Efficient two-dimensional smoothing with P-spline ANOVA mixed models and nested bases

Low-rank smoothing techniques have gained much popularity in non-standard regression modeling. In particular, penalized splines and tensor product smooths are used as flexible tools to study non-parametric relationships among several covariates. The use of standard statistical software facilitates t...

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Veröffentlicht in:Computational statistics & data analysis Jg. 61; S. 22 - 37
Hauptverfasser: Lee, Dae-Jin, Durbán, María, Eilers, Paul
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier B.V 01.05.2013
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ISSN:0167-9473, 1872-7352
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Abstract Low-rank smoothing techniques have gained much popularity in non-standard regression modeling. In particular, penalized splines and tensor product smooths are used as flexible tools to study non-parametric relationships among several covariates. The use of standard statistical software facilitates their use for several types of problems and applications. However, when interaction terms are considered in the modeling, and multiple smoothing parameters need to be estimated standard software does not work well when datasets are large or higher-order interactions are included or need to be tested. In this paper, a general approach for constructing and estimating bivariate smooth models for additive and interaction terms using penalized splines is proposed. The formulation is based on the mixed model representation of the smooth-ANOVA model by Lee and Durbán (in press), and several nested models in terms of random effects components are proposed. Each component has a clear interpretation in terms of function shape and model identifiability constraints. The term PS-ANOVA is coined for this type of models. The estimation method is relatively straightforward based on the algorithm by Schall (1991) for generalized linear mixed models. Further, a simplification of the smooth interaction term is used by constructing lower-rank basis (nested basis). Finally, some simulation studies and real data examples are presented to evaluate the new model and the estimation method.
AbstractList Low-rank smoothing techniques have gained much popularity in non-standard regression modeling. In particular, penalized splines and tensor product smooths are used as flexible tools to study non-parametric relationships among several covariates. The use of standard statistical software facilitates their use for several types of problems and applications. However, when interaction terms are considered in the modeling, and multiple smoothing parameters need to be estimated standard software does not work well when datasets are large or higher-order interactions are included or need to be tested. In this paper, a general approach for constructing and estimating bivariate smooth models for additive and interaction terms using penalized splines is proposed. The formulation is based on the mixed model representation of the smooth-ANOVA model by Lee and Durbán (in press), and several nested models in terms of random effects components are proposed. Each component has a clear interpretation in terms of function shape and model identifiability constraints. The term PS-ANOVA is coined for this type of models. The estimation method is relatively straightforward based on the algorithm by Schall (1991) for generalized linear mixed models. Further, a simplification of the smooth interaction term is used by constructing lower-rank basis (nested basis). Finally, some simulation studies and real data examples are presented to evaluate the new model and the estimation method.
Low-rank smoothing techniques have gained much popularity in non-standard regression modeling. In particular, penalized splines and tensor product smooths are used as flexible tools to study non-parametric relationships among several covariates. The use of standard statistical software facilitates their use for several types of problems and applications. However, when interaction terms are considered in the modeling, and multiple smoothing parameters need to be estimated standard software does not work well when datasets are large or higher-order interactions are included or need to be tested. In this paper, a general approach for constructing and estimating bivariate smooth models for additive and interaction terms using penalized splines is proposed. The formulation is based on the mixed model representation of the smooth-ANOVA model by Lee and Durbán (in press), and several nested models in terms of random effects components are proposed. Each component has a clear interpretation in terms of function shape and model identifiability constraints. The term PS-ANOVA is coined for this type of models. The estimation method is relatively straightforward based on the algorithm by Schall (1991) for generalized linear mixed models. Further, a simplification of the smooth interaction term is used by constructing lower-rank basis (nested basis). Finally, some simulation studies and real data examples are presented to evaluate the new model and the estimation method.
