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Relevant bibliographies by topics / Moments method (Statistics)

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Academic literature on the topic 'Moments method (Statistics)'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 August 2024

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Journal articles on the topic "Moments method (Statistics)"

1

Headrick, Todd C. "A Characterization of Power Method Transformations throughL-Moments." Journal of Probability and Statistics 2011 (2011): 1–22. http://dx.doi.org/10.1155/2011/497463.

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Power method polynomial transformations are commonly used for simulating continuous nonnormal distributions with specified moments. However, conventional moment-based estimators can (a) be substantially biased, (b) have high variance, or (c) be influenced by outliers. In view of these concerns, a characterization of power method transformations byL-moments is introduced. Specifically, systems of equations are derived for determining coefficients for specifiedL-moment ratios, which are associated with standard normal and standard logistic-based polynomials of order five and three. Boundaries forL-moment ratios are also derived, and closed-formed formulae are provided for determining if a power method distribution has a valid probability density function. It is demonstrated thatL-moment estimators are nearly unbiased and have relatively small variance in the context of the power method. Examples of fitting power method distributions to theoretical and empirical distributions based on the method ofL-moments are also provided.

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Dell'Aquila, Rosario. "Generalized Method of Moments." Journal of the American Statistical Association 101, no. 475 (September 2006): 1309–10. http://dx.doi.org/10.1198/jasa.2006.s120.

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Orlov, A. I. "Interval statistics: Maximum likelihood method and method of moments." Journal of Mathematical Sciences 88, no. 6 (March 1998): 833–39. http://dx.doi.org/10.1007/bf02365369.

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Hyde, Milo W. "Independently Controlling Stochastic Field Realization Magnitude and Phase Statistics for the Construction of Novel Partially Coherent Sources." Photonics 8, no. 2 (February 22, 2021): 60. http://dx.doi.org/10.3390/photonics8020060.

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In this paper, we present a method to independently control the field and irradiance statistics of a partially coherent beam. Prior techniques focus on generating optical field realizations whose ensemble-averaged autocorrelation matches a specified second-order field moment known as the cross-spectral density (CSD) function. Since optical field realizations are assumed to obey Gaussian statistics, these methods do not consider the irradiance moments, as they, by the Gaussian moment theorem, are completely determined by the field’s first and second moments. Our work, by including control over the irradiance statistics (in addition to the CSD function), expands existing synthesis approaches and allows for the design, modeling, and simulation of new partially coherent beams, whose underlying field realizations are not Gaussian distributed. We start with our model for a random optical field realization and then derive expressions relating the ensemble moments of our fields to those of the desired partially coherent beam. We describe in detail how to generate random optical field realizations with the proper statistics. We lastly generate two example partially coherent beams using our method and compare the simulated field and irradiance moments theory to validate our technique.

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Kuersteiner, Guido M., and Laszlo Matyas. "Generalized Method of Moments Estimation." Journal of the American Statistical Association 95, no. 451 (September 2000): 1014. http://dx.doi.org/10.2307/2669498.

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Kormann, U., R. Theodorescu, and H. Wolff. "A dynamic method of moments." Statistics 18, no. 1 (January 1987): 131–40. http://dx.doi.org/10.1080/02331888708802002.

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Morrison, Hugh, Matthew R. Kumjian, Charlotte P. Martinkus, Olivier P. Prat, and Marcus van Lier-Walqui. "A General N-Moment Normalization Method for Deriving Raindrop Size Distribution Scaling Relationships." Journal of Applied Meteorology and Climatology 58, no. 2 (February 2019): 247–67. http://dx.doi.org/10.1175/jamc-d-18-0060.1.

