Relevant bibliographies by topics / Generalized least square (GLS)

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Generalized least square (GLS)'

Author: Grafiati
Published: 4 June 2021
Last updated: 19 February 2022

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Journal articles on the topic "Generalized least square (GLS)"

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R, Aditya Setyawan, Mustika Hadijati, and Ni Wayan Switrayni. "Analisis Masalah Heteroskedastisitas Menggunakan Generalized Least Square dalam Analisis Regresi." EIGEN MATHEMATICS JOURNAL 1, no. 2 (2019): 61. http://dx.doi.org/10.29303/emj.v1i2.43.

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Regression analysis is one statistical method that allows users to analyze the influence of one or more independent variables (X) on a dependent variable (Y).The most commonly used method for estimating linear regression parameters is Ordinary Least Square (OLS). But in reality, there is often a problem with heteroscedasticity, namely the variance of the error is not constant or variable for all values of the independent variable X. This results in the OLS method being less effective. To overcome this, a parameter estimation method can be used by adding weight to each parameter, namely the Gen
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Rashid, Intan Maizura Abd. "Determinants of FDI Inflows in Agriculture Sector Using Pooled Ordinary Least Square (OLS), Pooled Generalized Least Square (GLS), Augmented Dickey-Fuller (ADF) and Philips-perron Unit Root Test." International Journal of Psychosocial Rehabilitation 24, no. 5 (2020): 2560–67. http://dx.doi.org/10.37200/ijpr/v24i5/pr201955.

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Angriany, A. Muthiah Nur, Georgina Maria Tinungki, and Raupong Raupong. "Estimasi Komponen Variansi pada Rancangan Faktorial Acak Lengkap Menggunakan Metode Generalized Least Squares." Jurnal Matematika Statistika dan Komputasi 15, no. 2 (2018): 54. http://dx.doi.org/10.20956/jmsk.v15i2.5714.

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AbstractsExperiment design is a test or a row of test by using both statistical description and inference statistical. The aim of this test is to change an input to become an output as a respond of the experiment. In the experiment design, variance of factor A, B , AB error of variance are called as variant component. The aim of this study is to estimate variance component on complete random factorial design for fixed model and mixed model by using Generalized Least Squares (GLS)method, where GLS method as a development of Ordinary Least Square method. It used to be applied on data of complete
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Yuan, Ke-Hai, and Yutaka Kano. "Meta-Analytical SEM: Equivalence Between Maximum Likelihood and Generalized Least Squares." Journal of Educational and Behavioral Statistics 43, no. 6 (2018): 693–720. http://dx.doi.org/10.3102/1076998618787799.

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Meta-analysis plays a key role in combining studies to obtain more reliable results. In social, behavioral, and health sciences, measurement units are typically not well defined. More meaningful results can be obtained by standardizing the variables and via the analysis of the correlation matrix. Structural equation modeling (SEM) with the combined correlations, called meta-analytical SEM (MASEM), is a powerful tool for examining the relationship among latent constructs as well as those between the latent constructs and the manifest variables. Three classes of methods have been proposed for MA
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Angriany, A. Muthiah Nur, Georgina Maria Tinungki, and Raupong Raupong. "Estimasi Komponen Variansi pada Rancangan Faktorial Acak Lengkap Menggunakan Metode Generalized Least Squares." Jurnal Matematika Statistika dan Komputasi 15, no. 2 (2018): 52. http://dx.doi.org/10.20956/jmsk.v15i2.5569.

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Perancangan percobaan adalah suatu uji atau sederet uji baik itu menggunakan statistika deskripsi maupun statistika inferensi, yang bertujuan untuk mengubah peubah input menjadi suatu output yang merupakan respon dari percobaan tersebut. Dalam perancangan percobaan, variansi dari faktor A, variansi dari faktor B, variansi interaksi faktor AB, dan variansi galat disebut dengan komponen varian. Penelitian ini bertujuan untuk mengestimasi komponen variansi pada rancangan faktorial acak lengkap model tetap dan model campuran menggunakan metode Generalized Least Squares (GLS), dimana metode GLS ada
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Ammari, Mohamed Lassaad, and Paul Fortier. "Analysis of MIMO Receiver Using Generalized Least Squares Method in Colored Environments." Journal of Computer Networks and Communications 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/720546.

