A survey of recent research in burn-in is undertaken. The emphasis is on mixture models, criteria for optimal burn-in and burn-in at the component or system level.

Stochastically changing covariates may influence survival. They may be observed, unobserved or partly observed. We review the properties of hazard models explicitly representing the effects of unobserved, and partially observed, stochastic covariates. Such models will increase in importance as new longitudinal population studies, and longitudinal surveys of high dimensional failure processes in humans, become available--many are now in progress. It is shown that marginal survival distributions and likelihoods generated in analytically closed form make such parametrically detailed models computationally tractable. Several ways of defining the marginal distribution of the data for constructing a likelihood function are considered. The most complete models can handle both continuously and discretely evolving covariates. Parameters can be estimated from multiple data sets to retrospectively and prospectively evaluate covariate trajectories. Such methods will both extract more information from a longitudinal study and use it in a parametric structure that is logically consistent with the behavior of the underlying processes of substantive interest.

Three papers from the early history of efficient parametric estimation are reprinted with commentary: (1) Fisher (1912), "On an absolute criterion for fitting frequency curves"; (2) Engledow and Yule (1914), "The determination of the best value of the coupling-ratio from a given set of data"; and (3) Fisher (1922), "The systematic location of genes by means of crossover observations."

This is an account of the life of the author's book Testing Statistical Hypotheses, its genesis, philosophy, reception and publishing history. There is also some discussion of the position of hypothesis testing and the Neyman-Pearson theory in the wider context of statistical methodology and theory.

Harald Bergström was born on April 1, 1908, in Mölltorp, situated in the middle of Sweden. A Master of Philosophy degree was awarded in 1931 at the University of Uppsala (in mathematics, physics and chemistry, extended to theoretical physics in 1932). He taught in secondary schools (gymnasiums) from 1932 to 1934, and then returned to Uppsala to pursue his research in mathematics toward a doctorate degree, which he received in 1938. He had a permanent lectureship in mathematics at the University of Uppsala from 1938 to 1945, and at a military college in 1945. In 1946, he was asked to hold a new established professorship in applied mathematics at the Chalmers University of Technology in Gothenburg, where he became full Professor in 1949. In 1960, the professorship in applied mathematics was expanded to two professorships--one in numerical analysis and one in mathematical statistics; he occupied the latter until his retirement in 1974.

Sujit Kumar Mitra was born on January 23, 1932, in Calcutta, India. He earned his B.Sc. degree in statistics from Presidency College, Calcutta, in 1949, an M.Sc. degree in statistics from Calcutta University in 1951 and a Ph.D. degree in statistics from the University of North Carolina at Chapel Hill in 1956, under the guidance of Professor S. N. Roy. He has made pioneering contributions in many areas of statistics and mathematics--including survey sampling, linear models, design of experiments, goodness-of-fit tests and linear algebra. He has been particularly credited for path-breaking contributions in the area of generalized inverses of matrices, culminating in a jointly authored landmark book with Professor C. R. Rao (published in 1971). He was Professor at the Indian Statistical Institute (ISI), both in Calcutta and Delhi, for almost 40 years. He has held visiting positions at Indiana University, Purdue University, University of Texas at Dallas, and Keio University, Japan. He retired from ISI in January 1992 and is currently Professor Emeritus. Unfortunately, he contracted Parkinson's disease in 1978. Despite an uphill battle against constant physical discomfort, he has continued as a leading contributor in many directions of mathematics and statistics. He is well known for his zest in attacking and solving some of the most difficult problems in linear algebra. He has earned many awards, honors and titles, including Fellow of the Indian National Science Academy and of the Indian Academy of Science. He was also elected President of the Statistics Section of the Indian Science Congress in 1988. He has been associated with many journals, including Sankhyā, and has edited or coedited several special volumes.