Relevant bibliographies by topics / Non-linear models

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

Academic literature on the topic 'Non-linear models'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Non-linear models"

1

Potocký, Rastislav, and Van Ban To. "On parameter-effects arrays in non-linear regression models." Applications of Mathematics 38, no. 2 (1993): 123–32. http://dx.doi.org/10.21136/am.1993.104539.

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Gasparrini, A., B. Armstrong, and M. G. Kenward. "Distributed lag non-linear models." Statistics in Medicine 29, no. 21 (2010): 2224–34. http://dx.doi.org/10.1002/sim.3940.

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Burnett, Richard T., W. H. Ross, and Daniel Krewski. "Non-linear mixed regression models." Environmetrics 6, no. 1 (1995): 85–99. http://dx.doi.org/10.1002/env.3170060108.

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Chaokui, Li, Zhu Qing, and Song Chengfang. "Processing approach of non-linear adjustment models in the space of non-linear models." Geo-spatial Information Science 6, no. 2 (2003): 25–30. http://dx.doi.org/10.1007/bf02826750.

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Morozumi, T., and S. Nojiri. "An Analysis of Non-Compact Non-Linear Models." Progress of Theoretical Physics 75, no. 3 (1986): 677–85. http://dx.doi.org/10.1143/ptp.75.677.

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V. Vallinayagam, V. Vallinayagam, S. Prathap S. Prathap, and P. Venkatesan P. Venkatesan. "Non-Linear Regression Models for Heart Attack Data – An Empirical Comparison." Indian Journal of Applied Research 4, no. 6 (2011): 332–34. http://dx.doi.org/10.15373/2249555x/june2014/102.

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Hines, W. G. S., and John Haigh. "Non-linear ESS models and polymorphism." Journal of Applied Probability 22, no. 4 (1985): 747–56. http://dx.doi.org/10.2307/3213942.

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Extensions of ESS theory to situations well outside the classical formulation often assume, as a convenience, that the population being modelled is, in some sense, monomorphic. While this assumption is in keeping with the original approach used in developing the theory, it is rendered less plausible by the observation that the original models do not preclude the possibility of polymorphism, a potentially serious omission. We consider a generalisation of the classical bilinear fitness function, and examine the circumstances that will tend to favour monomorphism.
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Baptista, J. M. "Twisting gauged non-linear sigma-models." Journal of High Energy Physics 2008, no. 02 (2008): 096. http://dx.doi.org/10.1088/1126-6708/2008/02/096.

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Müller, Peter, Mike West, and Steven MacEachern. "Bayesian Models for Non‐linear Autoregressions." Journal of Time Series Analysis 18, no. 6 (1997): 593–614. http://dx.doi.org/10.1111/1467-9892.00070.

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Hines, W. G. S., and John Haigh. "Non-linear ESS models and polymorphism." Journal of Applied Probability 22, no. 04 (1985): 747–56. http://dx.doi.org/10.1017/s0021900200107983.

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Extensions of ESS theory to situations well outside the classical formulation often assume, as a convenience, that the population being modelled is, in some sense, monomorphic. While this assumption is in keeping with the original approach used in developing the theory, it is rendered less plausible by the observation that the original models do not preclude the possibility of polymorphism, a potentially serious omission. We consider a generalisation of the classical bilinear fitness function, and examine the circumstances that will tend to favour monomorphism.
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Dissertations / Theses on the topic "Non-linear models"

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Bowtell, Philip. "Non-linear functional relationships." Thesis, University of Reading, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.284183.

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Schittenkopf, Christian, Georg Dorffner, and Engelbert J. Dockner. "Non-linear versus non-gaussian volatility models." SFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business, 1999. http://epub.wu.ac.at/724/1/document.pdf.

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One of the most challenging topics in financial time series analysis is the modeling of conditional variances of asset returns. Although conditional variances are not directly observable there are numerous approaches in the literature to overcome this problem and to predict volatilities on the basis of historical asset returns. The most prominent approach is the class of GARCH models where conditional variances are governed by a linear autoregressive process of past squared returns and variances. Recent research in this field, however, has focused on modeling asymmetries of conditional varianc
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Liangrocapart, Sompong. "Non-linear spectral mixing models." Thesis, University of Surrey, 2001. http://epubs.surrey.ac.uk/842807/.