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The classical detection techniques for multiple-input multiple-output (MIMO) systems are usually designed with the assumption that the additive complex Gaussian noise is uncorrelated. However, for closely spaced antennas, the additive noise is correlated due to the mutual antenna coupling. This letter analyzes an improved zero-forcing (ZF) technique for MIMO channels in colored environments. The additive noise is assumed to be correlated and the Rayleigh MIMO channel is considered doubly correlated. The improved ZF detector, based on the generalized least squares estimator (GLS), takes into ac
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Prastuti, Mike, and Iis Dewi Ratih. "KAJIAN SIMULASI ESTIMASI PARAMETER MODEL GSTAR-GLS UNTUK DATA BERPOLA MUSIMAN." MEDIA BINA ILMIAH 13, no. 12 (2019): 1769. http://dx.doi.org/10.33758/mbi.v13i12.261.

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Secara umum, metode untuk mengestimasi parameter dalam model GSTAR adalah Ordinary Least Squares (OLS). Estimasi parameter dengan menggunakan OLS untuk model GSTAR dengan residual yang berkorelasi akan menghasilkan estimator yang tidak efisien. Metode yang sesuai untuk mengestimasi parameter dengan residual yang berkorelasi adalah Generalized Least Square (GLS). Tujuan dari makalah ini adalah untuk mengusulkan metode GLS untuk mengestimasi parameter dalam model GSTAR Musiman, yang dikenal sebagai GSTAR-GLS, dan membandingkan hasilnya dengan metode OLS atau GSTAR-OLS. Selain itu, tujuan dari ma
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Roch, Sebastien, and Karl Rohe. "Generalized least squares can overcome the critical threshold in respondent-driven sampling." Proceedings of the National Academy of Sciences 115, no. 41 (2018): 10299–304. http://dx.doi.org/10.1073/pnas.1706699115.

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To sample marginalized and/or hard-to-reach populations, respondent-driven sampling (RDS) and similar techniques reach their participants via peer referral. Under a Markov model for RDS, previous research has shown that if the typical participant refers too many contacts, then the variance of common estimators does not decay like O(n−1), where n is the sample size. This implies that confidence intervals will be far wider than under a typical sampling design. Here we show that generalized least squares (GLS) can effectively reduce the variance of RDS estimates. In particular, a theoretical anal
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Affandi, Affandi, and Eddy Gunawan. "PENGARUH EKSPOR, IMPOR DAN JUMLAH PENDUDUK TERHADAP PDB INDONESIA TAHUN 1969 -2016." JURNAL PERSPEKTIF EKONOMI DARUSSALAM 4, no. 2 (2019): 249–64. http://dx.doi.org/10.24815/jped.v4i2.13021.

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This research aims to know the influence of export, import and population against Indonesia gross domestic product. The data used in this research is secondary data from the years 1969-2016 were sourced from a variety of reports and the compilation of the particular publication of the World Bank. The model used was multiple linear regression analysis method using the approach of Generalized Least Square parameter estimation (GLS). The results of calculations indicate that the variable is positive and significant effect of exports to GDP, population of Indonesia a negative and significant effec
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Nisak, Siti Choirun. "Seemingly Unrelated Regression Approach for GSTARIMA Model to Forecast Rain Fall Data in Malang Southern Region Districts." CAUCHY 4, no. 2 (2016): 57. http://dx.doi.org/10.18860/ca.v4i2.3488.

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Time series forecasting models can be used to predict phenomena that occur in nature. Generalized Space Time Autoregressive (GSTAR) is one of time series model used to forecast the data consisting the elements of time and space. This model is limited to the stationary and non-seasonal data. Generalized Space Time Autoregressive Integrated Moving Average (GSTARIMA) is GSTAR development model that accommodates the non-stationary and seasonal data. Ordinary Least Squares (OLS) is method used to estimate parameter of GSTARIMA model. Estimation parameter of GSTARIMA model using OLS will not produce
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Dissertations / Theses on the topic "Generalized least square (GLS)"

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Wang, Shuo. "An Improved Meta-analysis for Analyzing Cylindrical-type Time Series Data with Applications to Forecasting Problem in Environmental Study." Digital WPI, 2015. https://digitalcommons.wpi.edu/etd-theses/386.

