Banerjee, Moulinath; Sen, Bodhisattva [Woodroofe, Michael] A conversation with Michael Woodroofe. (English) Zbl 1442.01014 Stat. Sci. 31, No. 3, 433-441 (2016). MSC: 01A70 Biographies, obituaries, personalia, bibliographies Keywords:biased sampling; nonlinear renewal theory; sequential analysis; shape-restricted inference; statistics in astronomy Biographic References: Woodroofe, Michael × Cite Format Result Cite Review PDF Full Text: DOI Euclid References: [1] Groeneboom, P. (1985). Estimating a monotone density. In Proceedings of the Berkeley Conference in Honor of Jerzy Neyman and Jack Kiefer, Vol. II (Berkeley, Calif., 1983). Wadsworth Statist./Probab. Ser. 539-555. Wadsworth, Belmont, CA. · Zbl 1373.62144 [2] Hill, B. M. and Woodroofe, M. (1975). Stronger forms of Zipf’s law. J. Amer. Statist. Assoc.70 212-219. · Zbl 0326.92014 · doi:10.1080/01621459.1975.10480291 [3] Maxwell, M. and Woodroofe, M. (2000). Central limit theorems for additive functionals of Markov chains. Ann. Probab.28 713-724. · Zbl 1044.60014 · doi:10.1214/aop/1019160258 [4] Parzen, E. (1962). On estimation of a probability density function and mode. Ann. Math. Statist.33 1065-1076. · Zbl 0116.11302 · doi:10.1214/aoms/1177704472 [5] Woodroofe, M. (1985). Estimating a distribution function with truncated data. Ann. Statist.13 163-177. · Zbl 0574.62040 · doi:10.1214/aos/1176346584 [6] Woodroofe, M. (1992). A central limit theorem for functions of a Markov chain with applications to shifts. Stochastic Process. Appl.41 33-44. · Zbl 0762.60023 · doi:10.1016/0304-4149(92)90145-G [7] Woodroofe, M. and Hill, B. (1975). On Zipf’s law. J. Appl. Probab.12 425-434. · Zbl 0343.60012 · doi:10.1017/S0021900200048233 This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.