If I could afford a
diamond-encrusted platinum bowl to award to the best Bayesian
researcher of all time, then my candidates would include Rudolf
Kálmán, Michael Newton, Peter Wakker, Subhashis Ghoshal, David
Dunson and Timothy Wallstrom. So I’d probably fill it with the
Elixir of Life, and invite them to all take a sip.
I’d give Susie Bayarri,
Grace Wahba, Sylvia Richardson, Nicky Best, and Sara Martino my
silver Scottish quaich, and fill it with Jura.
Every discipline needs
its Purveyors of the Word, prominent, extrovert figures who
are prepared to stand on a pedestal and project its concepts and
ideas across other disciplines, throughout Society, and around the
world, at the risk of appearing to be peering down their noses at
the children on the pavement.
St. Paul of Tarsus, the
thirteenth Apostle, though maybe a phoney one since he only ever met
the Son of God in a vision on the road to Damascus, purveyed his
assimilations of the Word of Christ outside Palestine and throughout
the Roman Empire.
George Tiao, Carlos
Pereira, Pilar Iglesias, and Jose Bernardo popularised Bayesian
concepts in the Far East, Brazil, Chile and Spain in somewhat
sounder and more convincing ways. P. Jeffrey Harrison and his merry
band purveyed the wonderful advantages of Kalman-style forecasting
around the world, albeit in at times quasi-intellectual and ‘Back to
the Future’ fashion.
In America, the key
Purveyors of the Word included Jimmie Savage, Arnold Zellner, Jay
Kadane and Rob Kass, and the quintessence of Yankee and alien
immigrant academia. In Britain they included Richard Price, Jack
Good, Dennis Lindley, and Sir Adrian Smith, and represented all the
extremities and idiosyncrasies of this class-conscious Sceptred
Unfortunately, St. Paul
sometimes got it wrong. He, for example, distorted the
representation in Matthew 25 of the Second Coming, and emphasised
faith in Christ, rather than good deeds, much more than James the
Less, or our good Lord, who was recognised in the Qur’an as the
earthly Prophet Isa, would have ever dreamt of.
The purveyors of the
Bayesian cause have sometimes got it wrong too. When a ‘child on the
sidewalk’ once inquired about the frequency coverage of his 95%
Bayesian interval, Arnold replied to the effect that he didn’t given
a toss. As a Nobel Prize nominee, he doubtlessly felt entitled. And
Jay Kadane still overemphasises the importance of the Expected
Utility Hypothesis, as ever faithful to the memory of Jimmie Savage
despite his Lord and Master’s long-time battering over his stern
adherence to the glaringly fallacious Sure Thing Principle and his
over-formalisation of the key conceptual ideas of utility of the
eighteenth century Swiss mathematician Daniel Bernoulli, which were
published in St. Petersburg in 1738.
Sir Adrian Smith got it
triumphantly right, with Alan Gelfand, when he popularised MCMC
during the 1990s, and he blinked in joy when the simulations
In response to MCMC and
the early 21 st. century development by two proud men and two bright
women of the model comparison criterion DIC, a pragmatic rather than
a quasi-religious view of Bayesianism has emerged. Bayes theorem and
DIC are nowadays regarded as useful parts of many statisticians’
toolkits. But they’re not the be all and end all, in particular in
situations where the choice of sampling model is unclear.
Sir Adrian has more
recently taken the concepts of evidence-based medicine and
evidence-based performance indicators into the widely-influential
area of evidence-based public policy making. But beware poorly
collected or skilfully reshuffled data, out of your Department of
Health or youth crime statistics or wherever, lest the conclusions
be spuriously evidence-based. Maybe the Prophet Isa is watching us,
as the ultimate ripple from above. According to my Moslem friends,
he will return in mortal form before the Final Day to judge us.
In Britain, the Rising
of the Bayesian Paradigm, like a phoenix from the ashes, began at
Bletchley Park and the Universities of Manchester and Cambridge
during the 1940s and 50s, continued in Aberystwyth during the 1960s,
and led to a brilliant resurgence at University College London which
almost flew out of control. In the 1970s, the now multi-lingual
Bayesians at the University of Warwick took up the cudgel while
reportedly experiencing a group psychosis and they currently lead
the rest of Europe in preserving the Word and the Force.
The development of
Bayesianism in the United States was subjected to some not
inconsiderable post-birth traumas during the McCarthy era.
But the paradigm soared
majestically , on the wings of seagulls and eagles, towards its
Seventh Heaven at the Harvard and Chicago Business Schools, and
notably at Carnegie-Mellon, aided and abetted by the adventurous
‘Jonathan Livingston Seagulls’ in Wisconsin and the small
all-Bayesian team at Duke. Nowadays, Bayes is alive and kicking in
every God-damned state in the USA, and in almost every country
around the globe.
International Society for Bayesian Analysis has enhanced the links
to other disciplines with a plethora of electronic communications.
And new, at times highly eminent, scientific and socio-economic
Bayesians are springing out of the woodwork from all directions.
generalisations of the conditional Laplacian approximations of the
1980s have now been well computer-packaged in INLA by Håvard Rue and
his colleagues, and they provide extremely valid alternatives, in a
great many situations, to the wild and woolly ramifications of MCMC,
MMCMC, Particle MCMC, reversible jump MCMC, arty smarty crafty MCMC
and so on and so forth.
The pendulum has already
swung, as various high quality
applications of INLA begin to trickle in, and
some of the old theoretical arts of Bayesianism from the Halcyon
days are being restored.
Perhaps the pendulum
will swing even more, and maybe Le Marquis Pierre-Simon de Laplace
will have the last laugh. He was of course the guy way across the
Channel who had the cheek to develop the general forms of our
much-fêted Bayes-Price Theorem.
debilitating mote has nevertheless been cast into our eyes by the
gross misrepresentations and misuses of Bayes theorem in Courts of
Law, for example when evaluating DNA evidence, and these have
stained our profession for many years to come. If our cynical
Establishments do not put a quick end to them, the ancient Greek
Goddess Themis may perchance find it necessary to fry a token
forensic scientist or Bayes factorist or two on her scales of
As evidenced by the
material critiqued in my Ch. 7, the kaleidoscope of Bayesian
discovery has now fully blossomed into an enrichment of many areas
of science, medicine, and socio-economics. While the
practical advantages of the Bayesian contributions to Genomics and
Economics have yet to be completely clarified, the beneficial
influences in Medicine, the Environment, Social Progress, Artificial
Intelligence, and Machine Learning have been ginormous, to the point
where the creative research within some of these areas has itself