A Czech mathematician who worked in theoretical and nonparametric statistics.
He contributed notably to these areas of statistics:
- Nonparametric statistics: Hájek made major contributions to rank tests, especially their asymptotic theory and efficiency.
- Survey sampling: He helped build the theory of finite-population sampling, including unequal-probability methods and estimation using auxiliary information.
- Asymptotic statistical theory: He contributed fundamental results on efficient estimation, including work behind the Hájek convolution theorem and local asymptotic minimax theory.
Hájek’s legacy lies in rank-based nonparametric inference, survey sampling, and asymptotic efficiency theory. His influence is still visible in names such as the Hájek predictor/estimator, Hájek-Rényi inequality, and the Hájek–Le Cam convolution theorem.