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This thesis provides a case study on how the wind direction plays an important role in the amount of rainfall, in the village of Somi$acute{o}$. The primary goal is to illustrate how a meta-analysis, together with circular data analytic methods, helps in analyzing certain environmental issues. The existing GLS meta-analysis combines the merits of usual meta-analysis that yields a better precision and also accounts for covariance among coefficients. But, it is quite limited since information about the covariance among coefficients is not utilized. Hence, in my proposed meta-analysis, I take the
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Wu, Ruochen. "Essays on semi-parametric Bayesian econometric methods." Thesis, University of Cambridge, 2019. https://www.repository.cam.ac.uk/handle/1810/288745.

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This dissertation consists of three chapters on semi-parametric Bayesian Econometric methods. Chapter 1 applies a semi-parametric method to demand systems, and compares the abilities to recover the true elasticities of different approaches to linearly estimating the widely used Almost Ideal demand model, by either iteration or approximation. Chapter 2 co-authored with Dr. Melvyn Weeks introduces a new semi-parametric Bayesian Generalized Least Square estimator, which employs the Dirichlet Process prior to cope with potential heterogeneity in the error distributions. Two methods are discussed a
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Mbah, Alfred Kubong. "On the theory of records and applications." [Tampa, Fla.] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0002216.

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"The generalized least square estimation of polychoric correlation." Chinese University of Hong Kong, 1985. http://library.cuhk.edu.hk/record=b5885574.

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Skatulla, Sebastian. "Computational aspects of generalized continua based on moving least square approximations." 2006. http://hdl.handle.net/2440/59012.

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In recent years, current engineering technology lead to a renewed interest in generalized continuum theories. In particular, generalized continua are able to address fundamental physical phenomena which are related to the underlying microstructure of the material. Specifically scale-effects are of special interest. In this work a generalized deformation formulation is developed which allows to incorporate material information from the microscopic and the macroscopic space into an unified constitutive model. The approach is based on a theory developed by Sansour (1998) which was originated in
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劉家銓. "A generalized least square formulation for multi-period optimization of asset allocation." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/68934980600308859989.

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碩士<br>國立政治大學<br>風險管理與保險研究所<br>94<br>This paper deals with the insurance and pension asset liability management issue. Huang (2004) derives a theoretical close solution of multi-period asset allocation. However, there are two further problems in his paper. First, short selling is allowable. Second, multi-period investing is not acceptable. These two restrictions sometimes are big problems in practice. This paper extends his paper and releases these two restrictions. In other words, we intend to find a solution of multi-period asset allocation so that we can invest money and change proportion of
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Wang, Shanshan. "Bootstrapping generalized two stage least square estimates in simultaneous equation model with both fixed and random coefficients." Thesis, 1990. http://spectrum.library.concordia.ca/2634/1/ML56033.pdf.

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Books on the topic "Generalized least square (GLS)"

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Cardot, Hervé, and Pascal Sarda. Functional Linear Regression. Edited by Frédéric Ferraty and Yves Romain. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199568444.013.2.

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This article presents a selected bibliography on functional linear regression (FLR) and highlights the key contributions from both applied and theoretical points of view. It first defines FLR in the case of a scalar response and shows how its modelization can also be extended to the case of a functional response. It then considers two kinds of estimation procedures for this slope parameter: projection-based estimators in which regularization is performed through dimension reduction, such as functional principal component regression, and penalized least squares estimators that take into account
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Book chapters on the topic "Generalized least square (GLS)"

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Pan, Jian-Xin, and Kai-Tai Fang. "Generalized Least Square Estimation." In Growth Curve Models and Statistical Diagnostics. Springer New York, 2002. http://dx.doi.org/10.1007/978-0-387-21812-0_2.

