Generalized Additive Models for Pair-Copula Constructions

Pair-copula constructions are flexible dependence models that use bivariate copulas as building blocks. In this article, we extend them with generalized additive models to allow covariates effects....

[1]  B. Gräler.  Modelling skewed spatial random fields through the spatial vine copula , 2014 .

[2]  S. Wood,et al.  Generalized additive models for large data sets , 2015 .

[3]  S. Wood.  Generalized Additive Models: An Introduction with R , 2006 .

[4]  Daniel B. Nelson.  CONDITIONAL HETEROSKEDASTICITY IN ASSET RETURNS: A NEW APPROACH , 1991 .

[5]  Irène Gijbels,et al.  Conditional copulas, association measures and their applications , 2011, Comput. Stat. Data Anal..

[6]  S. Wood.  Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models , 2011 .

[7]  Andrew J. Patton.  Applications of copula theory in financial econometrics , 2002 .

[8]  S. Wood.  Stable and Efficient Multiple Smoothing Parameter Estimation for Generalized Additive Models , 2004 .

[9]  Johannes Gehrke,et al.  Sparse Partially Linear Additive Models , 2014, ArXiv.

[10]  Claudia Czado,et al.  Noncanonical links in generalized linear models – when is the effort justified? , 2000 .

[11]  Simon N. Wood,et al.  Generalized Additive Models for Gigadata: Modeling the U.K. Black Smoke Network Daily Data , 2017 .

[12]  Claudia Czado,et al.  Spatial composite likelihood inference using local C-vines , 2014, J. Multivar. Anal..

[13]  H. Joe.  Asymptotic efficiency of the two-stage estimation method for copula-based models , 2005 .

[14]  Pavel Krupskii,et al.  Factor copula models for multivariate data , 2013, J. Multivar. Anal..

[15]  T. Hastie,et al.  Generalized Additive Model Selection , 2015, 1506.03850.

[16]  Pavel Krupskii,et al.  Structured factor copula models: Theory, inference and computation , 2015, J. Multivar. Anal..

[17]  Torsten Hothorn,et al.  Boosting additive models using component-wise P-Splines , 2008, Comput. Stat. Data Anal..

[18]  Claudia Czado,et al.  Evading the curse of dimensionality in nonparametric density estimation with simplified vine copulas , 2015, J. Multivar. Anal..

[19]  Simon N. Wood,et al.  A simple test for random effects in regression models , 2013 .

[20]  Christian Genest,et al.  Beyond simplified pair-copula constructions , 2012, J. Multivar. Anal..

[21]  Joel L. Horowitz,et al.  NONPARAMETRIC ESTIMATION OF A GENERALIZED ADDITIVE MODEL WITH AN UNKNOWN LINK FUNCTION , 2001 .

[22]  Ingrid Hobæk Haff,et al.  Parameter estimation for pair-copula constructions , 2013, 1303.4890.

[23]  Peter Buhlmann,et al.  BOOSTING ALGORITHMS: REGULARIZATION, PREDICTION AND MODEL FITTING , 2007, 0804.2752.

[24]  I. Gijbels,et al.  Estimation of a Conditional Copula and Association Measures , 2011 .

[25]  Ker-Chau Li,et al.  Regression Analysis Under Link Violation , 1989 .

[26]  R. Nelsen.  An Introduction to Copulas , 1998 .

[27]  R. Tibshirani,et al.  Generalized Additive Models , 1986 .

[28]  H. Joe.  Multivariate models and dependence concepts , 1998 .

[29]  Rosalba Radice,et al.  Copula regression spline models for binary outcomes , 2015, Statistics and Computing.

[30]  S. Wood,et al.  Smoothing Parameter and Model Selection for General Smooth Models , 2015, 1511.03864.

[31]  A. Gallant,et al.  On the bias in flexible functional forms and an essentially unbiased form : The fourier flexible form , 1981 .

[32]  Kjersti Aas,et al.  On the simplified pair-copula construction - Simply useful or too simplistic? , 2010, J. Multivar. Anal..

[33]  T. Bollerslev,et al.  Deutsche Mark–Dollar Volatility: Intraday Activity Patterns, Macroeconomic Announcements, and Longer Run Dependencies , 1998 .

