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Relevant bibliographies by topics / Bayesian analysis, Maximum Likelihood Estimation (MLE)

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Journal articles
Dissertations / Theses
Book chapters
Conference papers

Academic literature on the topic 'Bayesian analysis, Maximum Likelihood Estimation (MLE)'

Author: Grafiati

Published: 4 June 2021

Last updated: 13 February 2022

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Journal articles on the topic "Bayesian analysis, Maximum Likelihood Estimation (MLE)"

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Zhang, Zhiyong, Fumiaki Hamagami, Lijuan Lijuan Wang, John R. Nesselroade, and Kevin J. Grimm. "Bayesian analysis of longitudinal data using growth curve models." International Journal of Behavioral Development 31, no. 4 (2007): 374–83. http://dx.doi.org/10.1177/0165025407077764.

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Bayesian methods for analyzing longitudinal data in social and behavioral research are recommended for their ability to incorporate prior information in estimating simple and complex models. We first summarize the basics of Bayesian methods before presenting an empirical example in which we fit a latent basis growth curve model to achievement data from the National Longitudinal Survey of Youth. This step-by-step example illustrates how to analyze data using both noninformative and informative priors. The results show that in addition to being an alternative to the maximum likelihood estimation

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Darwis, Darwis, Sunusi N, and Kresna A.J. "Parameter Estimation of the Temporal Point Process Model through the Bayesian Approach (Case Study : Malaria Disease Data from Wahidin Hospital in Makassar City)." Journal of Data Analysis 2, no. 2 (2020): 71–79. http://dx.doi.org/10.24815/jda.v2i2.15264.

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Penelitian ini bertujuan mengestimasi parameter melalui pendekatan Bayesian dari model temporal point process. Paramater intensitas bersyarat model tersebut dipandang sebagai suatu renewal process yang selanjutnya digunakan melalui pendekatan Squared Error Loss Function (SELF). Parameter intensitas bersyarat model temporal point process diestimasi menggunakan metode maximum likelihood estimation melalui persamaan likelihood point process. Selain itu, penelitian ini mengkaji metode estimasi maksimum likelihood dan metode Bayes untuk menganalis fungsi resiko dari hasil penaksir parameter intensi

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Seenoi, Palakorn, Piyapatr Busababodhin, and Jeong-Soo Park. "Bayesian Inference in Extremes Using the Four-Parameter Kappa Distribution." Mathematics 8, no. 12 (2020): 2180. http://dx.doi.org/10.3390/math8122180.

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Maximum likelihood estimation (MLE) of the four-parameter kappa distribution (K4D) is known to be occasionally unstable for small sample sizes and to be very sensitive to outliers. To overcome this problem, this study proposes Bayesian analysis of the K4D. Bayesian estimators are obtained by virtue of a posterior distribution using the random walk Metropolis–Hastings algorithm. Five different priors are considered. The properties of the Bayesian estimators are verified in a simulation study. The empirical Bayesian method turns out to work well. Our approach is then compared to the MLE and the

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Yanuar, Ferra, Sisca Wulandari, and Izzati Rahmi HG. "ANALISIS SURVIVAL UNTUK PARAMETER SKALA DARI DISTRIBUSI WEIBULL MENGGUNAKAN MLE DAN METODE BAYESIAN." BAREKENG: Jurnal Ilmu Matematika dan Terapan 15, no. 1 (2021): 147–56. http://dx.doi.org/10.30598/barekengvol15iss1pp147-156.

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Modeling of survival data is necessary and important to do. Survival data is generally assumed to have a Weibull distribution. Bayesian approach has been implemented to estimate the parameter in such this survival analysis. This study purposes to compare the performance of the Maximum Likelihood and Bayesian using Invers Gamma as prior conjugate for estimating the survival function of scale parameter of Weibull distribution. The comparisons are made through simulation study. The best performance of both estimators is chosen based on the lowest value of absolute bias and the mean square error.

