Relevant bibliographies by topics / Maximum likelihood method - MMV

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  2. Dissertations / Theses
  3. Books
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Academic literature on the topic 'Maximum likelihood method - MMV'

Author: Grafiati
Published: 4 June 2021
Last updated: 13 February 2022

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Journal articles on the topic "Maximum likelihood method - MMV"

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Mülthei, H. N. "Iterative continuous maximum-likelihood reconstruction method." Mathematical Methods in the Applied Sciences 15, no. 4 (May 1992): 275–86. http://dx.doi.org/10.1002/mma.1670150405.

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Mülthei, H. N., B. Schorr, and W. Törnig. "On properties of the iterative maximum likelihood reconstruction method." Mathematical Methods in the Applied Sciences 11, no. 3 (May 1989): 331–42. http://dx.doi.org/10.1002/mma.1670110303.

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Guo, Qingqian, Changyu Ma, Xin Zhang, Yajie Xu, Meisheng Fan, Peng Yu, Tao Hu, Yan Chang, and Xiaodong Yang. "SQUID-Based Magnetic Resonance Imaging at Ultra-Low Field Using the Backprojection Method." Concepts in Magnetic Resonance Part B, Magnetic Resonance Engineering 2020 (October 22, 2020): 1–11. http://dx.doi.org/10.1155/2020/8882329.

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Ultra-low field magnetic resonance imaging (ULF MRI) is an effective imaging technique that applies the ultrasensitive detector of superconducting quantum interference device (SQUID) sensor to detect the MR signal at a microtesla field range. In this work, we designed and developed a SQUID-based ULF MRI system with a frequency-adjustable measurement field, the performance of which was characterized via water phantoms. In order to enhance the MR signals, a 500 mT Halbach magnet was used to prepolarize the magnetization of the sample prior to excitation. The signal-to-noise-ratio (SNR) of the spin-echo- (SE-) based pulse sequence can reach up to 70 in a single scan. The images were then reconstructed successfully by using the maximum likelihood expectation maximization (MLEM) algorithm based on the backprojection imaging method. It was demonstrated that an in-plane resolution of 1.8 × 1.8 mm2 can be achieved which indicated the feasibility of SQUID-based MRI at the ULF.
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Annunziato, Mario, and Hanno Gottschalk. "CALIBRATION OF LÉVY PROCESSES USING OPTIMAL CONTROL OF KOLMOGOROV EQUATIONS WITH PERIODIC BOUNDARY CONDITIONS." Mathematical Modelling and Analysis 23, no. 3 (June 14, 2018): 390–413. http://dx.doi.org/10.3846/mma.2018.024.

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We present an optimal control approach to the problem of model calibration for Lévy processes based on an non-parametric estimation procedure of the measure. The optimization problem is related to the maximum likelihood theory of sieves [25] and is formulated with the Fokker-Planck-Kolmogorov approach [3, 4]. We use a generic spline discretization of the Lévy jump measure and select an adequate size of the spline basis using the Akaike Information Criterion (AIC) [12]. The first order necessary optimality conditions are derived based on the Lagrange multiplier technique in a functional space. The resulting Partial Integral-Differential Equations (PIDE) are discretized, numerically solved using a scheme composed of Chang-Cooper, BDF2 and direct quadrature methods, jointly to a non-linear conjugate gradient method. For the numerical solver of the Kolmogorov's forward equation we prove conditions for non-negativity and stability in the L1 norm of the discrete solution.
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McLaughlin, M. A., J. R. Mattox, J. M. Cordes, and D. J. Thompson. "Variability of CGRO/EGRET Gamma Ray Sources." International Astronomical Union Colloquium 160 (1996): 357–58. http://dx.doi.org/10.1017/s0252921100041889.