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Chan, Kit Yan, C. K. Kwong, and Tharam S. Dillon. "Generalized Fuzzy Least Square Regression for Generating Customer Satisfaction Models." In Computational Intelligence Techniques for New Product Design. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27476-3_7.

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Cen, Song, and Zhi-Fei Long. "Generalized Conforming Thin Plate Element III — Perimeter-Point and Least-Square Conforming Schemes." In Advanced Finite Element Method in Structural Engineering. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00316-5_7.

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Li, Haoqi. "Generalized Least Square Estimation of Error-in-Variable Models and its Statistical Property." In Lecture Notes in Electrical Engineering. Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2386-6_200.

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Nithya, C., and V. Saravanan. "Generalized Least Square Feature Engineering-Based Weighted Gradient Boost SVM Classifier for Medical Data Diagnosis." In Smart Intelligent Computing and Applications. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9282-5_25.

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Sorman, A. U. "Regional Streamflow Network Analysis Using the Generalized Least Square Method: A Case Study in The Kizilirmak River Basin." In Integrated Technologies for Environmental Monitoring and Information Production. Springer Netherlands, 2003. http://dx.doi.org/10.1007/978-94-010-0231-8_8.

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"Generalized Least Squares (GLS): Extensions of the Classical Linear Regression Model." In Linear Regression: A Mathematical Introduction. SAGE Publications, Inc, 2019. http://dx.doi.org/10.4135/9781071802571.n5.

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Taneja, Abhishek. "Enhancing Web Data Mining." In Advances in Data Mining and Database Management. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-0613-3.ch005.

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An enormous production of databases in almost every area of human endeavor particularly through web has created a great demand for new, powerful tools for turning data into useful, task-oriented knowledge. The aim of this study is to study the predictive ability of Factor Analysis a web mining technique to prevent voting, averaging, stack generalization, meta- learning and thus saving much of our time in choosing the right technique for right kind of underlying dataset. This chapter compares the three factor based techniques viz. principal component regression (PCR), Generalized Least Square (GLS) Regression, and Maximum Likelihood Regression (MLR) method and explores their predictive ability on theoretical as well as on experimental basis. All the three factor based techniques have been compared using the necessary conditions for forecasting like R-Square, Adjusted R-Square, F-Test, JB (Jarque-Bera) test of normality. This study can be further explored and enhanced using sufficient conditions for forecasting like Theil's Inequality coefficient (TIC), and Janur Quotient (JQ).
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Ben Romdhane, Youssra, Sahar Loukil, and Souhaila Kammoun. "Economic African Development in the Context of FinTech." In Advances in Electronic Government, Digital Divide, and Regional Development. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1851-9.ch014.

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The purpose of this chapter is to analyze the effect of FinTech and political incertitude on economic growth through a multiple regression. Thus, the authors employ the method of generalized least square (GLS) with panel data. The sample concerns 21 African countries during (2001-2014-2017). The authors use a wide range of measures from Global Findex Database 2017, the World Bank platform, the World Bank national accounts data, and the OECD National Accounts data files base in the context of Africa. Empirical results show that FinTech is a driver of economic growth unless it is actively used in a developed digital infrastructure. In fact, the authors prove that, when financial technologies are used in both transactions (receive and made digital payment), they significantly contribute to the economic cycle. Passive use like simple consumption actions are not a significant lever for the economy. The principal contribution is to highlight that the active use of financial innovations and not passive one and the developed digital infrastructure do promote economic growth in African countries.
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Lee, Youngjo, Lars Rönnegård, and Maengseok Noh. "GLMs via Iterative Weighted Least Squares." In Data Analysis Using Hierarchical Generalized Linear Models With R. Chapman and Hall/CRC, 2017. http://dx.doi.org/10.1201/9781315211060-2.

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Conference papers on the topic "Generalized least square (GLS)"

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Velni, J. M., and K. Khorasani. "Localization of wideband sources in colored noise VIA generalized least squares (GLS)." In 2005 Microwave Electronics: Measurements, Identification, Applications. IEEE, 2005. http://dx.doi.org/10.1109/ssp.2005.1628651.

