Bayesian statistics
先生も書かれているようにMH370便の捜索は容易ではないようです。そこで登場したのが統計学。ただ今風の５％水準の話ではなく、古い手法のようです。
MH370 Malaysia plane: How maths helped find an earlier crash
Statisticians helped locate an Air France plane in 2011 which was missing for two years. Could mathematical techniques inspired by an 18th Century Presbyterian minister be used to locate the mysterious disappearance of Malaysia Airlines Flight MH370?
In June 2009, Air France flight 447 went missing flying from Rio de Janeiro in Brazil to Paris, France.
Debris from the Airbus A330 was found floating on the surface of the Atlantic five days later, but the mystery of why the plane crashed could only be answered by finding the black box and the cockpit voice recorder.
You may think that having found the debris it would be easy to find the rest of the plane, but it's not that simple - after a number of days, the material would have moved with the ocean current.
Software does exist that can simulate how the debris has travelled from the initial impact. It is used regularly by the US coast guard.
But in this case, because this area near the equator is known for unpredictable currents - particularly at that time of year - it was no help.
American, Brazilian and French ships, planes and submarines all searched for the plane, but they couldn't find it.
At this point France's aviation accident investigation authority, BEA, made a call to a group of statisticians in the US who had expertise in finding objects lost at sea.
Senior analyst Colleen Keller flew to France to help.
"The French BEA had already done a wonderful job of coming up with different theories for why the aircraft might have crashed," she says.
They also had lots of data about historical crashes and the results of the searches that had already been carried out.
To turn all this information into numbers and probability, Keller and her team from Metron Inc in Virginia, relied on Bayesian statistics named after a British Presbyterian minister called Thomas Bayes.
This type of thinking allows you to assess various scenarios at once - even contradictory ones. The probability of each being true is brought together to give you the most likely solution. And if you find new information, you can revise your model easily.
Keller and her colleagues went through all the available information and assessed the uncertainties of each piece of data - applying Bayesian principles of probability to work out the most likely location of the plane.
The team split up the search area into a grid, and applied to each cell a figure representing the probability that the plane would be found there.
http://www.bbc.com/news/magazine-26680633
今回の捜索で注目されているのが、Bayesian statistics「ベイズ/ベイジアン統計（学）」という手法だそうです。記事にもありますが、逆確率計算法を基礎にした統計学の体系の総称だそうです。詳しくは以下のサイトでどうぞ。（Ume）