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AbstractA general drop size distribution (DSD) normalization method is formulated in terms of generalized power series relating any DSD moment to any number and combination of reference moments. This provides a consistent framework for comparing the variability of normalized DSD moments using different sets of reference moments, with no explicit assumptions about the DSD functional form (e.g., gamma). It also provides a method to derive any unknown moment plus an estimate of its uncertainty from one or more known moments, which is relevant to remote sensing retrievals and bulk microphysics schemes in weather and climate models. The approach is applied to a large dataset of disdrometer-observed and bin microphysics-modeled DSDs. As expected, the spread of normalized moments decreases as the number of reference moments is increased, quantified by the logarithmic standard deviation of the normalized moments, σ. Averaging σ for all combinations of reference moments and normalized moments of integer order 0–10, 42.9%, 81.3%, 93.7%, and 96.9% of spread are accounted for applying one-, two-, three-, and four-moment normalizations, respectively. Thus, DSDs can be well characterized overall using three reference moments, whereas adding a fourth reference moment contributes little independent information. The spread of disdrometer-observed DSD moments from uncertainty associated with drop count statistics generally lies between values of σ using two- and three-moment normalizations. However, this uncertainty has little impact on the derived DSD scaling relationships or σ when considered.

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Bisgaard, Torben Maack. "Method of moments on semigroups." Journal of Theoretical Probability 9, no. 3 (July 1996): 631–45. http://dx.doi.org/10.1007/bf02214079.

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Yin, Guosheng, Yanyuan Ma, Faming Liang, and Ying Yuan. "Stochastic Generalized Method of Moments." Journal of Computational and Graphical Statistics 20, no. 3 (January 2011): 714–27. http://dx.doi.org/10.1198/jcgs.2011.09210.

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Amani Zakaria, Zahrahtul, Jarah Moath Ali Suleiman, and Mumtazimah Mohamad. "Rainfall frequency analysis using LH-moments approach: A case of Kemaman Station, Malaysia." International Journal of Engineering & Technology 7, no. 2.15 (April 6, 2018): 107. http://dx.doi.org/10.14419/ijet.v7i2.15.11363.

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Statistical analysis of extreme events is often carried out to obtain the probability distribution of floods data and then predict the occurrence of floods for a significant return period. L-moments approach is known as the most popular approach in frequency analysis. This paper discusses comparison of the L-moments method with higher order moments (LH-moments) method. LH-moment, a generalization of L-moment, which is proposed based on the linear combinations of higher-order statistics has been used to characterize the upper part of distributions and larger events in flood data. It is observed from a comparative study that the results of the analysis of observed data and the diagram based on the K3D-II distribution using LH-moments method is more efficient and reasonable than the L-moments method for estimating data of the upper part of the distribution events.

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Dissertations / Theses on the topic "Moments method (Statistics)"

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Lai, Yanzhao. "Generalized method of moments exponential distribution family." View electronic thesis (PDF), 2009. http://dl.uncw.edu/etd/2009-2/laiy/yanzhaolai.pdf.

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Liu, Jianguo, and 劉建國. "Fast computation of moments with applications to transforms." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1996. http://hub.hku.hk/bib/B31235086.

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Liu, Jianguo. "Fast computation of moments with applications to transforms /." Hong Kong : University of Hong Kong, 1996. http://sunzi.lib.hku.hk/hkuto/record.jsp?B17664986.

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Virk, Bikram. "Implementing method of moments on a GPGPU using Nvidia CUDA." Thesis, Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/33980.

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This thesis concentrates on the algorithmic aspects of Method of Moments (MoM) and Locally Corrected Nyström (LCN) numerical methods in electromagnetics. The data dependency in each step of the algorithm is analyzed to implement a parallel version that can harness the powerful processing power of a General Purpose Graphics Processing Unit (GPGPU). The GPGPU programming model provided by NVIDIA's Compute Unified Device Architecture (CUDA) is described to learn the software tools at hand enabling us to implement C code on the GPGPU. Various optimizations such as the partial update at every iteration, inter-block synchronization and using shared memory enable us to achieve an overall speedup of approximately 10. The study also brings out the strengths and weaknesses in implementing different methods such as Crout's LU decomposition and triangular matrix inversion on a GPGPU architecture. The results suggest future directions of study in different algorithms and their effectiveness on a parallel processor environment. The performance data collected show how different features of the GPGPU architecture can be enhanced to yield higher speedup.

