Bibliografie tematiche / Targeted Maximum Likelihood Estimation

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Letteratura scientifica selezionata sul tema "Targeted Maximum Likelihood Estimation"

Autore: Grafiati
Pubblicato: 25 gennaio 2025
Ultima modifica: 19 luglio 2025

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Articoli di riviste sul tema "Targeted Maximum Likelihood Estimation"

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Pang, Menglan, Tibor Schuster, Kristian B. Filion, Maria Eberg, and Robert W. Platt. "Targeted Maximum Likelihood Estimation for Pharmacoepidemiologic Research." Epidemiology 27, no. 4 (2016): 570–77. http://dx.doi.org/10.1097/ede.0000000000000487.

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Lendle, Samuel D., Bruce Fireman, and Mark J. van der Laan. "Targeted maximum likelihood estimation in safety analysis." Journal of Clinical Epidemiology 66, no. 8 (2013): S91—S98. http://dx.doi.org/10.1016/j.jclinepi.2013.02.017.

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Zheng, Wenjing, and Mark J. van der Laan. "Targeted Maximum Likelihood Estimation of Natural Direct Effects." International Journal of Biostatistics 8, no. 1 (2012): 1–40. http://dx.doi.org/10.2202/1557-4679.1361.

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Dijkhuis, Talko B., and Frank J. Blaauw. "Transfering Targeted Maximum Likelihood Estimation for Causal Inference into Sports Science." Entropy 24, no. 8 (2022): 1060. http://dx.doi.org/10.3390/e24081060.

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Abstract (sommario):
Although causal inference has shown great value in estimating effect sizes in, for instance, physics, medical studies, and economics, it is rarely used in sports science. Targeted Maximum Likelihood Estimation (TMLE) is a modern method for performing causal inference. TMLE is forgiving in the misspecification of the causal model and improves the estimation of effect sizes using machine-learning methods. We demonstrate the advantage of TMLE in sports science by comparing the calculated effect size with a Generalized Linear Model (GLM). In this study, we introduce TMLE and provide a roadmap for
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Schuler, Megan S., and Sherri Rose. "Targeted Maximum Likelihood Estimation for Causal Inference in Observational Studies." American Journal of Epidemiology 185, no. 1 (2016): 65–73. http://dx.doi.org/10.1093/aje/kww165.

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Luque-Fernandez, Miguel Angel, Michael Schomaker, Bernard Rachet, and Mireille E. Schnitzer. "Targeted maximum likelihood estimation for a binary treatment: A tutorial." Statistics in Medicine 37, no. 16 (2018): 2530–46. http://dx.doi.org/10.1002/sim.7628.

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Cho, Sunyoung, Heejo Koo, Beom Kyung Kim, and Euna Han. "Causal Analyses of Statin to Prevent Liver Disease Progression: A Nationwide Study Using Superlearning Targeted Maximum Likelihood Estimation." Yakhak Hoeji 68, no. 1 (2024): 44–55. http://dx.doi.org/10.17480/psk.2024.68.1.44.

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Many studies have shown that statins reduce the risk of progression to liver cirrhosis (LC) and hepatocellular carcinoma (HCC) among at-risk populations. However, causality has not been proved. This study examined whether statins could prevent LC and HCC in patients with progressive and worsening chronic liver disease, using a robust methodology for causality. Between 2002 and 2013, 52,145 patients with chronic liver diseases were identified from the National Health Insurance Service database in South Korea. The inverse probability weighting (IPW) and superlearning targeted maximum likelihood
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Cai, Weixin, and Mark J. Laan. "One‐step targeted maximum likelihood estimation for time‐to‐event outcomes." Biometrics 76, no. 3 (2019): 722–33. http://dx.doi.org/10.1111/biom.13172.

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Stitelman, Ori M., C. William Wester, Victor De Gruttola, and Mark J. van der Laan. "Targeted Maximum Likelihood Estimation of Effect Modification Parameters in Survival Analysis." International Journal of Biostatistics 7, no. 1 (2011): 1–34. http://dx.doi.org/10.2202/1557-4679.1307.

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Grossman, J., M. Ghadessi, A. Contijoch, et al. "MSR75 Correlate: Assessing Dose Effect Using Targeted Maximum Likelihood Estimation (TMLE)." Value in Health 26, no. 12 (2023): S407. http://dx.doi.org/10.1016/j.jval.2023.09.2134.