[34]  Fabian Spanhel,et al.  The partial vine copula: A dependence measure and approximation based on the simplifying assumption , 2015, 1510.06971.

[35]  Fabian Spanhel,et al.  Simplified vine copula models: Approximations based on the simplifying assumption , 2015, Electronic Journal of Statistics.

[36]  Ashley Petersen,et al.  Fused Lasso Additive Model , 2014, Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America.

[37]  P. Bühlmann,et al.  Boosting With the L2 Loss , 2003 .

[38]  Gerhard Tutz,et al.  Boosting ridge regression , 2007, Comput. Stat. Data Anal..

[39]  Luis Garrote,et al.  A bivariate return period based on copulas for hydrologic dam design: accounting for reservoir routing in risk estimation , 2013 .

[40]  Robert F. Engle,et al.  Forecasting intraday volatility in the US equity market. Multiplicative component GARCH , 2012 .

[41]  B. Silverman,et al.  Nonparametric Regression and Generalized Linear Models: A roughness penalty approach , 1993 .

[42]  Claudia Czado,et al.  R‐vine models for spatial time series with an application to daily mean temperature , 2014, Biometrics.

[43]  S. Wood.  On p-values for smooth components of an extended generalized additive model , 2013 .

[44]  H. Joe,et al.  The Estimation Method of Inference Functions for Margins for Multivariate Models , 1996 .

[45]  B. Silverman,et al.  Nonparametric Regression and Generalized Linear Models: A roughness penalty approach , 1993 .

[46]  Radu V. Craiu,et al.  In mixed company: Bayesian inference for bivariate conditional copula models with discrete and continuous outcomes , 2012, J. Multivar. Anal..

[47]  Roger M. Cooke,et al.  Probability Density Decomposition for Conditionally Dependent Random Variables Modeled by Vines , 2001, Annals of Mathematics and Artificial Intelligence.

[48]  Wolfgang Härdle,et al.  Partially Linear Models , 2000 .

[49]  T. Bollerslev,et al.  Intraday periodicity and volatility persistence in financial markets , 1997 .

[50]  Radu V. Craiu,et al.  Additive Models for Conditional Copulas , 2014 .

[51]  Claudia Czado,et al.  Computational Statistics and Data Analysis Regime Switches in the Dependence Structure of Multidimensional Financial Data , 2022 .

[52]  Simon N Wood,et al.  A generalized Fellner‐Schall method for smoothing parameter optimization with application to Tweedie location, scale and shape models , 2016, Biometrics.

[53]  Peter Craven,et al.  Smoothing noisy data with spline functions , 1978 .

[54]  Thibault Vatter,et al.  Generalized additive models for conditional dependence structures , 2015, J. Multivar. Anal..

[55]  Claudia Czado,et al.  Simplified pair copula constructions - Limitations and extensions , 2013, J. Multivar. Anal..

[56]  M. Sklar.  Fonctions de repartition a n dimensions et leurs marges , 1959 .

[57]  A. Frigessi,et al.  Pair-copula constructions of multiple dependence , 2009 .

[58]  W. Newey,et al.  Large sample estimation and hypothesis testing , 1986 .

[59]  S. Wood,et al.  Coverage Properties of Confidence Intervals for Generalized Additive Model Components , 2012 .

[60]  Claudia Czado,et al.  Pair-Copula Constructions of Multivariate Copulas , 2010 .

[61]  Nadja Klein,et al.  Simultaneous inference in structured additive conditional copula regression models: a unifying Bayesian approach , 2016, Stat. Comput..

[62]  Radu V. Craiu,et al.  Dependence Calibration in Conditional Copulas: A Nonparametric Approach , 2011, Biometrics.

[63]  Rosalba Radice,et al.  Bivariate copula additive models for location, scale and shape , 2016, Comput. Stat. Data Anal..

[64]  Douglas Nychka,et al.  Bayesian Confidence Intervals for Smoothing Splines , 1988 .

[65]  T. Bedford,et al.  Vines: A new graphical model for dependent random variables , 2002 .

[66]  Alan Y. Chiang,et al.  Generalized Additive Models: An Introduction With R , 2007, Technometrics.

[67]  B. Yu,et al.  Boosting with the L 2-loss regression and classification , 2001 .