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Chen, Houfei. "Fast electromagnetic simulation for interconnects on high speed circuits /." Thesis, Connect to this title online; UW restricted, 2002. http://hdl.handle.net/1773/5940.

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Ragusa, Giuseppe. "Essays on moment conditions models econometrics /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2005. http://wwwlib.umi.com/cr/ucsd/fullcit?p3170252.

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Killian, Tyler Norton Rao S. M. "Fast solution of large-body problems using domain decomposition and null-field generation in the method of moments." Auburn, Ala, 2009. http://hdl.handle.net/10415/1881.

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Pant, Mohan Dev. "Simulating Univariate and Multivariate Burr Type III and Type XII Distributions Through the Method of L-Moments." OpenSIUC, 2011. https://opensiuc.lib.siu.edu/dissertations/401.

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The Burr families (Type III and Type XII) of distributions are traditionally used in the context of statistical modeling and for simulating non-normal distributions with moment-based parameters (e.g., Skew and Kurtosis). In educational and psychological studies, the Burr families of distributions can be used to simulate extremely asymmetrical and heavy-tailed non-normal distributions. Conventional moment-based estimators (i.e., the mean, variance, skew, and kurtosis) are traditionally used to characterize the distribution of a random variable or in the context of fitting data. However, conventional moment-based estimators can (a) be substantially biased, (b) have high variance, or (c) be influenced by outliers. In view of these concerns, a characterization of the Burr Type III and Type XII distributions through the method of L-moments is introduced. Specifically, systems of equations are derived for determining the shape parameters associated with user specified L-moment ratios (e.g., L-Skew and L-Kurtosis). A procedure is also developed for the purpose of generating non-normal Burr Type III and Type XII distributions with arbitrary L-correlation matrices. Numerical examples are provided to demonstrate that L-moment based Burr distributions are superior to their conventional moment based counterparts in the context of estimation, distribution fitting, and robustness to outliers. Monte Carlo simulation results are provided to demonstrate that L-moment-based estimators are nearly unbiased, have relatively small variance, and are robust in the presence of outliers for any sample size. Simulation results are also provided to show that the methodology used for generating correlated non-normal Burr Type III and Type XII distributions is valid and efficient. Specifically, Monte Carlo simulation results are provided to show that the empirical values of L-correlations among simulated Burr Type III (and Type XII) distributions are in close agreement with the specified L-correlation matrices.

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Lemdiasov, Rostislav A. "A general purpose computational approach to the design of gradient coils for arbitrary geometries." Worcester, Mass. : Worcester Polytechnic Institute, 2004. http://www.wpi.edu/Pubs/ETD/Available/etd-09214-155502/.

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Imeci, Sehabeddin Taha. "Transmission through an arbitrarily shaped aperture in a conducting plane separating air and a chiral medium." Related electronic resource: Current Research at SU : database of SU dissertations, recent titles available, full text:, 2007. http://wwwlib.umi.com/cr/syr/main.

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Books on the topic "Moments method (Statistics)"

1

Center, Langley Research, ed. Moment method analysis of linearly tapered slot antennas. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1993.

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J, Trew Robert, Kauffman J. Frank, and United States. National Aeronautics and Space Administration., eds. Moment method analysis of linearly tapered slot antennas: Low loss components for switched beam radiometers : final report. Raleigh, NC: Dept. of Electrical and Computer Engineering, North Carolina State University, 1992.

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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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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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1935-, Miller E. K., Medgyesi-Mitschang Louis 1940-, and Newman Edward H. 1946-, eds. Computational electromagnetics: Frequency-domain method of moments. New York: IEEE Press, 1992.

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Gibson, Walton C. The method of moments in electromagnetics. Boca Raton: Chapman & Hall/CRC, 2008.

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1946-, Newman Edward H., and Langley Research Center, eds. Moment method analysis of microstrip antennas over a wide frequency range. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1986.

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8

Lee, Myoung-jae. Methods of moments and semiparametric econometrics for limited dependent and variable models. New York: Springer, 1996.