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We have developed a method for quantifying the flux variabilities of high energy gamma ray sources. We have applied this method to 128 sources listed in the second catalog of sources detected with the Energetic Gamma Ray Experiment Telescope (EGRET) (Thompson et. al. 1995). These sources include the Large Magellanic Cloud, 5 pulsars, 41 active galactic nuclei (AGN), and 81 sources not yet identified with known objects.Our data include photon maps (E > 100 MeV) from 134 EGRET viewing periods spanning a roughly 3year period. Each source was observed in 3-20 viewing periods ranging from a few days to 3 weeks in length. For each observation, a source flux was calculated using the method of maximum likelihood (Mattoxet al. 1996) which simultaneously estimates the strength of the Galactic and isotropic diffuse emission, and that of a point source distributed as the EGRET point spread function.
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SATOH, T., M. KOKA, W. KADA, A. YOKOYAMA, T. OHKUBO, A. YAMAZAKI, Y. ISHII, T. KAMIYA, and N. KOZAI. "EFFECTIVENESS OF A COMBINATION OF ML-EM AND STIM-CT IN PIXE-CT FOR BIOLOGICAL SPECIMEN." International Journal of PIXE 22, no. 01n02 (January 2012): 73–80. http://dx.doi.org/10.1142/s0129083512400025.

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In this study, we applied ML-EM (maximum likelihood expectation maximization) iterative algorithm and STIM-CT to a three dimension imaging technique of PIXE -CT for cellular analysis using 3 MeV proton microbeam with a diameter of 1 μm at TIARA (Takasaki Ion Accelerators for Advanced Radiation Application). The algorithm had been applied to tomography such as SPECT (Single Photon Emission Computed Tomography). It is also possible and suitable to apply the algorithm to PIXE-CT because the algorithm can be used to project images taking into account errors due to rare events. Energy loss of incident particles and absorption of X-rays, however, affect quantitative values dramatically in the case of PIXE -CT. We estimated those effects from density distribution of major elements measured by STIM-CT in this work. In order to show the appropriateness of this method, X-ray yield and absorption were calculated using density distribution of two-dimensional Shepp phantom. The PIXE-CT experiments were carried out using a dried unicellulate as a test sample placed on an automatic rotation stage, which made a full turn by rotating 360° at each step of 18° in vacuum. The results of those simulation and experiments have proved that this method is effective.
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Broze, Laurence, and Christian Gouriéroux. "Pseudo-maximum likelihood method, adjusted pseudo-maximum likelihood method and covariance estimators." Journal of Econometrics 85, no. 1 (July 1998): 75–98. http://dx.doi.org/10.1016/s0304-4076(97)00095-x.

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D’hooge, Elizabet, Pierre Becker, Dirk Stubbe, Anne-Cécile Normand, Renaud Piarroux, and Marijke Hendrickx. "Black aspergilli: A remaining challenge in fungal taxonomy?" Medical Mycology 57, no. 6 (December 11, 2018): 773–80. http://dx.doi.org/10.1093/mmy/myy124.

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AbstractAspergillus section Nigri is a taxonomically difficult but medically and economically important group. In this study, an update of the taxonomy of A. section Nigri strains within the BCCM/IHEM collection has been conducted. The identification accuracy of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) was tested and the antifungal susceptibilities of clinical isolates were evaluated. A total of 175 strains were molecularly analyzed. Three regions were amplified (ITS, benA, and caM) and a multi-locus phylogeny of the combined loci was created by using maximum likelihood analysis. The in-house MALDI-TOF MS reference database was extended and an identification data set of 135 strains was run against a reference data set. Antifungal susceptibility was tested for voriconazole, itraconazole, and amphotericin B, using the EUCAST method. Phylogenetic analysis revealed 18 species in our data set. MALDI-TOF MS was able to distinguish between A. brasiliensis, A. brunneoviolaceus, A. neoniger, A. niger, A. tubingensis, and A. welwitschiae of A. sect. Nigri. In the routine clinical lab, isolates of A. sect. Nigri are often identified as A. niger. However, in the clinical isolates of our data set, A. tubingensis (n = 35) and A. welwitschiae (n = 34) are more common than A. niger (n = 9). Decreased antifungal susceptibility to azoles was observed in clinical isolates of the /tubingensis clade. This emphasizes the importance of identification up to species level or at least up to clade level in the clinical lab. Our results indicate that MALDI-TOF MS can be a powerful tool to replace classical morphology.
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Ameta, Gaurav, Joseph K. Davidson, and Jami J. Shah. "Using Tolerance-Maps to Generate Frequency Distributions of Clearance and Allocate Tolerances for Pin-Hole Assemblies." Journal of Computing and Information Science in Engineering 7, no. 4 (July 13, 2007): 347–59. http://dx.doi.org/10.1115/1.2795308.