Author Eilers, Paul
Durbán, María
Lee, Dae-Jin
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Cites_doi 10.18637/jss.v009.i01
10.1007/s11222-012-9314-z
10.1198/1061860043010
10.1111/j.1541-0420.2006.00574.x
10.1214/ss/1038425655
10.1016/j.csda.2007.10.022
10.1016/j.csda.2008.05.032
10.1093/biomet/60.2.255
10.1016/j.csda.2004.07.008
10.1111/j.1467-9868.2008.00695.x
10.1198/106186002844
10.1191/1471082X04st080oa
10.1177/1471082X1001100104
10.1111/j.1467-9868.2010.00749.x
10.1093/biomet/78.4.719
10.1214/aos/1176344136
10.1080/01621459.1993.10594284
10.1111/j.2517-6161.1993.tb01939.x
10.1111/j.1467-9868.2006.00543.x
10.1111/j.2517-6161.1993.tb01917.x
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Keywords Schall’s algorithm
Penalized splines
Mixed models
Smooth-ANOVA decomposition
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References Breslow, Clayton (br000020) 1993; 88
Bowman, Azzalini (br000015) 1997
Duncan (br000050) 1961
Ruppert, Wand, Carroll (br000120) 2003
Belitz, Lang (br000010) 2008; 53
Schall (br000125) 1991; 78
Lee, D.-J., 2010. Smothing mixed model for spatial and spatio-temporal data. Ph.D. Thesis, Department of Statistics, Universidad Carlos III de Madrid, Spain.
Currie, Durbán, Eilers (br000045) 2006; 68
Gu (br000070) 2002
Hastie, Tibshirani (br000075) 1990
Reiss, Ogden (br000115) 2009; 71
Hastie, Tibshirani (br000080) 1993; 55
Wood, S.N., Scheipl, F., Faraway, J., 2012. Straightforward intermediate rank tensor product smoothing in mixed models. Statistics and Computing, in press
Ngo, Wand (br000105) 2004; 9
Pinheiro, Bates (br000110) 2000
Akaike (br000005) 1973; 60
Eilers, Marx (br000060) 1996; 11
Lang, Brezger (br000085) 2004; 13
Buja, Hastie, Tibshirani (br000025) 1989; 17
Cameron, Trivedi (br000030) 1998; vol. 30
Wahba (br000145) 1990
spline ANOVA-type interaction models for spatio-temporal smoothing. Statistical Modelling 1, 49–69 (in press).
Scheipl, Greven, Küchenhoff (br000130) 2008; 52
.
Wood (br000150) 2006
Wood (br000155) 2006; 62
Eilers, Currie, Durbán (br000055) 2006; 50
Eilers, Marx (br000065) 2002; 11
Wood (br000160) 2011; 73
Searle, Casella, McCulloch (br000140) 1992
Chen (br000035) 1993; 55
Currie, Durbán, Eilers (br000040) 2004; 4
Lee, D.-J., Durbán, M., 2011.
Schwarz (br000135) 1978; 6
Lee, Nelder, Pawitan (br000100) 2006
10.1016/j.csda.2012.11.013_br000095
Gu (10.1016/j.csda.2012.11.013_br000070) 2002
Wood (10.1016/j.csda.2012.11.013_br000155) 2006; 62
Akaike (10.1016/j.csda.2012.11.013_br000005) 1973; 60
Duncan (10.1016/j.csda.2012.11.013_br000050) 1961
Buja (10.1016/j.csda.2012.11.013_br000025) 1989; 17
Currie (10.1016/j.csda.2012.11.013_br000045) 2006; 68
Eilers (10.1016/j.csda.2012.11.013_br000060) 1996; 11
10.1016/j.csda.2012.11.013_br000090
Ngo (10.1016/j.csda.2012.11.013_br000105) 2004; 9
Searle (10.1016/j.csda.2012.11.013_br000140) 1992
Belitz (10.1016/j.csda.2012.11.013_br000010) 2008; 53
Currie (10.1016/j.csda.2012.11.013_br000040) 2004; 4
Breslow (10.1016/j.csda.2012.11.013_br000020) 1993; 88
Eilers (10.1016/j.csda.2012.11.013_br000065) 2002; 11
Wahba (10.1016/j.csda.2012.11.013_br000145) 1990
Cameron (10.1016/j.csda.2012.11.013_br000030) 1998; vol. 30
Lee (10.1016/j.csda.2012.11.013_br000100) 2006
Schall (10.1016/j.csda.2012.11.013_br000125) 1991; 78
Scheipl (10.1016/j.csda.2012.11.013_br000130) 2008; 52
Wood (10.1016/j.csda.2012.11.013_br000150) 2006
10.1016/j.csda.2012.11.013_br000165
Hastie (10.1016/j.csda.2012.11.013_br000080) 1993; 55
Bowman (10.1016/j.csda.2012.11.013_br000015) 1997
Lang (10.1016/j.csda.2012.11.013_br000085) 2004; 13
Chen (10.1016/j.csda.2012.11.013_br000035) 1993; 55
Ruppert (10.1016/j.csda.2012.11.013_br000120) 2003
Reiss (10.1016/j.csda.2012.11.013_br000115) 2009; 71
Wood (10.1016/j.csda.2012.11.013_br000160) 2011; 73
Pinheiro (10.1016/j.csda.2012.11.013_br000110) 2000
Schwarz (10.1016/j.csda.2012.11.013_br000135) 1978; 6
Eilers (10.1016/j.csda.2012.11.013_br000055) 2006; 50
Hastie (10.1016/j.csda.2012.11.013_br000075) 1990
References_xml – volume: 11