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Noor, Farzana, Saadia Masood, Mehwish Zaman, et al. "Bayesian Analysis of Inverted Kumaraswamy Mixture Model with Application to Burning Velocity of Chemicals." Mathematical Problems in Engineering 2021 (May 18, 2021): 1–18. http://dx.doi.org/10.1155/2021/5569652.

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Burning velocity of different chemicals is estimated using a model from mixed population considering inverted Kumaraswamy (IKum) distribution for component parts. Two estimation techniques maximum likelihood estimation (MLE) and Bayesian analysis are applied for estimation purposes. BEs of a mixture model are obtained using gamma, inverse beta prior, and uniform prior distribution with two loss functions. Hyperparameters are determined through the empirical Bayesian method. An extensive simulation study is also a part of the study which is used to foresee the characteristics of the presented m

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Leoni, Leonardo, Farshad BahooToroody, Saeed Khalaj, Filippo De Carlo, Ahmad BahooToroody, and Mohammad Mahdi Abaei. "Bayesian Estimation for Reliability Engineering: Addressing the Influence of Prior Choice." International Journal of Environmental Research and Public Health 18, no. 7 (2021): 3349. http://dx.doi.org/10.3390/ijerph18073349.

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Over the last few decades, reliability analysis has attracted significant interest due to its importance in risk and asset integrity management. Meanwhile, Bayesian inference has proven its advantages over other statistical tools, such as maximum likelihood estimation (MLE) and least square estimation (LSE), in estimating the parameters characterizing failure modelling. Indeed, Bayesian inference can incorporate prior beliefs and information into the analysis, which could partially overcome the lack of data. Accordingly, this paper aims to provide a closed-mathematical representation of Bayesi

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Maposa, D., J. J. Cochran, M. Lesaoana, and C. Sigauke. "Estimating high quantiles of extreme flood heights in the lower Limpopo River basin of Mozambique using model based Bayesian approach." Natural Hazards and Earth System Sciences Discussions 2, no. 8 (2014): 5401–25. http://dx.doi.org/10.5194/nhessd-2-5401-2014.

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Abstract. In this paper we discuss a comparative analysis of the maximum likelihood (ML) and Bayesian parameter estimates of the generalised extreme value (GEV) distribution. We use a Markov Chain Monte Carlo (MCMC) Bayesian method to estimate the parameters of the GEV distribution in order to estimate extreme flood heights and their return periods in the lower Limpopo River basin of Mozambique. The return periods of extreme flood heights based on the Bayesian approach show an improvement over the frequentist approach based on the maximum likelihood estimation (MLE) method. However, both appro

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Almetwally, Ehab M., Mohamed A. H. Sabry, Randa Alharbi, Dalia Alnagar, Sh A. M. Mubarak, and E. H. Hafez. "Marshall–Olkin Alpha Power Weibull Distribution: Different Methods of Estimation Based on Type-I and Type-II Censoring." Complexity 2021 (March 8, 2021): 1–18. http://dx.doi.org/10.1155/2021/5533799.

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This paper introduces the new novel four-parameter Weibull distribution named as the Marshall–Olkin alpha power Weibull (MOAPW) distribution. Some statistical properties of the distribution are examined. Based on Type-I censored and Type-II censored samples, maximum likelihood estimation (MLE), maximum product spacing (MPS), and Bayesian estimation for the MOAPW distribution parameters are discussed. Numerical analysis using real data sets and Monte Carlo simulation are accomplished to compare various estimation methods. This novel model’s supremacy upon some famous distributions is explained

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Dey, Sanku, and Fernando Antonio Moala. "Estimation of reliability of multicomponent stress-strength of a bathtub shape or increasing failure rate function." International Journal of Quality & Reliability Management 36, no. 2 (2019): 122–36. http://dx.doi.org/10.1108/ijqrm-01-2017-0012.