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A new mathematical model for representing the geometric variations of lines is extended to include probabilistic representations of one-dimensional (1D) clearance, which arise from positional variations of the axis of a hole, the size of the hole, and a pin-hole assembly. The model is compatible with the ASME/ ANSI/ISO Standards for geometric tolerances. Central to the new model is a Tolerance-Map (T-Map) (Patent No. 69638242), a hypothetical volume of points that models the 3D variations in location and orientation for a segment of a line (the axis), which can arise from tolerances on size, position, orientation, and form. Here, it is extended to model the increases in yield that occur when maximum material condition (MMC) is specified and when tolerances are assigned statistically rather than on a worst-case basis; the statistical method includes the specification of both size and position tolerances on a feature. The frequency distribution of 1D clearance is decomposed into manufacturing bias, i.e., toward certain regions of a Tolerance-Map, and into a geometric bias that can be computed from the geometry of multidimensional T-Maps. Although the probabilistic representation in this paper is built from geometric bias, and it is presumed that manufacturing bias is uniform, the method is robust enough to include manufacturing bias in the future. Geometric bias alone shows a greater likelihood of small clearances than large clearances between an assembled pin and hole. A comparison is made between the effects of choosing the optional material condition MMC and not choosing it with the tolerances that determine the allowable variations in position.
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Siegert, Thomas. "Vertical position of the Sun with γ-rays." Astronomy & Astrophysics 632 (November 29, 2019): L1. http://dx.doi.org/10.1051/0004-6361/201936659.

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We illustrate a method for estimating the vertical position of the Sun above the Galactic plane by γ-ray observations. Photons of γ-ray wavelengths are particularly well suited for geometrical and kinematic studies of the Milky Way because they are not subject to extinction by interstellar gas or dust. Here, we use the radioactive decay line of 26Al at 1.809 MeV to perform maximum likelihood fits to data from the spectrometer SPI on board the INTEGRAL satellite as a proof-of-concept study. Our simple analytic 3D emissivity models are line-of-sight integrated, and varied as a function of the Sun’s vertical position, given a known distance to the Galactic centre. We find a vertical position of the Sun of z0 = 15 ± 17 pc above the Galactic plane, consistent with previous studies, finding z0 in a range between 5 and 29 pc. Even though the sensitivity of current MeV instruments is several orders of magnitude below that of telescopes for other wavelengths, this result reveals once more the disregarded capability of soft γ-ray telescopes. We further investigate possible biases in estimating the vertical extent of γ-ray emission if the Sun’s position is set incorrectly, and find that the larger the true extent, the less is it affected by the observer position. In the case of 26Al with an exponential scale height of 150 pc (700 pc) in the inner (full) Galaxy, this may lead to misestimates of up to 25%.
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Dissertations / Theses on the topic "Maximum likelihood method - MMV"

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Costa, Sidney Tadeu Santiago. "Teoria de resposta ao item aplicada no ENEM." Universidade Federal de Goiás, 2017. http://repositorio.bc.ufg.br/tede/handle/tede/6944.

