In Memory of Professor Kesar Singh
Article first published online: 1 APR 2013
© 2013 The Authors. International Statistical Review © 2013 International Statistical Institute
International Statistical Review
Volume 81, Issue 1, page 2, April 2013
How to Cite
Liu, R. and Xie, M.-g. (2013), In Memory of Professor Kesar Singh. International Statistical Review, 81: 2. doi: 10.1111/insr.12013
- Issue published online: 1 APR 2013
- Article first published online: 1 APR 2013
Kesar Singh, a beloved colleague, friend, teacher, extraordinary researcher and statistician, left us forever, and far too soon, on Wednesday May 16, 2012.
Kesar was born on June 20, 1955, in Varanasi, India. He got his B.Sc. degree in 1973 from Allahabad University and Ph.D. degree in 1979 from the Indian Statistical Institute (ISI), Kolkata, with Jogesh Babu as his advisor. Kesar was considered exceptionally brilliant by his teachers and fellow students at ISI. He was awarded a Ford Foundation Fellowship in 1979 to join the Stanford Statistics Department as a post-doc. It was around that time that Brad Efron from Stanford introduced the bootstrap method. Many statisticians were racing to provide a theoretical justification for bootstrap. Kesar, as a fresh Ph.D. holder, was the first to show that the bootstrap approximation is superior to that derived from the Central Limit Theorem for the distribution of the sample mean of i.i.d. random variables from a non-lattice distribution. This landmark result and his subsequent seminal work in many statistics areas, including resampling, data depth and confidence distributions, made Kesar a world-renowned statistician.
Kesar was a brilliant scholar and a beloved teacher. His knowledge of statistics was deep and extensive. His willingness to share his gifts was always present. He published almost 100 papers and supervised 10 Ph.D. students. He was elected a Fellow of Institute of Mathematical Statistics and a Member of International Statistical Institute. Kesar will be greatly missed for his enormous intellect, as well as his generosity and gentleness.