scholarly journals Correlation bounds, mixing and m-dependence under random time-varying network distances with an application to Cox-processes

Bernoulli ◽  
2021 ◽  
Vol 27 (3) ◽  
Author(s):  
Alexander Kreiß
Keyword(s):  
Random Time ◽  
Time Varying ◽  
Cox Processes

scholarly journals Universal Statistics of Waves in a Random Time-Varying Medium

2021 ◽  
Vol 127 (9) ◽  
Author(s):  
R. Carminati ◽  
H. Chen ◽  
R. Pierrat ◽  
B. Shapiro
Keyword(s):  
Random Time ◽  
Time Varying ◽  
Time Varying Medium

scholarly journals NONPARAMETRIC IDENTIFICATION OF THE MIXED HAZARD MODEL USING MARTINGALE-BASED MOMENTS

2019 ◽  
Vol 36 (2) ◽  
pp. 331-346
Author(s):  
Johannes Ruf ◽  
James Lewis Wolter
Keyword(s):  
Hazard Function ◽  
Hazard Model ◽  
Random Time ◽  
Nonparametric Identification ◽  
Model Parameters ◽  
Time Varying ◽  
Moment Conditions ◽  
True Model ◽  
Incorrect Model ◽  
Path Structure

Nonparametric identification of the Mixed Hazard model is shown. The setup allows for covariates that are random, time-varying, satisfy a rich path structure and are censored by events. For each set of model parameters, an observed process is constructed. The process corresponding to the true model parameters is a martingale, the ones corresponding to incorrect model parameters are not. The unique martingale structure yields a family of moment conditions that only the true parameters can satisfy. These moments identify the model and suggest a GMM estimation approach. The moments do not require use of the hazard function.

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