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Purpose The purpose of this paper is to deal with the Bayesian and non-Bayesian estimation methods of multicomponent stress-strength reliability by assuming the Chen distribution. Design/methodology/approach The reliability of a multicomponent stress-strength system is obtained by the maximum likelihood (MLE) and Bayesian methods and the results are compared by using MCMC technique for both small and large samples. Findings The simulation study shows that Bayes estimates based on γ prior with absence of prior information performs little better than the MLE with regard to both biases and mean s

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Wang, Juan. "Data Analysis of Step-Stress Accelerated Life Test with Random Group Effects under Weibull Distribution." Mathematical Problems in Engineering 2020 (February 5, 2020): 1–11. http://dx.doi.org/10.1155/2020/4898123.

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Step-stress accelerating life test (SSALT), aiming to predict the failure behavior under use condition by the data collected from elevated test setting, is implemented to specimen with time-varying stress levels. Typical testing protocols in SSALT, such as subsampling, cannot guarantee complete randomization and thus result in correlated observations among groups. To consider the random effects from the group-to-group variation, we build a nonlinear mixed effect model (NLMM) with the assumption of Weibull distribution for life time data analysis from SSALT. Both maximum likelihood estimation (

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Dissertations / Theses on the topic "Bayesian analysis, Maximum Likelihood Estimation (MLE)"

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Ji, Yuxiong. "Distribution-based Approach to Take Advantage of Automatic Passenger Counter Data in Estimating Period Route-level Transit Passenger Origin-Destination Flows:Methodology Development, Numerical Analyses and Empirical Investigations." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1299688722.

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Naeem, Muhammad Farhan. "Analysis of an Ill-posed Problem of Estimating the Trend Derivative Using Maximum Likelihood Estimation and the Cramér-Rao Lower Bound." Thesis, Linnéuniversitetet, Institutionen för fysik och elektroteknik (IFE), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-95163.

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The amount of carbon dioxide in the Earth’s atmosphere has significantly increased in the last few decades as compared to the last 80,000 years approximately. The increase in carbon dioxide levels are affecting the temperature and therefore need to be understood better. In order to study the effects of global events on the carbon dioxide levels, one need to properly estimate the trends in carbon dioxide in the previous years. In this project, we will perform the task of estimating the trend in carbon dioxide measurements taken in Mauna Loa for the last 46 years, also known as the Keeling Curve

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Gianfelice, Paulo Roberto de Lima. "Bayesian and classical inference for extensions of Geometric Exponential distribution with applications in survival analysis under the presence of the data covariated and randomly censored /." Presidente Prudente, 2020. http://hdl.handle.net/11449/192924.

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Orientador: Fernando Antonio Moala<br>Abstract: This work presents a study of probabilistic modeling, with applications to survival analysis, based on a probabilistic model called Exponential Geometric (EG), which o ers great exibility for the statistical estimation of its parameters based on samples of life time data complete and censored. In this study, the concepts of estimators and lifetime data are explored under random censorship in two cases of extensions of the EG model: the Extended Geometric Exponential (EEG) and the Generalized Extreme Geometric Exponential (GE2). The work still con

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Motrunich, Anastasiia. "Estimation des paramètres pour les séquences de Markov avec application dans des problèmes médico-économiques." Thesis, Le Mans, 2015. http://www.theses.fr/2015LEMA1009/document.

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Dans la première partie de cette thèse, nous considérons plusieurs problèmes d'estimation de paramètre de dimension finie pour les séquences de Markov dans l'asymptotique des grands échantillons. Le comportement asymptotique des estimateurs bayésiens et les estimateurs obtenus par la méthode des moments sont décrits. Nous montrons que sous les conditions de régularité ces estimateurs sont consistants et asymptotiquement normaux et que l'estimateur bayésien est asymptotiquement efficace. Les estimateur-processus du maximum de vraisemblance un-pas et deux-pas sont étudiés. Ces estimateurs nous p

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Δασκαλάκη, Ιωάννα. "Εκτίμηση των παραμέτρων της διπαραμετρικής εκθετικής κατανομής από ένα διπλά διακεκομμένο δείγμα". Thesis, 2010. http://nemertes.lis.upatras.gr/jspui/handle/10889/4019.

