer

“…First, the model is formulated, and some of its statistical properties are studied. Next, maximum likelihood estimation of the parameters of the model is considered, and the performance of the estimators of the parameters of the proposed models is evaluated via simulation. …”
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Truncated Cauchy Power Odd Fréchet-G Family of Distributions: Theory and Applications by M. Shrahili, I. Elbatal

“…We investigate the maximum likelihood method for predicting model parameters of the new family. …”
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Alpha Power Transformed Log-Logistic Distribution with Application to Breaking Stress Data by Maha A. Aldahlan

“…The model parameters are estimated using maximum likelihood method of estimation. The simulation study is performed to investigate the effectiveness of the estimates. …”
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Probabilistic decoding algorithm for quantum stabilizer codes by XIAO Fang-ying, CHEN Han-wu

“…To improve the performance of quantum decoding algorithm,a quantum probabilistic decoding algorithm（QPDA） based on the check matrix for quantum stabilizer codes was proposed.To achieve low error rates the error op-erator with the minimum quantum weight was chosen and to shorten the time of decoding a quantum standard array（QSA） was constructed before decoding.Comparing with the quantum maximum likelihood decoding algorithm,the QPAD improves the reliability of degenerate decoding due to uniform decoding methods for degenerate and non-degenerate codes,furthermore,has less complexity due to does not require pre-search the bases of vector space cor-responding to the error operator.…”
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Parameter Estimation for p-Order Random Coefficient Autoregressive (RCA) Models Based on Kalman Filter by Mohammed Benmoumen, Jelloul Allal, Imane Salhi

“…This algorithm combines quasi-maximum likelihood method, the Kalman filter, and the simulated annealing method. …”
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Variable Selection of High-Dimensional Spatial Autoregressive Panel Models with Fixed Effects by Miaojie Xia, Yuqi Zhang, Ruiqin Tian

“…Then, a penalized quasi-maximum likelihood is developed for variable selection and parameter estimation in the transformed panel model. …”
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Bernoulli Poisson Moment Exponential Distribution: Mathematical Properties, Regression Model, and Applications by Amani Alrumayh

“…A count regression model is also proposed based on this distribution. The maximum likelihood estimation method is used to estimate the model parameters. …”
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D-Optimal Design for a Causal Structure for Completely Randomized and Random Blocked Experiments by Zaher Kmail, Kent Eskridge

“…In this research, search algorithms are used to produce a D-optimal design for a SEM for three-stage least squares and full information maximum likelihood estimators. Then, a D-optimal design for the estimate of the model parameters of a mixed-effects SEM is obtained. …”
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Modelling to Engineering Data Using a New Class of Continuous Models by I. Elbatal, Naif Alotaibi

“…We discuss the estimation of the model parameters by the maximum likelihood (MLL) estimations. Simulations are carried out to show the consistency and efficiency of parameter estimates, and finally, real data sets are used to demonstrate the flexibility and potential usefulness of the proposed family of algorithms by using the TLW exponential model as example of the new suggested family.…”
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Kibria–Lukman Hybrid Estimator for Handling Multicollinearity in Poisson Regression Model: Method and Application by Hleil Alrweili

“…However, when explanatory variables in the model are correlated, the estimation of regression coefficients using the maximum likelihood estimator (MLE) can be compromised by multicollinearity. …”
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Estimation for a Second-Order Jump Diffusion Model from Discrete Observations: Application to Stock Market Returns by Tianshun Yan, Yanyong Zhao, Shuanghua Luo

“…We develop an appropriate maximum likelihood approach to estimate model parameters. …”
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A New Extension of the Exponentiated Weibull Model Mathematical Properties and Modelling by Majdah Mohammed Badr, Amal T. Badawi, Alya S. Alzubidi

“…Model parameters were estimated using the maximum likelihood technique (ML). The behavior of the various estimators was investigated using a simulated exercise. …”
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Recovering Decay Rates from Noisy Measurements with Maximum Entropy in the Mean by Henryk Gzyl, Enrique Ter Horst

“…We show how to obtain an estimator with the noise filtered out, and using simulated data, we compare the performance of our method with the Bayesian and maximum likelihood approaches.…”
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Molecular phylogenetic studies on the lichenicolous Xanthoriicola physciae reveal Antarctic rock-inhabiting fungi and Piedraia species among closest relatives in the Teratosphaeria... by C. Ruibal, A.M. Millanes, D.L. Hawksworth

“…Sequences of the nLSU region were obtained from 11 specimens of X. physciae, which formed a single clade supported both by parsimony (91 %), and maximum likelihood (100 %) bootstraps, and Bayesian Posterior Probabilities (1.0). …”
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Alpha Power Transformation of the Lindley Probability Distribution by Shibiru Jabessa Dugasa, Ayele Taye Goshu, Butte Gotu Arero

“…Its properties including moments, moment-generating and quantile functions are obtained. The maximum likelihood method is derived for parameter estimation of the model. …”
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Inferences for Generalized Pareto Distribution Based on Progressive First-Failure Censoring Scheme by Rashad M. El-Sagheer, Taghreed M. Jawa, Neveen Sayed-Ahmed

“…Finally, the performance of Bayes estimates is compared with that of maximum likelihood estimates through a Monte Carlo simulation study.…”
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Biaxial fatigue tests of notched specimens for AISI 304L stainless steel by G. Beretta, V. Chaves, A. Navarro

“…The S-N curves were constructed following the ASTM E739 standard and the fatigues limits were calculated following the method of maximum likelihood proposed by Bettinelli. The crack direction along the surface was analysed, with especial attention to the crack initiation zones. …”
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