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Tesi sul tema "Targeted Maximum Likelihood Estimation"

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Schnitzer, Mireille. "Targeted maximum likelihood estimation for longitudinal data." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=114242.

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Abstract (sommario):
Semiparametric efficient methods in causal inference have been developed to robustly and efficiently estimate causal parameters. As in general causal estimation, the methods rely on a set of mathematical assumptions that translate into requirements of causal knowledge and confounder identification. Targeted maximum likelihood estimation (TMLE) methodology has been developed as a potential improvement on efficient estimating equations, in that it shares the qualities of double robustness (unbiasedness under partial misspecification) and semiparametric efficiency, but can be constructed to provi
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Sarovar, Varada. "Targeted Maximum Likelihood Estimation for Evaluation of the Health Impacts of Air Pollution." Thesis, University of California, Berkeley, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10279902.

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<p> The adverse effects of air pollution on human life is of serious concern for today&rsquo;s society. Two population groups that are especially vulnerable to air pollution are pregnant women and their growing fetuses, and the focus of this thesis is to study the effects of air pollution on these populations. In order to address the methodological limitations in prior research, we quantify the impact of air pollution on various adverse pregnancy outcomes, utilizing machine learning and novel causal inference methods. Specifically, we utilize two semi-parametric, double robust, asymptotically
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Khanafer, Sajida. "Sensory Integration During Goal Directed Reaches: The Effects of Manipulating Target Availability." Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/23422.

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When using visual and proprioceptive information to plan a reach, it has been proposed that the brain combines these cues to estimate the object and/or limb’s location. Specifically, according to the maximum-likelihood estimation (MLE) model, more reliable sensory inputs are assigned a greater weight (Ernst & Banks, 2002). In this research we examined if the brain is able to adjust which sensory cue it weights the most. Specifically, we asked if the brain changes how it weights sensory information when the availability of a visual cue is manipulated. Twenty-four healthy subjects reached to v
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Ruprecht, Jürg. "Maximum likelihood estimation of multipath channels /." [S.l.] : [s.n.], 1989. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=8789.

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Horbelt, Werner. "Maximum likelihood estimation in dynamical systems." [S.l. : s.n.], 2001. http://deposit.ddb.de/cgi-bin/dokserv?idn=963810812.

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Sabbagh, Yvonne. "Maximum Likelihood Estimation of Hammerstein Models." Thesis, Linköping University, Department of Electrical Engineering, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2061.

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<p>In this Master's thesis, Maximum Likelihood-based parametric identification methods for discrete-time SISO Hammerstein models from perturbed observations on both input and output, are investigated. </p><p>Hammerstein models, consisting of a static nonlinear block followed by a dynamic linear one, are widely applied to modeling nonlinear dynamic systems, i.e., dynamic systems having nonlinearity at its input. </p><p>Two identification methods are proposed. The first one assumes a Hammerstein model where the input signal is noise-free and the output signal is perturbed with colored noise. The
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Leeuw, Johannes Leonardus van der. "Maximum likelihood estimation of exact ARMA models /." Tilburg : Tilburg University Press, 1997. http://www.gbv.de/dms/goettingen/265169976.pdf.

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Ehlers, Rene. "Maximum likelihood estimation procedures for categorical data." Pretoria : [s.n.], 2002. http://upetd.up.ac.za/thesis/available/etd-07222005-124541.

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Zou, Yiqun. "Attainment of Global Convergence in Maximum Likelihood Estimation." Thesis, University of Manchester, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.511845.

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Mariano, Machado Robson José. "Penalised maximum likelihood estimation for multi-state models." Thesis, University College London (University of London), 2018. http://discovery.ucl.ac.uk/10060352/.

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Abstract (sommario):
Multi-state models can be used to analyse processes where change of status over time is of interest. In medical research, processes are commonly defined by a set of living states and a dead state. Transition times between living states are often interval censored. In this case, models are usually formulated in a Markov processes framework. The likelihood function is then constructed using transition probabilities. Models are specified using proportional hazards for the effect of covariates on transition intensities. Time-dependency is usually defined by parametric models, which can represent a
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Libri sul tema "Targeted Maximum Likelihood Estimation"

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Eliason, Scott. Maximum Likelihood Estimation. SAGE Publications, Inc., 1993. http://dx.doi.org/10.4135/9781412984928.

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Eggermont, P. P. B., and V. N. LaRiccia. Maximum Penalized Likelihood Estimation. Springer New York, 2001. http://dx.doi.org/10.1007/978-1-0716-1244-6.