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With the note gotten in the Exame Nacional do Ensino Médio - ENEM the students can applay the vacant in diverse public institutions of superior education and programs of the government, for example, the program Universidade para Todos(Prouni) and the Fundo de Financiamento Estudantil (Fies). The ENEM uses a methodology of correction of the objective questions called Theory of Reply to the Item - TRI, that has some aspects that are different of the Classic Theory of the Tests - TCT. The main factor that determines the result of a citizen in a avaliativo process where if uses the TCT, is the number of correct answers, while in the TRI, beyond the amount of rightnesss is basic if to analyze which answers they are correct. The objective of this work is to explain what it is the TRI and as if it applies this methodology in evaluations of wide scale. A historical boarding of the logistic models used by the TRI and the justification of the existence of each parameter will be made that composes the main equation of the modeling. To determine each parameter that composes the model of the TRI and to calculate the final note of each candidate, a procedure of called optimization will be used Method of Maximum Probability - MMV. The computational tools in the work had been software R, with packages developed for application of the TRI and the Visual programming language beginner’s all-purpose symbolic instruction code to program functions, called as macros, in electronic spread sheets.
Com a nota obtida no Exame Nacional do Ensino Médio - ENEM os estudantes podem se candidatar a vagas em diversas instituições públicas de ensino superior e programas do governo, por exemplo, o programa Universidade para Todos (Prouni) e o Fundo de Financiamento Estudantil (Fies). O ENEM utiliza uma metodologia de correção das questões objetivas denominada Teoria de Resposta ao Item - TRI, que possui vários aspectos que são diferentes da Teoria Clássica dos Testes - TCT. O principal fator que determina o resultado de um sujeito em um processo avaliativo onde se utiliza a TCT, é o número de respostas corretas, enquanto na TRI, além da quantidade de acertos é fundamental se analisar quais respostas estão corretas. O objetivo deste trabalho é explicar o que é a TRI e como se aplica essa metodologia em avaliações de larga escala. Será feita uma abordagem histórica dos modelos logísticos utilizados pela TRI e a justificativa da existência de cada parâmetro que compõe a equação principal da modelagem. Para determinar cada parâmetro que compõe o modelo da TRI e calcular a nota final de cada candidato, será utilizado um procedimento de otimização denominado Método da Máxima Verossimilhança - MMV. As ferramentas computacionais no trabalho foram o software R, com pacotes desenvolvidos para aplicação da TRI e a linguagem de programação Visual Basic para programar funções, denominadas como macros, em planilhas eletrônicas.
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Al-Nashi, Hamid Rasheed. "A maximum likelihood method to estimate EEG evoked potentials /." Thesis, McGill University, 1985. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=72016.

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A new method for the estimation of the EEG evoked potential (EP) is presented in this thesis. This method is based on a new model of the EEG response which is assumed to be the sum of the EP and independent correlated Gaussian noise representing the spontaneous EEG activity. The EP is assumed to vary in both shape and latency, with the shape variation represented by correlated Gaussian noise which is modulated by the EP. The latency of the EP is also assumed to vary over the ensemble of responses in a random manner governed by some unspecified probability density. No assumption on stationarity is needed for the noise.
With the model described in state-space form, a Kalman filter is constructed, and the variance of the innovation process of the response measurements is derived. A maximum likelihood solution to the EP estimation problem is then obtained via this innovation process.
Tests using simulated responses show that the method is effective in estimating the EP signal at signal-to-noise ratio as low as -6db. Other tests using real normal visual response data yield reasonably consistent EP estimates whose main components are narrower and larger than the ensemble average. In addition, the likelihood function obtained by our method can be used as a discriminant between normal and abnormal responses, and it requires smaller ensembles than other methods.
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Montpellier, Pierre Robert. "The maximum likelihood method of estimating dynamic properties of structures." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp04/mq21050.pdf.

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Khiabanian, Hossein. "A maximum-likelihood multi-resolution weak lensing mass reconstruction method." View abstract/electronic edition; access limited to Brown University users, 2008. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3318339.

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Donmez, Ayca. "Adaptive Estimation And Hypothesis Testing Methods." Phd thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/3/12611724/index.pdf.