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Martinez-Flores, Rene, Achintya Haldar, and Hasan Katkhuda. "Structural Health Assessment After an Impact." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-13718.

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An innovative technique to assess structural health just after subjected to impulsive loadings (blasts, explosions, etc.) underdevelopment at the University of Arizona was experimentally verified and is presented in this paper. The authors called it the Generalized Iterative Least Square Extended Kalman Filter with Unknown Input (GILS-EKF-UI) method. The system is represented by finite elements and a Kalman filter-based system identification (SI) technique is used to identify the system. Some of the major characteristics of the method are that it does not require information on input excitatio
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Li, Tongying, and Hongbo Zhu. "Design and Implementation of Autoleveller Algorithm Based on Generalized Least Square Method." In 2019 Chinese Automation Congress (CAC). IEEE, 2019. http://dx.doi.org/10.1109/cac48633.2019.8996967.

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Laili, Masnatul, Bambang Widjanarko Otok, and Vita Ratnasari. "Hierarchical linear models on abdominal circumference research data using generalized least square." In THE 2016 CONFERENCE ON FUNDAMENTAL AND APPLIED SCIENCE FOR ADVANCED TECHNOLOGY (CONFAST 2016): Proceeding of ConFAST 2016 Conference Series: International Conference on Physics and Applied Physics Research (ICPR 2016), International Conference on Industrial Biology (ICIBio 2016), and International Conference on Information System and Applied Mathematics (ICIAMath 2016). Author(s), 2016. http://dx.doi.org/10.1063/1.4953975.

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Le, Anh Tuyen, Yijiang Nan, Le Chung Tran, Xiaojing Huang, Y. Jay Guo, and Yiannis Vardaxoglou. "Analog Least Mean Square Loop for Self-Interference Cancellation in Generalized Continuous Wave SAR." In 2018 IEEE 88th Vehicular Technology Conference (VTC-Fall). IEEE, 2018. http://dx.doi.org/10.1109/vtcfall.2018.8690717.

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Robberto, M. "A generalized least square algorithm to process infrared data taken in non-destructive readout mode." In SPIE Astronomical Telescopes + Instrumentation, edited by Jacobus M. Oschmann, Mark Clampin, Giovanni G. Fazio, and Howard A. MacEwen. SPIE, 2014. http://dx.doi.org/10.1117/12.2060114.

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Choi, Hon-Chit, Lingfeng Wen, Stefan Eberl, and Dagan Feng. "Fuzzy C-mean clustering on kinetic parameter estimation with generalized linear least square algorithm in SPECT." In Medical Imaging, edited by Joseph M. Reinhardt and Josien P. W. Pluim. SPIE, 2006. http://dx.doi.org/10.1117/12.653017.

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Thompson, Lonny L., and Prapot Kunthong. "A Residual Based Variational Method for Reducing Dispersion Error in Finite Element Methods." In ASME 2005 International Mechanical Engineering Congress and Exposition. ASMEDC, 2005. http://dx.doi.org/10.1115/imece2005-80551.

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A difficulty of the standard Galerkin finite element method has been the ability to accurately resolve oscillating wave solutions at higher frequencies. Many alternative methods have been developed including high-order methods, stabilized Galerkin methods, multi-scale variational methods, and other wave-based discretization methods. In this work, consistent residuals, both in the form of least-squares and gradient least-squares are linearly combined and added to the Galerkin variational Helmholtz equation to form a new generalized Galerkin least-squares method (GGLS). By allowing the stabiliza
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Deng, Yi, Han Liu, Huilong Wang, and Ding Liu. "Implicit Generalized Predictive Control of multivariable systems based on online Least Square Support Vector Machines of inverse system." In 2014 33rd Chinese Control Conference (CCC). IEEE, 2014. http://dx.doi.org/10.1109/chicc.2014.6896901.

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Zhang, Jialiang, and Jianfu Cao. "Fault Diagnosis for Closed Loop Nonlinear System Using Generalized Frequency Response Functions and Least Square Support Vector Machine." In 2019 1st International Conference on Industrial Artificial Intelligence (IAI). IEEE, 2019. http://dx.doi.org/10.1109/iciai.2019.8850734.

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