Bayesian Networks for Max-Linear Models

[1]  S. Lauritzen,et al.  Identifiability and estimation of recursive max‐linear models , 2019, Scandinavian Journal of Statistics.

[2]  C. Kluppelberg,et al.  Semiparametric estimation for isotropic max-stable space-time processes , 2016, Bernoulli.

[3]  C. Kluppelberg,et al.  Max-linear models on directed acyclic graphs , 2015, Bernoulli.

[4]  Nadine Gissibl,et al.  Big Data: Progress in Automating Extreme Risk Analysis , 2017 .

[5]  S. Lauritzen,et al.  Unifying Markov properties for graphical models , 2016, The Annals of Statistics.

[6]  Johan Segers,et al.  A continuous updating weighted least squares estimator of tail dependence in high dimensions , 2016, Extremes.

[7]  Anthony C. Davison,et al.  Extremes on river networks , 2015, 1501.02663.

[8]  P. Spirtes,et al.  A uniformly consistent estimator of causal effects under the k-Triangle-Faithfulness assumption , 2014, 1502.00829.

[9]  J. Peters,et al.  Identifiability of Gaussian structural equation models with equal error variances , 2012, 1205.2536.

[10]  Peter Buhlmann,et al.  Geometry of the faithfulness assumption in causal inference , 2012, 1207.0547.

[11]  Anthony C. Davison,et al.  Statistical Modelling of Spatial Extremes , 2012 .

[12]  A. Davison,et al.  Statistical Modeling of Spatial Extremes , 2012, 1208.3378.

[13]  Claudia Kluppelberg,et al.  Statistical inference for max‐stable processes in space and time , 2012, 1204.5581.

[14]  Raphael Huser,et al.  Space–time modelling of extreme events , 2012, 1201.3245.

[15]  Yizao Wang,et al.  Conditional sampling for spectrally discrete max-stable random fields , 2010, Advances in Applied Probability.

[16]  P. Butkovic Max-linear Systems: Theory and Algorithms , 2010 .

[17]  S. Resnick Heavy-Tail Phenomena: Probabilistic and Statistical Modeling , 2006 .

[18]  J. Hoef,et al.  Spatial statistical models that use flow and stream distance , 2006, Environmental and Ecological Statistics.

[19]  Aapo Hyvärinen,et al.  A Linear Non-Gaussian Acyclic Model for Causal Discovery , 2006, J. Mach. Learn. Res..

[20]  L. Haan,et al.  Extreme value theory , 2006 .

[21]  L. Haan,et al.  Extreme value theory : an introduction , 2006 .

[22]  J. Teugels,et al.  Statistics of Extremes , 2004 .

[23]  Holger Rootzén,et al.  Extreme Values in Finance, Telecommunications, and the Environment , 2003 .

[24]  T. Richardson Markov Properties for Acyclic Directed Mixed Graphs , 2003 .

[25]  Michael I. Jordan Graphical Models , 2003 .

[26]  C. Klüppelberg,et al.  Modelling Extremal Events , 1997 .

[27]  D. West Introduction to Graph Theory , 1995 .

[28]  Christopher Meek,et al.  Strong completeness and faithfulness in Bayesian networks , 1995, UAI.

[29]  PAUL EMBRECHTS,et al.  Modelling of extremal events in insurance and finance , 1994, Math. Methods Oper. Res..

[30]  P. Spirtes,et al.  Causation, prediction, and search , 1993 .

[31]  Steffen L. Lauritzen,et al.  Independence properties of directed markov fields , 1990, Networks.

[32]  Judea Pearl,et al.  Equivalence and Synthesis of Causal Models , 1990, UAI.

[33]  M. Frydenberg The chain graph Markov property , 1990 .

[34]  Sidney I. Resnick,et al.  Basic properties and prediction of max-ARMA processes , 1989, Advances in Applied Probability.

[35]  R. P. McDonald,et al.  Structural Equations with Latent Variables , 1989 .

[36]  S. Resnick Extreme Values, Regular Variation, and Point Processes , 1987 .

[37]  R. Gill Non- and semi-parametric maximum likelihood estimators and the Von Mises method , 1986 .

[38]  A. Dawid Conditional Independence for Statistical Operations , 1980 .

[39]  F. W. Scholz,et al.  Towards a unified definition of maximum likelihood , 1980 .

[40]  Søren Johansen,et al.  The product limit estimator as maximum likelihood estimator , 1978 .

[41]  J. Kiefer,et al.  CONSISTENCY OF THE MAXIMUM LIKELIHOOD ESTIMATOR IN THE PRESENCE OF INFINITELY MANY INCIDENTAL PARAMETERS , 1956 .