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164 Exciting times15.3.3 Joining the revolutionSo, this is how I came to statistics — by necessity, with employment in mindand having a distinct, persistently theoretical outlook. A paper on nonparametricdensity estimation by Eve Bofinger (1975), whom I’d met in 1974 whileI was an MSc student, drew a connection for me between the theory of orderstatistics and nonparametric function estimation, and gave me a start therein the late 1970s.I already had a strong interest in rates of convergence in the central limittheorem, and in distribution approximations. That gave me a way, in the1980s, of accessing theory for the bootstrap, which I found absolutely fascinating.All these methodologies — function estimation, particularly techniques forchoosing tuning parameters empirically, and of course the bootstrap — werepart of the “contemporary nonparametric” revolution in the 1970s and 1980s.It took off when it became possible to do the computation. I was excited tobe part of it, even if mainly on the theoretical side. In the early 1980s a seniorcolleague, convinced that in the future statistical science would be developedthrough computer experimentation, and that the days of theoretical work instatistics were numbered, advised me to discontinue my interests in theoryand focus instead on simulation. However, stubborn as usual, I ignored him.It is curious that the mathematical tools used to develop statistical theorywere regarded firmly as parts of probability theory in the 1970s, 80s and eventhe 90s, whereas today they are seen as statistical. For example, recent experienceserving on an IMS committee has taught me that methods built aroundempirical processes, which were at the heart of wondrous results in probabilityin the 1970s (see, e.g., Komlós et al., 1975, 1976), are today seen by more thanafewprobabilistsasdistinctlystatisticalcontributions.Convergenceratesinthe central limit theorem are viewed in the same light. Indeed, most resultsassociated with the central limit theorem seem today to be seen as statistical,rather than probabilistic. (So, I could have moved from probability tostatistics simply by standing still, while time washed over me!)This change of viewpoint parallels the “reinterpretation” of theory forspecial functions, which in the era of Whittaker and Watson (1902), and indeedalso of the more widely used fourth edition in 1927, was seen as theoreticalmathematics, but which, by the advent of Abramowitz and Stegun (1964)(planning for that volume had commenced as early as 1954), had migrated tothe realm of applied mathematics.Throughout all this work in nonparametric statistics, theoretical developmentwas my guide. Using it hand in hand with intuition I was able to gomuch further than I could have managed otherwise. This has always been myapproach — use theory to augment intuition, and allow them to work togetherto elucidate methodology.Function estimation in the 1970s and 1980s had, to a theoretician likemyself, a fascinating character. Today we can hardly conceive of constructing