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For statistical estimation of population parameters, Fisher&rsquo
s maximum likelihood estimators (MLEs) are commonly used. They are consistent, unbiased and efficient, at any rate for large n. In most situations, however, MLEs are elusive because of computational difficulties. To alleviate these difficulties, Tiku&rsquo
s modified maximum likelihood estimators (MMLEs) are used. They are explicit functions of sample observations and easy to compute. They are asymptotically equivalent to MLEs and, for small n, are equally efficient. Moreover, MLEs and MMLEs are numerically very close to one another. For calculating MLEs and MMLEs, the functional form of the underlying distribution has to be known. For machine data processing, however, such is not the case. Instead, what is reasonable to assume for machine data processing is that the underlying distribution is a member of a broad class of distributions. Huber assumed that the underlying distribution is long-tailed symmetric and developed the so called M-estimators. It is very desirable for an estimator to be robust and have bounded influence function. M-estimators, however, implicitly censor certain sample observations which most practitioners do not appreciate. Tiku and Surucu suggested a modification to Tiku&rsquo
s MMLEs. The new MMLEs are robust and have bounded influence functions. In fact, these new estimators are overall more efficient than M-estimators for long-tailed symmetric distributions. In this thesis, we have proposed a new modification to MMLEs. The resulting estimators are robust and have bounded influence functions. We have also shown that they can be used not only for long-tailed symmetric distributions but for skew distributions as well. We have used the proposed modification in the context of experimental design and linear regression. We have shown that the resulting estimators and the hypothesis testing procedures based on them are indeed superior to earlier such estimators and tests.
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Li, Ka Lok. "A Strategy for Earthquake Catalog Relocations Using a Maximum Likelihood Method." Thesis, Uppsala universitet, Geofysik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-188826.

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A strategy for relocating earthquakes in a catalog is presented. The strategy is based on the argument that the distribution of the earthquake events in a catalog is reasonable a priori information for earthquake relocation in that region. This argument can be implemented using the method of maximum likelihood for arrival time data inversion, where the a priori probability distribution of the event locations is defined as the sum of the probability densities of all events in the catalog. This a priori distribution is then added to the standard misfit criterion in earthquake location to form the likelihood function. The probability density of an event in the catalog is described by a Gaussian probability density. The a priori probability distribution is, therefore, defined as the normalized sum of the Gaussian probability densities of all events in the catalog, excluding the event being relocated. For a linear problem, the likelihood function can be approximated by the joint probability density of the a priori distribution and the distribution of an unconstrained location due to the misfit alone. After relocating the events according to the maximum of the likelihood function, a modified distribution of events is generated. This distribution should be more densely clustered than before in general since the events are moved towards the maximum of the posterior distribution. The a priori distribution is updated and the process is iterated. The strategy is applied to the aftershock sequence in southwest Iceland after a pair of earthquakes on 29th May 2008. The relocated events reveal the fault systems in that area. Three synthetic data sets are used to test the general behaviour of the strategy. It is observed that the synthetic data give significantly different behaviour from the real data.
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Kraay, Andrea L. (Andrea Lorraine) 1976. "Physically constrained maximum likelihood method for snapshot deficient adaptive array processing." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/87331.

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Thesis (Elec.E. and S.M. in Electrical Engineering)--Joint Program in Applied Ocean Physics and Engineering (Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; and the Woods Hole Oceanographic Institution), 2003.
"February 2003."
Includes bibliographical references (leaves 139-141).
by Andrea L. Kraay.
Elec.E.and S.M.in Electrical Engineering
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Stamatakis, Alexandros. "Distributed and parallel algorithms and systems for inference of huge phylogenetic trees based on the maximum likelihood method." [S.l. : s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=973053380.

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Ishakova, Gulmira. "On the use of Quasi-Maximum Likelihood Estimation and Indirect Method for Stochastic Volatility models." Thesis, Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-1641.

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Stochastic volatility models have been focus for research in recent years.

One interesting and important topic has been the estimation procedure.

For a given stochastic volatility model this project aims to compare two

methods of parameter estimation.

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Li, Xiangfei. "Reliability Assessment for Complex Systems Using Multi-level, Multi-type Reliability Data and Maximum Likelihood Method." Ohio University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1402483535.

