ESTIMATION FOR THE PREDICTION OF POINT PROCESSES WITH MANY COVARIATES

DOI10.1017/S0266466617000172zbMath1390.62048arXiv1702.05315OpenAlexW3123713529MaRDI QIDQ4643224

Alessio Sancetta

Publication date: 24 May 2018

Published in: Econometric Theory (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1702.05315

zbMATH Keywords

point processnonparametric estimationcovariable

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Nonparametric estimation (62G05) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items (2)

State-dependent Hawkes processes and their application to limit order book modelling ⋮ ESTIMATION OF A HIGH-DIMENSIONAL COUNTING PROCESS WITHOUT PENALTY FOR HIGH-FREQUENCY EVENTS

Cites Work

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• Greedy algorithms for prediction
• Regularization for Cox's proportional hazards model with NP-dimensionality
• Statistics for high-dimensional data. Methods, theory and applications.
• Cox's regression model for counting processes: A large sample study
• The asymptotic behaviour of maximum likelihood estimators for stationary point processes
• Point processes and queues. Martingale dynamics
• Local likelihood and local partial likelihood in hazard regression
• Kernel estimation in a nonparametric marker dependent hazard model
• Exponential inequalities for martingales, with application to maximum likelihood estimation for counting processes
• High-dimensional additive hazards models and the lasso
• Approximation and learning by greedy algorithms
• Stability of nonlinear Hawkes processes
• Rate of convergence to equilibrium of marked Hawkes processes
• A NONPARAMETRIC ESTIMATOR FOR THE COVARIANCE FUNCTION OF FUNCTIONAL DATA
• Modelling Financial High Frequency Data Using Point Processes
• A cross-validatory method for dependent data
• Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data
• Stability Selection
• On Testing the Validity of Sequential Probability Forecasts
• SMOOTH TRANSITION AUTOREGRESSIVE MODELS — A SURVEY OF RECENT DEVELOPMENTS
• Sup-norm approximation bounds for networks through probabilistic methods
• Learning Theory and Kernel Machines

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