  start-page: 758
  year: 2002
  end-page: 783
  ident: br000065
  article-title: Generalized linear additive smooth structures
  publication-title: Journal of Computational and Graphical Statistics
– reference: Wood, S.N., Scheipl, F., Faraway, J., 2012. Straightforward intermediate rank tensor product smoothing in mixed models. Statistics and Computing, in press (
– year: 2006
  ident: br000150
  publication-title: Generalized Additive Models—An Introduction With R
– year: 2000
  ident: br000110
  publication-title: Mixed-Effects Models in
– volume: 52
  start-page: 3283
  year: 2008
  end-page: 3299
  ident: br000130
  article-title: Size and power of tests for a zero random effect variance or polynomial regression in additive and linear mixed models
  publication-title: Computational Statistics and Data Analysis
– volume: 50
  start-page: 61
  year: 2006
  end-page: 76
  ident: br000055
  article-title: Fast and compact smoothing on large multidimensional grids
  publication-title: Computational Statistics and Data Analysis
– volume: 62
  start-page: 1025
  year: 2006
  end-page: 1036
  ident: br000155
  article-title: Low-rank scale-invariant tensor product smooths for generalized additive mixed models
  publication-title: Biometrics
– reference: ).
– volume: 9
  year: 2004
  ident: br000105
  article-title: Smoothing with mixed model software
  publication-title: Journal of Statistical Software
– volume: 4
  start-page: 279
  year: 2004
  end-page: 298
  ident: br000040
  article-title: Smoothing and forecasting mortality rates
  publication-title: Statistical Modelling
– reference: Lee, D.-J., 2010. Smothing mixed model for spatial and spatio-temporal data. Ph.D. Thesis, Department of Statistics, Universidad Carlos III de Madrid, Spain.
– year: 1992
  ident: br000140
  publication-title: Variance Components
– reference: -spline ANOVA-type interaction models for spatio-temporal smoothing. Statistical Modelling 1, 49–69 (in press).
– year: 1990
  ident: br000075
  publication-title: Generalized Additive Models
– volume: 71
  start-page: 505
  year: 2009
  end-page: 523
  ident: br000115
  article-title: Smoothing parameter selection for a class of semiparametric linear models
  publication-title: Journal of the Royal Statistical Society: Series B
– volume: 55
  start-page: 473
  year: 1993
  end-page: 491
  ident: br000035
  article-title: Fitting multivariate regression functions by interaction spline models
  publication-title: Journal of the Royal Statistical Society. Series B
– year: 1961
  ident: br000050
  article-title: A Socioeconomic Index for All Occupations
– volume: 68
  start-page: 1
  year: 2006
  end-page: 22
  ident: br000045
  article-title: Generalized linear array models with applications to multidimensional smoothing
  publication-title: Journal of the Royal Statistical Society. Series B
– volume: vol. 30
  year: 1998
  ident: br000030
  publication-title: Regression Analysis of Count Data
– year: 2002
  ident: br000070
  publication-title: Smoothing Spline ANOVA Models
– year: 1990
  ident: br000145
  article-title: Spline Models for Observational Data
– volume: 13
  start-page: 183
  year: 2004
  end-page: 212
  ident: br000085
  article-title: Bayesian
  publication-title: Journal of Computational and Graphical Statistics
– volume: 60
  start-page: 255
  year: 1973
  end-page: 265
  ident: br000005
  article-title: Maximum likelihood identification of gaussian autoregressive moving average models
  publication-title: Biometrika
– volume: 53
  start-page: 61
  year: 2008
  end-page: 81
  ident: br000010
  article-title: Simultaneous selection of variables and smoothing parameters in structured additive regression models
  publication-title: Computational Statistics and Data Analysis
– volume: 11
  start-page: 89
  year: 1996
  end-page: 121
  ident: br000060
  article-title: Flexible smoothing with
  publication-title: Statistical Science
– volume: 6
  start-page: 461
  year: 1978
  end-page: 464
  ident: br000135