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Books on the topic "Maximum likelihood method - MMV"

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Aït-Sahalia, Yacine. Maximum likelihood estimation of stochastic volatility models. Cambridge, MA: National Bureau of Economic Research, 2004.

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Kunitomo, Naoto, Seisho Sato, and Daisuke Kurisu. Separating Information Maximum Likelihood Method for High-Frequency Financial Data. Tokyo: Springer Japan, 2018. http://dx.doi.org/10.1007/978-4-431-55930-6.

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S, Burrus C., ed. Maximum-likelihood deconvolution: A journey into model-based signal processing. New York: Springer-Verlag, 1990.

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Güimil, Fernando. Comparing the Maximum Likelihood Method and a Modified Moment Method to fit a Weibull distribution to aircraft engine failure time data. Monterey, Calif: Naval Postgraduate School, 1997.

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Morelli, Eugene A. Determining the accuracy of aerodynamic model parameters estimated from flight test data. Washington, D.C: American Institute of Aeronautics and Astronautics, 1995.

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Morelli, Eugene A. Determining the accuracy of aerodynamic model parameters estimated from flight test data. Washington, D.C: American Institute of Aeronautics and Astronautics, 1995.

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Morelli, Eugene A. Determining the accuracy of aerodynamic model parameters estimated from flight test data. Washington, D.C: American Institute of Aeronautics and Astronautics, 1995.

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Schwenzfeger, K. J. Comparison of ERS-1 scatterometer Monte Carlo performance simulations using a weighted nonlinear least-squares and a maximum likelihood estimation method. Neubiberg: Hochschule der Bundeswehr München, 1985.

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Kunitomo, Naoto, Seisho Sato, and Daisuke Kurisu. Separating Information Maximum Likelihood Method for High-Frequency Financial Data. Springer, 2018.

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Geological Survey (U.S.), ed. Adjusted maximum likelihood estimation of the moments of lognormal populations from type 1 censored samples. [Denver, Colo.?]: Dept. of the Interior, U.S. Geological Survey, 1988.

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Book chapters on the topic "Maximum likelihood method - MMV"

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Širca, Simon. "Maximum-Likelihood Method." In Graduate Texts in Physics, 203–25. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-31611-6_8.

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Ziegler, Andreas. "Maximum likelihood method." In Generalized Estimating Equations, 29–49. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0499-6_4.

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Zabarankin, Michael, and Stan Uryasev. "Maximum Likelihood Method." In Statistical Decision Problems, 45–52. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8471-4_4.

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Brandt, Siegmund. "The Method of Maximum Likelihood." In Data Analysis, 187–211. New York, NY: Springer New York, 1999. http://dx.doi.org/10.1007/978-1-4612-1446-5_7.

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Brandt, Siegmund. "The Method of Maximum Likelihood." In Data Analysis, 153–73. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-03762-2_7.

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Piterbarg, Leonid I., and Alexander G. Ostrovskii. "The Inverse Problem: Maximum Likelihood Method." In Advection and Diffusion in Random Media, 119–44. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4757-4458-3_6.

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Cawley, Robert, and A. Lewis Licht. "Maximum likelihood method for evaluating correlation dimension." In The Physics of Phase Space Nonlinear Dynamics and Chaos Geometric Quantization, and Wigner Function, 90–103. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/3-540-17894-5_329.

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Yoshioka, Michifumi, and Sigeru Omatu. "Camera Calibration Method Based on Maximum Likelihood Estimation." In Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living, 616–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02481-8_90.

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Wills, Adrian, and Lennart Ljung. "Wiener System Identification Using the Maximum Likelihood Method." In Lecture Notes in Control and Information Sciences, 89–110. London: Springer London, 2010. http://dx.doi.org/10.1007/978-1-84996-513-2_7.

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Chervonenkis, Alexei, Alex Gammerman, and Mark Herbster. "A combined Bayes — maximum likelihood method for regression." In Data Fusion and Perception, 25–49. Vienna: Springer Vienna, 2001. http://dx.doi.org/10.1007/978-3-7091-2580-9_2.