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LaRiccia, Vincent N., and Paul P. Eggermont. Maximum Penalized Likelihood Estimation. Springer New York, 2009. http://dx.doi.org/10.1007/b12285.

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N, LaRiccia V., ed. Maximum penalized likelihood estimation. Springer, 2001.

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Millar, Russell B. Maximum Likelihood Estimation and Inference. John Wiley & Sons, Ltd, 2011. http://dx.doi.org/10.1002/9780470094846.

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Jeffrey, Pitblado, Sribney William, and Stata Corporation, eds. Maximum likelihood estimation with stata. 3rd ed. Stata Press, 2006.

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S, Pitblado Jeffrey, and Poi Brian, eds. Maximum likelihood estimation with Stata. 4th ed. Stata Press, 2010.

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Nagelkerke, Nico J. D. Maximum Likelihood Estimation of Functional Relationships. Springer New York, 1992. http://dx.doi.org/10.1007/978-1-4612-2858-5.

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Nagelkerke, Nico J. D. Maximum likelihood estimation of functional relationships. Springer-Verlag, 1992.

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10

Ruprecht, Jürg. Maximum-likelihood estimation of multipath channel. Hartung-Gorre, 1989.

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Capitoli di libri sul tema "Targeted Maximum Likelihood Estimation"

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Gruber, Susan, and Mark van der Laan. "Collaborative Targeted Maximum Likelihood Estimation to Assess Causal Effects in Observational Studies." In Biopharmaceutical Applied Statistics Symposium. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7826-2_1.

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Baig, Nauman Anwar, Muhammad Anwar Baig, Thawban Anwar Baig, Adnan Anwar Baig, and Abdullah Anwar Baig. "Estimation of Phase, Range, Doppler of Targets Using Maximum Likelihood Estimator." In Proceedings of the Future Technologies Conference (FTC) 2018. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02683-7_34.

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Heidenreich, Philipp, and Abdelhak M. Zoubir. "Computational Aspects of Maximum Likelihood DOA Estimation of Two Targets with Applications to Automotive Radar." In Smart Mobile In-Vehicle Systems. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-9120-0_1.

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Kelley Pace, R. "Maximum Likelihood Estimation." In Handbook of Regional Science. Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-642-36203-3_88-1.

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Lee, Myoung-jae. "Maximum Likelihood Estimation." In Methods of Moments and Semiparametric Econometrics for Limited Dependent Variable Models. Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4757-2550-6_4.

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Nguyen, Hung T., and Gerald S. Rogers. "Maximum Likelihood Estimation." In Springer Texts in Statistics. Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4613-8914-9_20.

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Pan, Jian-Xin, and Kai-Tai Fang. "Maximum Likelihood Estimation." In Growth Curve Models and Statistical Diagnostics. Springer New York, 2002. http://dx.doi.org/10.1007/978-0-387-21812-0_3.

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Brown, Jonathon D. "Maximum-Likelihood Estimation." In Linear Models in Matrix Form. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11734-8_3.

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Krolzig, Hans-Martin. "Maximum Likelihood Estimation." In Lecture Notes in Economics and Mathematical Systems. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-51684-9_7.

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Haynes, Winston. "Maximum Likelihood Estimation." In Encyclopedia of Systems Biology. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_1235.

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Atti di convegni sul tema "Targeted Maximum Likelihood Estimation"

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Zheng, Hao, Yong Cheng, and Yang Liu. "Maximum Expected Likelihood Estimation for Zero-resource Neural Machine Translation." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/594.

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Abstract (sommario):
While neural machine translation (NMT) has made remarkable progress in translating a handful of high-resource language pairs recently, parallel corpora are not always available for many zero-resource language pairs. To deal with this problem, we propose an approach to zero-resource NMT via maximum expected likelihood estimation. The basic idea is to maximize the expectation with respect to a pivot-to-source translation model for the intended source-to-target model on a pivot-target parallel corpus. To approximate the expectation, we propose two methods to connect the pivot-to-source and source
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Moghari, Mehdi Hedjazi, and Purang Abolmaesumi. "Maximum likelihood estimation of the distribution of target registration error." In Medical Imaging, edited by Michael I. Miga and Kevin R. Cleary. SPIE, 2008. http://dx.doi.org/10.1117/12.768868.