  article-title: Estimating the dimension of a model
  publication-title: Annals of Statistics
– volume: 17
  start-page: 453
  year: 1989
  end-page: 555
  ident: br000025
  article-title: Linear smoothers and additive models (with discussion)
  publication-title: The Annals of Statistics
– year: 2006
  ident: br000100
  publication-title: Generalized Linear Models with Random Effects: Unified Analysis Via
– volume: 78
  start-page: 719
  year: 1991
  end-page: 721
  ident: br000125
  article-title: Estimation in generalized linear models with random effects
  publication-title: Biometrika
– year: 2003
  ident: br000120
  publication-title: Semiparametric Regression
– year: 1997
  ident: br000015
  publication-title: Applied Smoothing Techniques for Data Analysis: The Kernel Approach with
– volume: 73
  start-page: 3
  year: 2011
  end-page: 36
  ident: br000160
  article-title: Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models
  publication-title: Journal of the Royal Statistical Society. Series B
– volume: 88
  start-page: 9
  year: 1993
  end-page: 25
  ident: br000020
  article-title: Aproximated inference in generalised linear mixed models
  publication-title: Journal of the American Statistical Association
– volume: 55
  start-page: 757
  year: 1993
  end-page: 796
  ident: br000080
  article-title: Varying-coefficient models
  publication-title: Journal of the Royal Statistical Society. Series B
– reference: Lee, D.-J., Durbán, M., 2011.
– year: 2006
  ident: 10.1016/j.csda.2012.11.013_br000150
– volume: 9
  issue: 1
  year: 2004
  ident: 10.1016/j.csda.2012.11.013_br000105
  article-title: Smoothing with mixed model software
  publication-title: Journal of Statistical Software
  doi: 10.18637/jss.v009.i01
– ident: 10.1016/j.csda.2012.11.013_br000165
  doi: 10.1007/s11222-012-9314-z
– volume: 13
  start-page: 183
  issue: 1
  year: 2004
  ident: 10.1016/j.csda.2012.11.013_br000085
  article-title: Bayesian P-splines
  publication-title: Journal of Computational and Graphical Statistics
  doi: 10.1198/1061860043010
– volume: 62
  start-page: 1025
  issue: 4
  year: 2006
  ident: 10.1016/j.csda.2012.11.013_br000155
  article-title: Low-rank scale-invariant tensor product smooths for generalized additive mixed models
  publication-title: Biometrics
  doi: 10.1111/j.1541-0420.2006.00574.x
– volume: 11
  start-page: 89
  year: 1996
  ident: 10.1016/j.csda.2012.11.013_br000060
  article-title: Flexible smoothing with B-splines and penalties
  publication-title: Statistical Science
  doi: 10.1214/ss/1038425655
– volume: 52
  start-page: 3283
  issue: 7
  year: 2008
  ident: 10.1016/j.csda.2012.11.013_br000130
  article-title: Size and power of tests for a zero random effect variance or polynomial regression in additive and linear mixed models
  publication-title: Computational Statistics and Data Analysis
  doi: 10.1016/j.csda.2007.10.022
– year: 1990
  ident: 10.1016/j.csda.2012.11.013_br000145
– volume: 53
  start-page: 61
  issue: 1
  year: 2008
  ident: 10.1016/j.csda.2012.11.013_br000010
  article-title: Simultaneous selection of variables and smoothing parameters in structured additive regression models
  publication-title: Computational Statistics and Data Analysis
  doi: 10.1016/j.csda.2008.05.032
– volume: 60
  start-page: 255
  year: 1973
  ident: 10.1016/j.csda.2012.11.013_br000005
  article-title: Maximum likelihood identification of gaussian autoregressive moving average models
  publication-title: Biometrika
  doi: 10.1093/biomet/60.2.255
– volume: vol. 30
  year: 1998
  ident: 10.1016/j.csda.2012.11.013_br000030
– year: 1990
  ident: 10.1016/j.csda.2012.11.013_br000075
– year: 2000
  ident: 10.1016/j.csda.2012.11.013_br000110
– volume: 50
  start-page: 61
  issue: 1
  year: 2006
  ident: 10.1016/j.csda.2012.11.013_br000055
  article-title: Fast and compact smoothing on large multidimensional grids
  publication-title: Computational Statistics and Data Analysis
  doi: 10.1016/j.csda.2004.07.008
– volume: 71
  start-page: 505
