Kernel estimation of the transition density in bifurcating Markov chains - Archive ouverte HAL
Article Dans Une Revue Journal of Statistical Planning and Inference Année : 2024

Kernel estimation of the transition density in bifurcating Markov chains

Résumé

We study the kernel estimators of the transition density of bifurcating Markov chains. Under some ergodic and regularity properties, we prove that these estimators are consistent and asymptotically normal. Next, in the numerical studies, we propose two data-driven methods to choose the bandwidth parameters. These methods, based on the so-called two bandwidths approach, are adaptation for bifurcating Markov chains of the least squares Cross-Validation and the rule of thumb method. Finally, we provide an example with real data.
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Dates et versions

hal-04813920 , version 1 (02-12-2024)

Identifiants

Citer

S. Valère Bitseki Penda. Kernel estimation of the transition density in bifurcating Markov chains. Journal of Statistical Planning and Inference, 2024, 231, pp.106138. ⟨10.1016/j.jspi.2023.106138⟩. ⟨hal-04813920⟩
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