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Η παρούσα μεταπτυχιακή διατριβή εντάσσεται ερευνητικά στην περιοχή της Στατιστικής Θεωρίας Αποφάσεων και ειδικότερα στην εκτίμηση των παραμέτρων στο μοντέλο της διπαραμετρικής εκθετικής κατανομής με παράμετρο θέσης μ και παράμετρο κλίμακος σ. Θεωρούμε ένα δείγμα n τυχαίων μεταβλητών, καθεμία από τις οποίες ακολουθεί την διπαραμετρική εκθετική κατανομή. Λογοκρίνουμε κάποιες αρχικές παρατηρήσεις και έστω ότι τερματίζουμε το πείραμά μας πριν αποτύχουν όλες οι συνιστώσες. Τότε προκύπτει ένα διπλά διακεκομμένο δείγμα διατεταγμένων παρατηρήσεων. Η εκτίμηση των παραμέτρων της διπαραμετρικής εκθετικής

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Book chapters on the topic "Bayesian analysis, Maximum Likelihood Estimation (MLE)"

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Campos-Knupp, Diego, Luciano G. da Silva, Luiz Bevilacqua, Augusto C. N. R. Galeão, and Antônio José da Silva Neto. "Inverse Analysis of a New Anomalous Diffusion Model Employing Maximum Likelihood and Bayesian Estimation." In Mathematical Modeling and Computational Intelligence in Engineering Applications. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-38869-4_7.

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Fer, Istem. "Analysis of Vegetation-Water Interactions: Application and Comparison of Maximum-Likelihood Estimation and Bayesian Inference." In Forest-Water Interactions. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-26086-6_9.

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Ahmad, Ishfaq, Alam Zeb Khan, Mirza Barjees Baig, and Ibrahim M. Almanjahie. "Flood Frequency Analysis Using Bayesian Paradigm." In Advances in Environmental Engineering and Green Technologies. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-5225-9771-1.ch005.

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At-site flood frequency analysis (FFA) of extreme hydrological events under Bayesian paradigm has been carried out and compared with frequentist paradigm of maximum likelihood estimation (MLE). The main objective of this chapter is to identify the best approach between Bayesian and frequentist one for at-site FFA. As a case study, the data of only two stations were used, Kotri and Rasul, and Bayesian and MLE approaches were implemented. Most commonly used tests were applied for checking initial assumptions. Goodness of fit (GOF) tests were used to identify the best model, which indicated that the generalized extreme value (GEV) distribution appeared to be best fitted for both stations. Under Bayesian paradigm, quantile estimates are constructed using Markov Chain Monte Carlo (MCMC) simulation method for their respective returned periods and non-exceedance probabilities. For MCMC simulations, as compared to other sampler, the M-H sampling technique was used to generate a large number of parameters. The analysis indicated that the standard errors of the parameters' estimates and ultimately the quantiles' estimates using Bayesian methods remained less as compared to maximum likelihood estimation (MLE), which shows the superiority of Bayesian methods over conventional ones in this study. Further, the safety amendments under two techniques were also calculated, which also show the robustness of Bayesian method over MLE. The outcomes of these analyses can be used in the selection of better design criteria for water resources management, particularly in flood mitigation.

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Dragan, Dejan, Tomaž Kramberger, and Darja Topolšek. "Efficiency and Travel Agencies." In Sustainable Logistics and Strategic Transportation Planning. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-5225-0001-8.ch010.