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In this research study, non-linear spectral mixing models have been developed and employed to achieve unmixing the proportions of components accurately and retrieving the physical parameters of the mixture. The first focus is on a comparative study of linear and non-linear spectral mixing models. A carefully-controlled experiment was conducted in the laboratory. The aim is to test both models to unmix ternary powdered-chalk mixtures by using the directional reflectance data. The results demonstrated the superiority of the non-linear model over the linear model. However, there was at least one
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Persson, Jonas. "Linear models of non-linear power system components." Licentiate thesis, KTH, Electrical Systems, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-1415.

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Lampietti, Dario Giovanni. "Foreign exchange markets linear vs. non-linear models /." [Zürich] : [Citibank], 1993. http://www.ub.unibe.ch/content/bibliotheken_sammlungen/sondersammlungen/dissen_bestellformular/index_ger.html.

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Ferro, Dennis Eduardo Zavaleta. "Some geometric aspects of non-linear sigma models /." São Paulo, 2016. http://hdl.handle.net/11449/151647.

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Orientador: Andrei Mikhailov<br>Resumo: We review some relevant examples for String Theory of non-linear sigma models. These are bosonic strings propagating in curved background, the Wess-Zumino-Witten model and superstrings in flat and AdS superspace. The mathematical tools required for the study of these models (e.g. topological quantization, Cartan geometry, Lie superalgebras and geometry on coset spaces) are also described. Throughout the dissertation we have focused on classical aspects of these models such as the construction of the action and its symmetries where conditions for holomorp
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Oxley, Andrew. "Linear models of non-precipitating convection." Thesis, University of Surrey, 2018. http://epubs.surrey.ac.uk/846538/.

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Convective clouds are a key driver of the earth's general circulation as well as producing important impacts on local weather. By investigating simplified systems that yield analytic solutions we hope to gain valuable insight into real world scenarios. We use the linearised Boussinesq form of the Navier-Stokes equations and the buoyancy equations derived for unsaturated and saturated air derived from the first law of thermodynamics as a basis to investigate the relationships between cloud spacing, cloud width and cloud growth rate for different choices of cloud scheme. We build on work by Bret
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Häggström, Lundevaller Erling. "Tests of random effects in linear and non-linear models." Doctoral thesis, Umeå universitet, Statistik, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-15.

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Häggström, Lundevaller Erling. "Tests of random effects in linear and non-linear models /." Umeå : Department of Statistics, University of Umeå, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-15.

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Wang, Wei. "CAUSAL MEDIATION ANALYSIS FOR NON-LINEAR MODELS." Case Western Reserve University School of Graduate Studies / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=case1332961697.

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Books on the topic "Non-linear models"

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Ketov, Sergei V. Quantum Non-linear Sigma-Models. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-662-04192-5.

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Fosseprez, Marc. Non-linear circuits: Qualitative analysis of non-linear, non-reciprocal circuits. J. Wiley, 1992.

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Berezin, I︠U︡ A. Modelling non-linear wave processes. VNU Science Press, 1987.

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Kitsos, Christos P. Optimal Experimental Design for Non-Linear Models. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-45287-1.

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Hall, Stephen. Optimal control of stochastic non-linear models. Bank of England, 1988.

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Guardia, Soledad M. Guarch. Unit root non-linear time series models. UMIST, 1997.

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7

Ohlsson, Esbjörn, and Björn Johansson. Non-Life Insurance Pricing with Generalized Linear Models. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-10791-7.

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Fraser, D. A. S. Non-nested linear models: A conditional confidence approach. University of Toronto, Dept. of Statistics, 1985.

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9

Gilbert, Abraham-Frois, ed. Non-linear dynamics and endogenous cycles. Springer, 1998.

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Yoshida, Kentaroh. Yang–Baxter Deformation of 2D Non-Linear Sigma Models. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1703-4.