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Hanson, Bradley A. Method of moments estimates for the four-parameter beta compound binomial model and the calculation of classification consistency indexes. Iowa City, Iowa: American College Testing Program, 1991.

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C, Hansen Robert, ed. Moment methods in antennas and scattering. Boston: Artech House, 1990.

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Book chapters on the topic "Moments method (Statistics)"

1

Wilson, Jeffrey R., and Kent A. Lorenz. "Generalized Method of Moments Logistic Regression Model." In ICSA Book Series in Statistics, 131–46. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23805-0_7.

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Bakar, Mohd Aftar Abu, Noratiqah Mohd Ariff, and Mohd Shahrul Mohd Nadzir. "Comparative Analysis Between L-Moments and Maximum Product Spacing Method for Extreme PM10 Concentration." In Proceedings of the International Conference on Mathematical Sciences and Statistics 2022 (ICMSS 2022), 214–27. Dordrecht: Atlantis Press International BV, 2022. http://dx.doi.org/10.2991/978-94-6463-014-5_21.

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Kursell, Julia. "Carl Stumpf and Control Groups." In Archimedes, 125–48. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-52954-2_5.

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AbstractIn the secondary literature, the notion of control group has so far been traced to two important moments in history of the life sciences: thinking in populations and applying statistics to these. This chapter proposes an additional lineage in the reduction of variation among the members of two paired groups in philosopher Carl Stumpf’s experimental psychology. His method of comparing the conditions of judgment in these groups is traced to three stages, the earliest being his research with individuals that do or do not have musical ability, followed by the stage of being confronted with non-European music, to the final stage of reaching a fully controlled and technically supported setting in which individuals are put in the position to judge either with or without previous knowledge about chosen sounds under scrutiny. The chapter uses Stumpf’s own notion of “practical epistemology” to align his experimental practice with his parallel elaborations of Brentanian logic.

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Hazelton, Martin L. "Methods of Moments Estimation." In International Encyclopedia of Statistical Science, 816–17. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-04898-2_364.

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Terdik, György. "T-Moments and T-Cumulants." In Multivariate Statistical Methods, 107–81. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81392-5_3.

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Galambos, Janos. "Moments, Binomial Moments and Combinatorics." In Advances in Combinatorial Methods and Applications to Probability and Statistics, 275–84. Boston, MA: Birkhäuser Boston, 1997. http://dx.doi.org/10.1007/978-1-4612-4140-9_16.

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de Ridder, Joris, Geert Molenberghs, and Conny Aerts. "Statistical Revision of the Moment Method." In Asteroseismology Across the HR Diagram, 125–28. Dordrecht: Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-017-0799-2_17.

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Terdik, György. "Gaussian Systems, T-Hermite Polynomials, Moments, and Cumulants." In Multivariate Statistical Methods, 183–239. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81392-5_4.

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Eu, Byung Chan. "The Chapman-Enskog and Moment Methods." In Nonequilibrium Statistical Mechanics, 96–122. Dordrecht: Springer Netherlands, 1998. http://dx.doi.org/10.1007/978-94-017-2438-8_6.

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Rachev, Svetlozar T., Lev B. Klebanov, Stoyan V. Stoyanov, and Frank J. Fabozzi. "Moment Distances." In The Methods of Distances in the Theory of Probability and Statistics, 237–70. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-4869-3_10.

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Conference papers on the topic "Moments method (Statistics)"

1

do Nascimento, Leonardo Sant’Anna, Luis Volnei Sudati Sagrilo, and Gilberto Bruno Ellwanger. "Conventional and Linear Statistical Moments Applied in Extreme Value Analysis of Non-Gaussian Response of Jack-Ups." In ASME 2012 31st International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/omae2012-83583.

