0000000001064261

AUTHOR

S. Valère Bitseki Penda

showing 2 related works from this author

A PHASE TRANSITION FOR LARGE VALUES OF BIFURCATING AUTOREGRESSIVE MODELS

2019

We describe the asymptotic behavior of the number $$Z_n[a_n,\infty )$$ of individuals with a large value in a stable bifurcating autoregressive process, where $$a_n\rightarrow \infty $$ . The study of the associated first moment is equivalent to the annealed large deviation problem of an autoregressive process in a random environment. The trajectorial behavior of $$Z_n[a_n,\infty )$$ is obtained by the study of the ancestral paths corresponding to the large deviation event together with the environment of the process. This study of large deviations of autoregressive processes in random environment is of independent interest and achieved first. The estimates for bifurcating autoregressive pr…

Statistics and Probability[MATH.MATH-PR] Mathematics [math]/Probability [math.PR]Phase transitionrandom environmentGeneral Mathematicsmedia_common.quotation_subjectmoderate deviationslimit-theoremsmarkov-chainsStatistics::Other StatisticsBranching processdeviation inequalities92D2501 natural sciencesAsymmetry010104 statistics & probability[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]Convergence (routing)[MATH.MATH-CO]Mathematics [math]/Combinatorics [math.CO]Applied mathematics60C05[MATH]Mathematics [math]0101 mathematicsautoregressive process60J20lawMathematicsBranching processmedia_commonEvent (probability theory)parametersconvergenceMarkov chain010102 general mathematics[MATH.MATH-CO] Mathematics [math]/Combinatorics [math.CO][MATH.MATH-PR]Mathematics [math]/Probability [math.PR]Large deviationslarge deviations Mathematics Subject Classification (2010): 60J8060K37Autoregressive modelcellsLarge deviations theoryStatistics Probability and Uncertaintyasymmetry60F10
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Local bandwidth selection for kernel density estimation in a bifurcating Markov chain model

2020

International audience; We propose an adaptive estimator for the stationary distribution of a bifurcating Markov Chain onRd. Bifurcating Markov chains (BMC for short) are a class of stochastic processes indexed by regular binary trees. A kernel estimator is proposed whose bandwidths are selected by a method inspired by the works of Goldenshluger and Lepski [(2011), 'Bandwidth Selection in Kernel Density Estimation: Oracle Inequalities and Adaptive Minimax Optimality',The Annals of Statistics3: 1608-1632). Drawing inspiration from dimension jump methods for model selection, we also provide an algorithm to select the best constant in the penalty. Finally, we investigate the performance of the…

Statistics and ProbabilityKernel density estimationadaptive estimationNonparametric kernel estimation01 natural sciences010104 statistics & probability[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]0502 economics and businessbinary treesApplied mathematicsbifurcating autoregressive processes0101 mathematics[MATH]Mathematics [math]050205 econometrics MathematicsBinary treeStationary distributionMarkov chainStochastic processModel selection05 social sciencesEstimator[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]Adaptive estimatorStatistics Probability and UncertaintyGoldenshluger-Lepski methodology
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