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Book chapters on the topic "Non-linear models"

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Mead, R., R. N. Curnow, and A. M. Hasted. "Non-linear models." In Statistical Methods in Agriculture and Experimental Biology. Springer US, 1993. http://dx.doi.org/10.1007/978-1-4899-6928-6_12.

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Mead, R., R. N. Curnow, and A. M. Hasted. "Non-linear models." In Statistical Methods in Agriculture and Experimental Biology. Springer US, 1992. http://dx.doi.org/10.1007/978-1-4899-6930-9_12.

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Venables, W. N., and B. D. Ripley. "Non-linear Models." In Statistics and Computing. Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4757-2719-7_9.

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Venables, W. N., and B. D. Ripley. "Non-linear Models." In Statistics and Computing. Springer New York, 1999. http://dx.doi.org/10.1007/978-1-4757-3121-7_8.

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5

Krijnen, Wim P., and Ernst C. Wit. "Non-linear Models." In Computational and Statistical Methods for Chemical Engineering. Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003178194-8.

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Chatfield, Chris, and Haipeng Xing. "Non-Linear Models." In The Analysis of Time Series. Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9781351259446-11.

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Sabatier, Jocelyn, Christophe Farges, and Vincent Tartaglione. "Non-linear Models." In Intelligent Systems, Control and Automation: Science and Engineering. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-96749-9_6.

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Kitsos, Christos P. "Non-linear Models." In International Encyclopedia of Statistical Science. Springer Berlin Heidelberg, 2025. https://doi.org/10.1007/978-3-662-69359-9_414.

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Doukhan, Paul. "Non-linear Processes." In Stochastic Models for Time Series. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-76938-7_7.

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Turkman, Kamil Feridun, Manuel González Scotto, and Patrícia de Zea Bermudez. "Nonlinear Time Series Models." In Non-Linear Time Series. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07028-5_2.

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Conference papers on the topic "Non-linear models"

1

MUIR, TG. "SOME SIMPLE PROPAGATION MODELS FOR LINEAR AND PARAMETRIC SOURCES IN SHALLOW WATER." In Underwater Applications of Non-Linear Acoustics 1979. Institute of Acoustics, 2024. http://dx.doi.org/10.25144/23535.

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Chen, Wenliang, Zhenghua Li, and Min Zhang. "Linear and Non-Linear Models for Purchase Prediction." In RecSys '15: Ninth ACM Conference on Recommender Systems. ACM, 2015. http://dx.doi.org/10.1145/2813448.2813518.

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Jastrzebski, Adam K., and Antony Davies. "Extraction of Linear and Non-Linear MESFET Models." In 21st European Microwave Conference, 1991. IEEE, 1991. http://dx.doi.org/10.1109/euma.1991.336468.

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Rao, Shilpa, Sundeep Prabhakar Chepuri, and Geert Leus. "Greedy sensor selection for non-linear models." In 2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP). IEEE, 2015. http://dx.doi.org/10.1109/camsap.2015.7383781.

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Foldesi, P., L. T. Koczy, and J. Botzheim. "Fuzzy Solution for Non-linear Quality Models." In 2008 International Conference on Intelligent Engineering Systems. IEEE, 2008. http://dx.doi.org/10.1109/ines.2008.4481306.

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Gershon, Ron, and Allan D. Jepson. "Non-Linear Models Of Early Chromatic Processing." In 1987 Cambridge Symposium, edited by T. Russell Hsing. SPIE, 1987. http://dx.doi.org/10.1117/12.976496.

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Alippi, A., A. Bettucci, A. Biagioni, et al. "Non linear behaviour of cell tensegrity models." In INTERNATIONAL CONGRESS ON ULTRASONICS: Gdańsk 2011. AIP, 2012. http://dx.doi.org/10.1063/1.3703199.

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Cakmak, Burak, Ole Winther, and Bernard H. Fleury. "S-AMP for non-linear observation models." In 2015 IEEE International Symposium on Information Theory (ISIT). IEEE, 2015. http://dx.doi.org/10.1109/isit.2015.7282968.