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This work investigates numerically two different methods of moments applied to Hermite derived probability distribution model and variations of Weibull distribution fitted to the short-term time series peaks sample of stochastic response parameters of a simplified jack-up platform model which represents a source of high non-Gaussian responses. The main focus of the work is to compare the results of short-term extreme response statistics obtained by the so-called linear method of moments (L-moments) and the conventional method of moments using either Hermite or Weibull models as the peaks distribution model. A simplified mass-spring system representing a three-legged jack-up platform is initially employed in order to observe directly impacts of the linear method of moments (L-moments) in extreme analysis results. Afterwards, the stochastic response of the three-legged jack-up platform is analyzed by means of 3-D finite element model. Bias and statistical uncertainty in the estimated extreme statistics parameters are computed considering as the “theoretical” estimates those evaluated by fitting a Gumbel to a sample of episodical extreme values obtained from distinct short-term realizations (or simulations). Results show that the variability of the extreme results, as a function of the simulation length, determined by the linear method of moments (L-moments) is smaller than their corresponding ones derived from the conventional method of moments and the biases are more or less the same.

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Tao, Zhao, Xiao-Yang Li, and Wen-Bin Chen. "An Uncertain Statistics of Uncertain Accelerated Degradation Model Based on the Method of Moments." In 2021 3rd International Conference on System Reliability and Safety Engineering (SRSE). IEEE, 2021. http://dx.doi.org/10.1109/srse54209.2021.00040.

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Anwar, Rohimatul, Anik Djuraidah, and Aji Hamim Wigena. "Comparison of Maximum Likelihood and Generalized Method of Moments in Spatial Autoregressive Model with Heteroskedasticity." In Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia. EAI, 2020. http://dx.doi.org/10.4108/eai.2-8-2019.2290489.

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Ispasoiu, Radu Gh, Constantin P. Cristescu, and Valentin M. Feru. "Sub-Poissonian photon statistics in second-harmonic generation." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1992. http://dx.doi.org/10.1364/oam.1992.thw14.

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The quantum statistical equations for the field produced in the process of second-harmonic generation (SHG) are expressed, based on a method proposed for four-wave mixing.1 We start from the following assumptions: 1) the field absorption in the nonlinear medium may be neglected; 2) the amplitude of the fundamental field is much greater than that of the SH field; 3) the Wigner function associated with the density operator of the field depends significantly only on the variables of the SH field. The coefficients of the Fokker–Planck equation thus obtained depend on the Laplace transforms of the correlation functions of the atomic polarization operator. The moments of the Wigner function2 are related to the moments of the SH field photon number; consequently, we impose the condition for sub-Poissonian photon-statistics and derive the corresponding relationships satisfied by the atomic correlation functions. A numerical interpretation is given.

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Morozov, A. L., R. R. Nigmatullin, G. Agrusti, P. Lino, G. Maione, Z. Kanovic, and J. Martinez-Roman. "Microcontroller Realization of an Induction Motors Fault Detection Method based on FFT and Statistics of Fractional Moments." In 2021 29th Mediterranean Conference on Control and Automation (MED). IEEE, 2021. http://dx.doi.org/10.1109/med51440.2021.9480322.

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Morozov, Arsenii L., Raoul R. Nigmatullin, Paolo Lino, Guido Maione, and Silvio Stasi. "An Improved Nonparametric Method for Fault Detection of Induction Motors Based on the Statistics of the Fractional Moments." In 2018 IEEE Conference on Control Technology and Applications (CCTA). IEEE, 2018. http://dx.doi.org/10.1109/ccta.2018.8511461.

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Houtani, Hidetaka, Sadaoki Matsui, and Wataru Fujimoto. "Numerical Investigation of the Statistics of Vertical Bending Moments of Ships in Nonlinearly Evolving Irregular Waves." In ASME 2023 42nd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/omae2023-104733.

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Abstract This study investigated ship response statistics in waves evolving due to nonlinear quasi-resonant interactions. For that purpose, a nonlinear strip method, NMRIW-II (nonlinear motion in regular and irregular waves), has been extended such that nonlinear wave fields precomputed by the higher-order spectral method (HOSM) can be input. In the numerical simulation, the significant wave height and nonlinear order of the input irregular waves were varied to investigate the impact of wave nonlinearity on ship responses. Furthermore, a container ship and a wall-sided ship were used in numerical simulations to separate the nonlinearity influences attributed to the hull geometry and wave. The lengths, breadths, drafts, and water plane geometries were the same between these ships. The numerical results revealed that the body (hull-geometry) nonlinearity enhances the tail of the sagging moment peak probability distributions. Furthermore, an increase in large wave occurrence due to nonlinear quasi-resonant interaction was revealed to further enhances the tail of the sagging moment peak probability distributions.