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Zhang, Mengdi, Hongyi Lu, Shiyin Li, and Zhiwei Li. "Maneuvering target imaging and motion parameter estimation based on improved maximum likelihood estimation." In IET International Radar Conference (IRC 2023). Institution of Engineering and Technology, 2023. http://dx.doi.org/10.1049/icp.2024.1674.

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Schatzberg, Alon, Anthony J. Devaney, and Ross Deming. "Maximum likelihood estimation of target location in acoustic and electromagnetic imaging." In SEG Technical Program Expanded Abstracts 1995. Society of Exploration Geophysicists, 1995. http://dx.doi.org/10.1190/1.1887557.

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Ramsay, Gordon, and Li Deng. "Maximum-likelihood estimation for articulatory speech recognition using a stochastic target model." In 4th European Conference on Speech Communication and Technology (Eurospeech 1995). ISCA, 1995. http://dx.doi.org/10.21437/eurospeech.1995-225.

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Baum, Marcus, and Peter Willett. "A hybrid data association model for efficient multi-target maximum likelihood estimation." In ICASSP 2014 - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2014. http://dx.doi.org/10.1109/icassp.2014.6854395.

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Dianat, Mojtaba, Mohammad Reza Taban, and Ali Akbar Tadaion. "A new approach for target localization using Maximum Likelihood Estimation in MIMO radar." In 2011 24th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE). IEEE, 2011. http://dx.doi.org/10.1109/ccece.2011.6030554.

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Lu, Chengye, Jinzhou Li, Miao Wang, and Jinfeng Hu. "Parameter Estimation for Maneuvering Target in OTHR Relying on Improved Maximum-Likelihood Algorithm." In 2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS). IEEE, 2019. http://dx.doi.org/10.1109/iucc/dsci/smartcns.2019.00143.

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Vikalo, H., B. Hassibi, and A. Hassibi. "On joint maximum-likelihood estimation of PCR efficiency and initial amount of target." In 2006 IEEE International Workshop on Genomic Signal Processing and Statistics. IEEE, 2006. http://dx.doi.org/10.1109/gensips.2006.353149.

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Hou, Wang, Gucan Long, Zhihui Lei, and Jing Dong. "The small target detection based on maximum likelihood estimation and spot detection operator." In Selected Proceedings of the Photoelectronic Technology Committee Conferences held July-December 2013, edited by Jorge Ojeda-Castaneda, Shensheng Han, Ping Jia, et al. SPIE, 2014. http://dx.doi.org/10.1117/12.2054032.

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Rapporti di organizzazioni sul tema "Targeted Maximum Likelihood Estimation"

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Ljung, Lennart, Sanjoy K. Mitter, and Jose M. Moura. Optimal Recursive Maximum Likelihood Estimation,. Defense Technical Information Center, 1987. http://dx.doi.org/10.21236/ada187980.

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Adams, Terry. Maximum Likelihood Estimation: Some Basics. Office of Scientific and Technical Information (OSTI), 2025. https://doi.org/10.2172/2496644.

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Ait-Sahalia, Yacine, and Robert Kimmel. Maximum Likelihood Estimation of Stochastic Volatility Models. National Bureau of Economic Research, 2004. http://dx.doi.org/10.3386/w10579.

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Bates, David. Maximum Likelihood Estimation of Latent Affine Processes. National Bureau of Economic Research, 2003. http://dx.doi.org/10.3386/w9673.

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Avdis, Efstathios, and Jessica Wachter. Maximum likelihood estimation of the equity premium. National Bureau of Economic Research, 2013. http://dx.doi.org/10.3386/w19684.

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Ainsleigh, P. L., J. D. George, and V. K. Jain. Maximum Likelihood Parameter Estimation for Acoustic Transducer Calibration. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada204923.

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Moore, Terrence, and Brian Sadler. Maximum-Likelihood Estimation and Scoring Under Parametric Constraints. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada448612.

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Diebold, Francis, and Til Schuermann. Exact Maximum Likelihood Estimation of Observation-Driven Econometric Models. National Bureau of Economic Research, 1996. http://dx.doi.org/10.3386/t0194.

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Hall, Jr, Lehnigk Charles E., Viswanath Siegfried H., and Guttalu R. Maximum-Likelihood Parameter Estimation of a Generalized Gumbel Distribution. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada207994.

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Lake, Douglas. Efficient Maximum Likelihood Estimation for Multiple and Coupled Harmonics. Defense Technical Information Center, 1999. http://dx.doi.org/10.21236/ada372834.

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