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The chapter deals with Bayesian structural equation modeling (SEM) for the case of travel agencies. The focus of research is the investigation of possible impacts of external integration with transport suppliers on the efficiency of travel agencies. In order to calculate the efficiency, the data envelopment analysis was used. For the construction of the measurement part of the model, the confirmatory factor analysis (CFA) was conducted, while its structural part was developed by the means of SEM procedure. When conducting the CFA and SEM procedures, the Bayesian estimation method was employed. Its performance was also compared with the maximum likelihood method and the fit indices of both methods were inspected. The results show that the derived model fits well to the real data. The study confirms certain positive effects of the external integration on the efficiency. This finding could represent an important guideline for the managers of the travel agencies.

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Conference papers on the topic "Bayesian analysis, Maximum Likelihood Estimation (MLE)"

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Yu, Bo Yang, Tomonori Honda, Gina M. Zak, et al. "Prognosis of Component Degradation Under Uncertainty: A Method for Early Stage Design of a Complex Engineering System." In ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/esda2012-82420.

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This paper proposes a method that dynamically improves a statistical model of system degradation by incorporating uncertainty. The method is illustrated by a case example of fouling, or degradation, in a heat exchanger in a cogeneration desalination plant. The goal of the proposed method is to select the best model from several representative condenser fouling models including linear, falling rate, and asymptotic fouling, and to validate and improve model parameters over the duration of operation. Maximum likelihood estimation (MLE) was applied to obtain a stochastic distribution of condenser

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Tran, Trong-Hieu, Tan-Phat Phan, Paul C. P. Chao, Yu-Jen Wang, and Chun-Chieh Wang. "A Six-DOF Force/Torque Sensor for Collaborative Robot and its Calibration Method." In ASME 2017 Conference on Information Storage and Processing Systems collocated with the ASME 2017 International Technical Conference and Exhibition on Packaging and Integration of Electronic and Photonic Microsystems. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/isps2017-5476.

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This study presents a new six-DOF force/torque sensor and its calibration method for a “collaborative robot or cobot”. This new calibration method applies the so-called “maximum likelihood estimation (MLE)”. MLE is used to determine and identify the parameters related to applied torques/forces and resulted deformations at varied locations of the sensor structure. Formulating the relations in a vector-matrix form, such parameters are captured as the coefficients in a matrix relating torques/forces to angular/linear deformations in different directions. In addition to applying MLE, finite elemen

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Raileanu, Valentin. "Analiza temperaturilor maxime și minime anuale în Chișinău." In Starea actuală a componentelor de mediu. Institute of Ecology and Geography, Republic of Moldova, 2019. http://dx.doi.org/10.53380/9789975315593.18.

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The article briefly describes the fields of application of the theory of extreme values, including climatology. The data format and the analysis methods of the annual maxima and minima temperatures in Chisinau are presented. Free R software and the GUI in2extRemes graphical package are used. Estimating the parameters of the Generalized Extreme Value distribution and return levels vs return periods is done using the Maximum Likelihood Estimation (MLE) method.

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Xu, Yanwen, and Pingfeng Wang. "A Comparison of Numerical Optimizers in Developing High Dimensional Surrogate Models." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-97499.

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Abstract The Gaussian Process (GP) model has become one of the most popular methods to develop computationally efficient surrogate models in many engineering design applications, including simulation-based design optimization and uncertainty analysis. When more observations are used for high dimensional problems, estimating the best model parameters of Gaussian Process model is still an essential yet challenging task due to considerable computation cost. One of the most commonly used methods to estimate model parameters is Maximum Likelihood Estimation (MLE). A common bottleneck arising in MLE

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Azarkhail, M., and M. Modarres. "A Novel Bayesian Framework for Uncertainty Management in Physics-Based Reliability Models." In ASME 2007 International Mechanical Engineering Congress and Exposition. ASMEDC, 2007. http://dx.doi.org/10.1115/imece2007-41333.