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Conference papers on the topic "Maximum likelihood method - MMV"

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Paris, M. G. A. "Maximum-likelihood method in quantum estimation." In The twentieth international workshop on bayesian inference and maximum entropy methods in science and engineering. AIP, 2001. http://dx.doi.org/10.1063/1.1381908.

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Streit, Roy L., and Tod E. Luginbuhl. "Maximum likelihood method for probabilistic multihypothesis tracking." In SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, edited by Oliver E. Drummond. SPIE, 1994. http://dx.doi.org/10.1117/12.179066.

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Enderlein, Joerg. "Ultrasensitive fluorescence detection and maximum likelihood method." In OE/LASE '94, edited by Robert F. Bonner, Gerald E. Cohn, Thomas M. Laue, and Alexander V. Priezzhev. SPIE, 1994. http://dx.doi.org/10.1117/12.180805.

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Raanes, P. N., G. Evensen, and A. S. Stordal. "Revising the Method of Ensemble Randomized Maximum Likelihood." In Petroleum Geostatistics 2019. European Association of Geoscientists & Engineers, 2019. http://dx.doi.org/10.3997/2214-4609.201902205.

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Escárate, Pedro, Karen Gonzalez, Rodrigo Carvajal, Juan Carlos Agüero, and Maria Coronel. "Vibration model identification using the maximum likelihood method." In Adaptive Optics Systems VI, edited by Dirk Schmidt, Laura Schreiber, and Laird M. Close. SPIE, 2018. http://dx.doi.org/10.1117/12.2314080.

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Lo, Edisanter. "Hyperspectral anomaly detection based on maximum likelihood method." In International Conference on Photonics Solutions 2015, edited by Surasak Chiangga and Sarun Sumriddetchkajorn. SPIE, 2015. http://dx.doi.org/10.1117/12.2196550.

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Ikemoto, Shinya, Tadashi Dohi, and Hiroyuki Okamura. "Estimating software reliability via pseudo maximum likelihood method." In the 27th Annual ACM Symposium. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2245276.2231960.

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Chen, Hongli, Qiang Li, and Ziyuan Wang. "Improved Maximum Likelihood Method for Ship Parameter Identification." In 2018 37th Chinese Control Conference (CCC). IEEE, 2018. http://dx.doi.org/10.23919/chicc.2018.8483871.

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Mugnier, L. M., A. Cornia, J. F. Sauvage, N. Védrenne, T. Fusco, and G. Rousset. "Maximum likelihood-based method for angular differential imaging." In SPIE Astronomical Telescopes + Instrumentation, edited by Norbert Hubin, Claire E. Max, and Peter L. Wizinowich. SPIE, 2008. http://dx.doi.org/10.1117/12.790329.

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WANG, P., B. B. ZHOU, M. TARAENEH, D. CHU, C. WANG, A. Y. ZOMAYA, and R. P. BRENT. "A GLOBAL MAXIMUM LIKELIHOOD SUPER-QUARTET PHYLOGENY METHOD." In 5th Asia-Pacific Bioinformatics Conference. PUBLISHED BY IMPERIAL COLLEGE PRESS AND DISTRIBUTED BY WORLD SCIENTIFIC PUBLISHING CO., 2007. http://dx.doi.org/10.1142/9781860947995_0014.

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Reports on the topic "Maximum likelihood method - MMV"

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Moreira, Marcelo. A Maximum Likelihood Method for the Incidental Parameter Problem. Cambridge, MA: National Bureau of Economic Research, February 2008. http://dx.doi.org/10.3386/w13787.

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Eisenhauer, Phillipp, James Heckman, and Stefano Mosso. Estimation of Dynamic Discrete Choice Models by Maximum Likelihood and the Simulated Method of Moments. Cambridge, MA: National Bureau of Economic Research, October 2014. http://dx.doi.org/10.3386/w20622.

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