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Lichiardopol, Stefan, and Christophe Sueur. "Decoupling of non-linear bond-graph models." In 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control. IEEE, 2006. http://dx.doi.org/10.1109/cacsd-cca-isic.2006.4776988.

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Lichiardopol, Stefan, and Christophe Sueur. "Decoupling of Non-Linear Bond-Graph Models." In 2006 IEEE International Conference on Control Applications. IEEE, 2006. http://dx.doi.org/10.1109/cca.2006.286214.

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Reports on the topic "Non-linear models"

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Marchese, Malvina. Advanced Non-Linear Regression Modelling. Instats Inc., 2023. http://dx.doi.org/10.61700/mrtlpflhp64q7469.

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This two-day seminar offers an in-depth introduction to non-linear regression models for cross sectional data, covering binary, multinomial, ordinal, censored, count, and the very popular quantile regression models. You will learn everything you need to know in order to understand and apply these methods in your own research. An official Instats certificate of completion is provided at the conclusion of the seminar. For European PhD students, the seminar offers 2 ECTS Equivalent point
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Marchese, Malvina. Advanced Non-Linear Regression Modelling. Instats Inc., 2023. http://dx.doi.org/10.61700/ovehw89kw8hwq469.

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This two-day seminar offers an in-depth introduction to non-linear regression models for cross sectional data, covering binary, multinomial, ordinal, censored, count, and the very popular quantile regression models. You will learn everything you need to know in order to understand and apply these methods in your own research. An official Instats certificate of completion is provided at the conclusion of the seminar. For European PhD students, the seminar offers 2 ECTS Equivalent point
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Armstrong, Dave. Interactions and Non-Linearities in Regression Models. Instats Inc., 2023. http://dx.doi.org/10.61700/lnujxkrxa8jtk469.

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Many theories in the social sciences and beyond suggest non-linear or conditional relationships. Even if relationships of interest are assumed to be linear, it is important to test whether those assumptions are tenable. In this course, we consider how to diagnose un-modeled non-linearity in generalized linear models, how to estimate models with non-linear and/or conditional relationships and how to best present the results of those models to people who may engage with your work. An official Instats certificate of completion is provided at the conclusion of the seminar. The seminar offers 2 ECT
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Armstrong, Dave. Interactions and Non-Linearities in Regression Models. Instats Inc., 2023. http://dx.doi.org/10.61700/0w8ov518ywasy469.

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Many theories in the social sciences and beyond suggest non-linear or conditional relationships. Even if relationships of interest are assumed to be linear, it is important to test whether those assumptions are tenable. In this course, we consider how to diagnose un-modeled non-linearity in generalized linear models, how to estimate models with non-linear and/or conditional relationships and how to best present the results of those models to people who may engage with your work. An official Instats certificate of completion is provided at the conclusion of the seminar. The seminar offers 2 ECT
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Mohammedi, Nourddine. Classically Integrable Two-Dimensional Non-Linear Sigma Models. GIQ, 2015. http://dx.doi.org/10.7546/giq-16-2015-250-255.

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Levit, B. Y. Approximately Integrable Linear Statistical Models in Non-Parametric Estimation. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada227395.

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Levi, Mark. Mathematical Models of Non-Linear Mechanical and Electrical Systems and Their Qualitative Behavior. Defense Technical Information Center, 1991. http://dx.doi.org/10.21236/ada248847.

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Arango-Thomas, Luis Eduardo, and Luis Fernando Melo-Velandia. Expansions and contractions in Brazil, Colombia and Mexico: a view through non-linear models. Banco de la República, 2003. http://dx.doi.org/10.32468/be.186.

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Andreasen, Martin, Jesús Fernández-Villaverde, and Juan Rubio-Ramírez. The Pruned State-Space System for Non-Linear DSGE Models: Theory and Empirical Applications. National Bureau of Economic Research, 2013. http://dx.doi.org/10.3386/w18983.

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Basu, Anirban, Daniel Polsky, and Willard Manning. Use of Propensity Scores in Non-Linear Response Models: The Case for Health Care Expenditures. National Bureau of Economic Research, 2008. http://dx.doi.org/10.3386/w14086.

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