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The physics-of-failure (POF) modeling approach is a proven and powerful method to predict the reliability of mechanical components and systems. Most of POF models have been originally developed based upon empirical data from a wide range of applications (e.g. fracture mechanics approach to the fatigue life). Available curve fitting methods such as least square for example, calculate the best estimate of parameters by minimizing the distance function. Such point estimate approaches, basically overlook the other possibilities for the parameters and fail to incorporate the real uncertainty of emp

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Raileanu, Valentin. "Utilizarea teoriei valorilor extreme în climatologie." In Starea actuală a componentelor de mediu. Institute of Ecology and Geography, Republic of Moldova, 2019. http://dx.doi.org/10.53380/9789975315593.17.

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The article briefly describes the history and fields of application of the theory of extreme values, including climatology. The data format, the Generalized Extreme Value (GEV) probability distributions with Bock Maxima, the Generalized Pareto (GP) distributions with Point of Threshold (POT) and the analysis methods are presented. Estimating the distribution parameters is done using the Maximum Likelihood Estimation (MLE) method. Free R software installation, the minimum set of required commands and the GUI in2extRemes graphical package are described. As an example, the results of the GEV anal

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Huspeni, Paul J., Ly Le, Wei Liu, Elli Saravanos, and Shannon Adkins. "Weibull Analysis Method Applied to Optical Fiber Breaking Stress Data." In ASME 2009 InterPACK Conference collocated with the ASME 2009 Summer Heat Transfer Conference and the ASME 2009 3rd International Conference on Energy Sustainability. ASMEDC, 2009. http://dx.doi.org/10.1115/interpack2009-89217.

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This paper details application of a 2-parameter Weibull maximum likelihood estimation (MLE) method to optical fiber breaking stress data. Optical fiber is used in a broad range of telecommunications applications and its associated performance in fabricated component assemblies is of critical importance to the proper functioning of telecom networks. Fiber optic components incorporating stripped optical fiber include optical couplers, optical splitters, WDM devices, connectors, and mechanical and fusion splices. The strength of optical fiber in component assemblies is dependent upon numerous asp

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Xiao, Jie, and Bohdan Kulakowski. "Hybrid Genetic Algorithm: A Robust Parameter Estimation Technique and Its Application to Heavy Duty Vehicles." In ASME 2003 International Mechanical Engineering Congress and Exposition. ASMEDC, 2003. http://dx.doi.org/10.1115/imece2003-41934.

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This study aims at establishing an accurate yet efficient parameter estimation strategy for developing dynamic vehicle models that can be easily implemented for simulation and controller design purposes. Generally, conventional techniques such as Least Square Estimation (LSE), Maximum Likelihood Estimation (MLE), and Instrumental Variable Methods (IVM), can deliver sufficient estimation results for given models that are linear-in-the-parameter. However, many identification problems in the engineering world are very complex in nature and are quite difficult to solve by those techniques. For the

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Martin, Jay D., and Timothy W. Simpson. "A Study on the Use of Kriging Models to Approximate Deterministic Computer Models." In ASME 2003 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/detc2003/dac-48762.

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The use of kriging models for approximation and global optimization has been steadily on the rise in the past decade. The standard approach used in the Design and Analysis of Computer Experiments (DACE) is to use an Ordinary kriging model to approximate a deterministic computer model. Universal and Detrended kriging are two alternative types of kriging models. In this paper, a description on the basics of kriging is given, highlighting the similarities and differences between these three different types of kriging models and the underlying assumptions behind each. A comparative study on the us

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Peng, B., and H. D. Espinosa. "Fracture Size Effect in Ultrananocrystalline Diamond: Weibull Theory Applicability." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-60070.

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Strength characterization and analysis of fracture size effect in ultrananocrystalline diamond (UNCD) thin films are presented. In this work, we report the changes in mechanical properties of UNCD by the addition of nitrogen gas to the Ar/CH4 microwave plasma. Both undoped and doped UNCD films show a decrease in fracture strength with an increase in specimen size. The strength data, obtained by using the membrane deflection experiment (MDE) developed at Nothwestern University, is interpreted using Weibull statistics. The capability of the theory is examined in conjunction with detailed fractog

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