  issue: 2
  year: 2009
  ident: 10.1016/j.csda.2012.11.013_br000115
  article-title: Smoothing parameter selection for a class of semiparametric linear models
  publication-title: Journal of the Royal Statistical Society: Series B
  doi: 10.1111/j.1467-9868.2008.00695.x
– volume: 11
  start-page: 758
  issue: 4
  year: 2002
  ident: 10.1016/j.csda.2012.11.013_br000065
  article-title: Generalized linear additive smooth structures
  publication-title: Journal of Computational and Graphical Statistics
  doi: 10.1198/106186002844
– volume: 4
  start-page: 279
  issue: 4
  year: 2004
  ident: 10.1016/j.csda.2012.11.013_br000040
  article-title: Smoothing and forecasting mortality rates
  publication-title: Statistical Modelling
  doi: 10.1191/1471082X04st080oa
– ident: 10.1016/j.csda.2012.11.013_br000095
  doi: 10.1177/1471082X1001100104
– volume: 17
  start-page: 453
  year: 1989
  ident: 10.1016/j.csda.2012.11.013_br000025
  article-title: Linear smoothers and additive models (with discussion)
  publication-title: The Annals of Statistics
– year: 1961
  ident: 10.1016/j.csda.2012.11.013_br000050
– ident: 10.1016/j.csda.2012.11.013_br000090
– year: 1997
  ident: 10.1016/j.csda.2012.11.013_br000015
– year: 2003
  ident: 10.1016/j.csda.2012.11.013_br000120
– volume: 73
  start-page: 3
  year: 2011
  ident: 10.1016/j.csda.2012.11.013_br000160
  article-title: Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models
  publication-title: Journal of the Royal Statistical Society. Series B
  doi: 10.1111/j.1467-9868.2010.00749.x
– year: 1992
  ident: 10.1016/j.csda.2012.11.013_br000140
– volume: 78
  start-page: 719
  issue: 4
  year: 1991
  ident: 10.1016/j.csda.2012.11.013_br000125
  article-title: Estimation in generalized linear models with random effects
  publication-title: Biometrika
  doi: 10.1093/biomet/78.4.719
– volume: 6
  start-page: 461
  issue: 2
  year: 1978
  ident: 10.1016/j.csda.2012.11.013_br000135
  article-title: Estimating the dimension of a model
  publication-title: Annals of Statistics
  doi: 10.1214/aos/1176344136
– year: 2006
  ident: 10.1016/j.csda.2012.11.013_br000100
– volume: 88
  start-page: 9
  issue: 421
  year: 1993
  ident: 10.1016/j.csda.2012.11.013_br000020
  article-title: Aproximated inference in generalised linear mixed models
  publication-title: Journal of the American Statistical Association
  doi: 10.1080/01621459.1993.10594284
– volume: 55
  start-page: 757
  issue: 4
  year: 1993
  ident: 10.1016/j.csda.2012.11.013_br000080
  article-title: Varying-coefficient models
  publication-title: Journal of the Royal Statistical Society. Series B
  doi: 10.1111/j.2517-6161.1993.tb01939.x
– volume: 68
  start-page: 1
  year: 2006
  ident: 10.1016/j.csda.2012.11.013_br000045
  article-title: Generalized linear array models with applications to multidimensional smoothing
  publication-title: Journal of the Royal Statistical Society. Series B
  doi: 10.1111/j.1467-9868.2006.00543.x
– year: 2002
  ident: 10.1016/j.csda.2012.11.013_br000070
– volume: 55
  start-page: 473
  year: 1993
  ident: 10.1016/j.csda.2012.11.013_br000035
  article-title: Fitting multivariate regression functions by interaction spline models
  publication-title: Journal of the Royal Statistical Society. Series B
  doi: 10.1111/j.2517-6161.1993.tb01917.x
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Snippet Low-rank smoothing techniques have gained much popularity in non-standard regression modeling. In particular, penalized splines and tensor product smooths are...
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SubjectTerms algorithms
analysis of variance
computer software
data collection
Mixed models
Penalized splines
Schall’s algorithm
Smooth-ANOVA decomposition
statistical models
Title Efficient two-dimensional smoothing with P-spline ANOVA mixed models and nested bases
URI https://dx.doi.org/10.1016/j.csda.2012.11.013
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Volume 61
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