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Books on the topic 'Linear random growth models'

Author: Grafiati

Published: 15 March 2025

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1

Damron, Michael, Firas Rassoul-Agha, and Timo Seppäläinen, eds. Random Growth Models. Providence, Rhode Island: American Mathematical Society, 2018. http://dx.doi.org/10.1090/psapm/075.

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2

Lee, Youngjo. Generalized Linear Models with Random Effects. Second edition. | Boca Raton, Florida : CRC Press, [2017] |: Chapman and Hall/CRC, 2018. http://dx.doi.org/10.1201/9781315119953.

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3

Srivastava, M. S. Growth curve models. Toronto: University of Toronto, Dept. of Statistics, 1998.

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4

Stanley, H. Eugene, and Nicole Ostrowsky, eds. Random Fluctuations and Pattern Growth: Experiments and Models. Dordrecht: Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-009-2653-0.

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5

1941-, Stanley H. Eugene, Ostrowsky Nicole 1943-, Institut d'études scientifiques de Cargèse., and North Atlantic Treaty Organization. Scientific Affairs Division., eds. Random fluctuations and pattern growth: Experiments and models. Dordrecht [Netherlands]: Kluwer Academic Publishers, 1988.

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6

Kshirsagar, Anant M. Growth curves. New York: M. Dekker, 1995.

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7

M. C. M. de Gunst. A random model for plant cell population growth. [Amsterdam, the Netherlands]: Centrum voor Wiskunde en Informatica, 1989.

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8

Kaufman, Robert L. Interaction Effects in Linear and Generalized Linear Models: Examples and Applications Using Stata. California, USA: SAGE Publications, Incorporated, 2018.

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9

Cisilino, Adrián. Linear and nonlinear crack growth using boundary elements. Southampton, UK: WIT Press, 2000.

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10

Grafarend, Erik. Linear and Nonlinear Models: Fixed effects, random effects, and total least squares. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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11

Hastie, Trevor. Generalized additive models. Toronto: University of Toronto, Dept. of Statistics, 1985.

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12

Hastie, Trevor. Generalized additive models. London: Chapman and Hall, 1990.

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13

Hastie, Trevor. Generalized additive models. Boca Raton, Fla: Chapman & Hall/CRC, 1999.

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14

Rosen, Dietrich von. Multivariate linear normal models with special references to the growth curve model. Stockholm: Stockholms Universitet, 1985.

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15

Clements, Michael P. Evaluating the forecast of densities of linear and non-linear models: Applications to output growth and unemployment. Coventry: University of Warwick, Department of Economics, 1998.

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16

Huyse, Luc. Random field solutions including boundary condition uncertainty for steady-stae generalized Burgers equation. Hampton, VA: Institute for Computer Applications in Science and Engineering, NASA Langley Research Center, 2001.

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17

Górski, Jarosław. Non-linear models of structures with random geometric and material imperfactions [sic] simulation-based approach. Gdańsk: Wydawn. Politechniki Gdańskiej, 2006.

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18

Hastie, Trevor. Generalized additive models: Some applications. Toronto: University of Toronto, Dept. of Statistics, 1985.

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19

Jiang, Jiming. Robust Mixed Model Analysis. Singapore: World Scientific Publishing Co Pte Ltd, 2019.

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20

Majumdar, Satya N. Random growth models. Edited by Gernot Akemann, Jinho Baik, and Philippe Di Francesco. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198744191.013.38.

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Abstract:

This article discusses the connection between a particular class of growth processes and random matrices. It first provides an overview of growth model, focusing on the TASEP (totally asymmetric simple exclusion process) with parallel updating, before explaining how random matrices appear. It then describes multi-matrix models and line ensembles, noting that for curved initial data the spatial statistics for large time t is identical to the family of largest eigenvalues in a Gaussian Unitary Ensemble (GUE multi-matrix model. It also considers the link between the line ensemble and Brownian motion, and whether this persists on Gaussian Orthogonal Ensemble (GOE) matrices by comparing the line ensembles at fixed position for the flat polynuclear growth model (PNG) and at fixed time for GOE Brownian motions. Finally, it examines (directed) last passage percolation and random tiling in relation to growth models.

