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Abstract
It is clear that the likelihood ratio statistics plays an important role in theories of asymptotical estimation and hypothesis testing. The aim of the paper is to investigate the asymptotic properties of likelihood ratio statistics in competing risks model with informative random censorship from both sides. We prove the approximation version of the locally asymptotically normality of the likelihood ratio statistics. The results have asymptotic representation of the likelihood ratio statistics using the strong approximation method where local asymptotic normality is obtained as a consequence.
Keywords
likelihood ratio statistics
competing risks model
locally asymptotically normality
random censoring
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How to Cite
Abdushukurov, A. A., & Nurmuhamedova, N. S. (2016). Approximation of the likelihood ratio statistics in competing risks model under informative random censorship from both sides. Pakistan Journal of Statistics and Operation Research, 12(1), 155-164. https://doi.org/10.18187/pjsor.v12i1.677