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Wunsch, Dirk, Roel Belt, Pascal Fede, and Olivier Simonin. "DNS/DPS of Inertial Droplet Coalescence in Homogeneous Isotropic Turbulence and Comparison With PDF Model Predictions Using the Direct Quadrature Method of Moments." In ASME 2009 Fluids Engineering Division Summer Meeting. ASMEDC, 2009. http://dx.doi.org/10.1115/fedsm2009-78091.

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To analyze in detail the coalescence mechanisms and validate modeling approaches, deterministic Lagrangian simulations of droplet trajectories (DPS) coupled with Direct Numerical Simulations (DNS) of a Homogeneous Isotropic Turbulence (HIT) are performed. The influence of the colliding particle velocity correlations induced by the fluid turbulence on the rate of droplet coalescence is investigated for different particle inertia. The results are compared to predictions using the Direct Quadrature Method of Moments (DQMOM) accounting for coalescence. The particle diameter distribution is written as a summation of Dirac functions. This allows to derive Eulerian transport equations for the dispersed phase statistics, which account for coalescence and conserve the low-order moments of the particle size distribution. The collision terms are modeled applying the molecular chaos assumption in order to account for coalescence. Particle size distributions and moments obtained from DQMOM are compared to those of the DNS/DPS simulations in function of particle inertia.

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Belt, Roel, and Olivier Simonin. "Quadrature Method of Moments for the PDF Modeling of Droplet Coalescence in Turbulent Two-Phase Flows." In ASME 2009 Fluids Engineering Division Summer Meeting. ASMEDC, 2009. http://dx.doi.org/10.1115/fedsm2009-78095.

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In this work, Eulerian transport equations are derived for a polydispersed cloud of droplets in a turbulent carrier flow, which take into account the effects of polydispersion and coalescence. The approach is an extension of the Direct Quadrature Method Of Moments (DQMOM) formalism initially proposed by Marchisio and Fox (2005, J. Aerosol Sci., 36, pp. 43–95). In the initial DQMOM approach of Marchisio and Fox, the effects of polydispersion and coalescence can only be accounted for in the mass balance equations. By combining the DQMOM approach and the joint fluid-particle pdf approach of Simonin (1996, Von Karman Lecture Notes), Eulerian transport equations can be written in the frame of the DQMOM formalism for the velocity, agitation and fluid-particle covariance, which quantities are required to predict the behavior of a cloud of droplets in a turbulent flow. It is formally shown that the Eulerian transport equations in the DQMOM framework are the same equations as those in the multi-class Eulerian approach, except that now there is a collision term in the equations. The collision term due to coalescence can be easily expressed due to the assumptions made in the DQMOM framework, and it is shown that it couples the transport equations of the different classes and dispersed phase statistics, according to the change of number, mass and momentum during coalescence.

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Sclavounos, Paul D., Yu Zhang, Yu Ma, and David F. Larson. "Offshore Wind Turbine Nonlinear Wave Loads and Their Statistics." In ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/omae2017-61184.

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The development is presented of an analytical model for the prediction of the stochastic nonlinear wave loads on the support structure of bottom mounted and floating offshore wind turbines. Explicit expressions are derived for the time-domain nonlinear exciting forces in a seastate with significant wave height comparable to the diameter of the support structure based on the fluid impulse theory. The method is validated against experimental measurements with good agreement. The higher order moments of the nonlinear load are evaluated from simulated force records and the derivation of analytical expressions for the nonlinear load statistics for their efficient use in design is addressed. The identification of the inertia and drag coefficients of a generalized nonlinear wave load model trained against experiments using Support Vector Machine learning algorithms is discussed.

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