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21

Random Growth Models. American Mathematical Society, 2018.

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22

Lee, Youngjo, John A. Nelder, and Yudi Pawitan. Generalized Linear Models with Random Effects. Chapman and Hall/CRC, 2006. http://dx.doi.org/10.1201/9781420011340.

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23

Nelder, John A., Yudi Pawitan, and Youngjo Lee. Generalized Linear Models with Random Effects. Taylor & Francis Group, 2021.

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24

Linear and nonlinear models: Fixed effects, random effects, and mixed models. Berlin: Walter de Gruyter, 2006.

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25

Growth Curve Models And Statistical Diagnostics. Springer, 2011.

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26

Pan, Jian-Xin, and Kai-Tai Fang. Growth Curve Models and Statistical Diagnostics. Springer London, Limited, 2012.

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27

Growth Curve Models With Statistical Diagnostics. Springer, 2002.

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28

Stanley, Harry Eugene, and N. Ostrowsky. Random Fluctuations and Pattern Growth: Experiments and Models. Springer, 2012.

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29

Random Fluctuations and Pattern Growth: Experiments and Models. Island Press, 1988.

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30

Smithson, Michael, and Yiyun Shou. Generalized Linear Models for Bounded and Limited Quantitative Variables. SAGE Publications, Incorporated, 2020.

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31

Capen, Robert Calvin. Exact testing procedures for unbalanced random and mixed linear models. 1991.

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32

Hodges, James S. Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects. Chapman and Hall/CRC, 2021.

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33

Hodges, James S. Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects. Taylor & Francis Group, 2013.

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34

Hodges, James S. Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects. Taylor & Francis Group, 2016.

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35

Hodges, James S. Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects. Taylor & Francis Group, 2016.

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36

Hodges, James S. Richly Parameterized Linear Models: Additive, Time Series, and Spatial Models Using Random Effects. Taylor & Francis Group, 2016.

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37

General Linear Model. Cambridge University Press, 2023.

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38

Pratt, James L. The laplace approximation and inference in generalized linear models with two or more random effects. 1994.

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39

Wood, Simon N. Generalized Additive Models. Taylor & Francis Group, 2006.

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40

Lee, Kiseok. Adaptive estimation of random parameter regression models by state space representation methods. 1990.

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41

Nelder, John A., Yudi Pawitan, and Youngjo Lee. Generalized Linear Models with Random Effects: Unified Analysis Via H-Likelihood. Taylor & Francis Group, 2006.

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42

Nelder, John A., Yudi Pawitan, and Youngjo Lee. Generalized Linear Models with Random Effects: Unified Analysis Via H-Likelihood. Taylor & Francis Group, 2010.

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43

Dasgupta, Ratan. Advances in Growth Curve Models: Topics from the Indian Statistical Institute. Springer London, Limited, 2013.

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44

Dasgupta, Ratan. Advances in Growth Curve Models: Topics from the Indian Statistical Institute. Springer, 2015.

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45

Linear And Nonlinear Models Vol I Fixed Effects Random Effects And Total Least Squares. Springer, 2012.

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46

General Linear Model: A Primer. Cambridge University Press, 2023.

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47

General Linear Model: A Primer. Cambridge University Press, 2023.

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48

Lorenz, Frederick O., Kandauda A. S. Wickrama, Tae Kyoung Lee, and Catherine Walker O'Neal. Higher-Order Growth Curves and Mixture Modeling with Mplus: A Practical Guide. Taylor & Francis Group, 2016.

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49

Gallo, Jose Manuel. Exact tests for fixed and random effects in unbalanced linear mixed models. 1987.

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50

Nelder, John A., Yudi Pawitan, and Youngjo Lee. Generalized Linear Models with Random Effects: Unified Analysis Via H-Likelihood, Second Edition. Taylor & Francis Group, 2017.

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