Baxter’s inequality and sieve bootstrap for random fields. (English) Zbl 1412.62127

Meyer, Marco; Jentsch, Carsten; Kreiss, Jens-Peter

Bernoulli 23, No. 4B, 2988-3020 (2017).

The paper is concerned with the evaluation of confidence in the use of sieve bootstrap in autoregression. Due to the importance of stationary spatial processes the importance of such research is remarkable. The authors developed a weighted Baxter-inequality for spatial processes that seems to have a good speed of convergence. The authors claim that the proposal has a better behavior than other bootstrap methods using simulation studies.

Reviewer: Carlos Narciso Bouza Herrera (Habana)

MSC:

62M40	Random fields; image analysis
62G09	Nonparametric statistical resampling methods
62M10	Time series, auto-correlation, regression, etc. in statistics (GARCH)
62M30	Inference from spatial processes

Keywords:

autoregression; bootstrap; random fields; Baxter’s inequality; sieve; resampling