4 ms·

It sounds like they know certain assumptions regarding parameters that are not of interest are wrong. So why explicitly model those, if we don't care about thei

It sounds like they know certain assumptions regarding parameters that are not of interest are wrong. So why explicitly model those, if we don't care about their distribution? We (apparently) only care about an accurate estimate of W boson mass.

lazide 5y ago
Because it’s all interrelated and too many variables make it impossible to nail down anything with certainty if you don’t assume some invariants somewhere?
nabla9 5y ago
That works if the thing is something you can remove from the experiment and model separately, then put it back. In CERN many variables are tied to this one huge machine that is one of its kind.
- spekcular 5y ago
  I admit I'm not familiar with the model used to aggregate the boson data. But there's an entire community of nonparametric/semiparametric statisticians that works on problems just like this. It seems crazy to me that that millions of dollars are spent to build the machines to collect this data, yet the papers are written using statistical models with distributional/independence assumptions known to be false. (The tweet linked above seems to be saying something similar.) Is there a concrete reason we can't be naive and just bootstrap confidence intervals for example? Of course I defer to the physicists here – but I'm curious whether there's some simple high-level reason the usual tricks don't work.
  - nabla9 5y ago
    Don't worry. High energy physics has been at the bleeding edge of statistical methods forever.
    - spekcular 5y ago
      Sure, but I'm not talking about high energy physics in general, I'm talking about the estimates in this specific paper. Which the guy who is doing bleeding edge stuff seems a little suspicious of (see tweet). See also: https://twitter.com/pietrovischia/status/1512174848558219270 https://twitter.com/pietrovischia/status/1512174848558219270 This does not seems like bleeding edge, it seems like "Gaussian approximations for everything." In fact, this is the reference for the technique they used: https://cds.cern.ch/record/183996/files/OUNP-88-05.pdf https://cds.cern.ch/record/183996/files/OUNP-88-05.pdf. (Although the criticism seems to be leveled at the way they estimate the correlations, not that linear estimator specifically?)

lazide 5y ago

Because it’s all interrelated and too many variables make it impossible to nail down anything with certainty if you don’t assume some invariants somewhere?

nabla9 5y ago

That works if the thing is something you can remove from the experiment and model separately, then put it back. In CERN many variables are tied to this one huge machine that is one of its kind.

spekcular 5y ago
I admit I'm not familiar with the model used to aggregate the boson data. But there's an entire community of nonparametric/semiparametric statisticians that works on problems just like this. It seems crazy to me that that millions of dollars are spent to build the machines to collect this data, yet the papers are written using statistical models with distributional/independence assumptions known to be false. (The tweet linked above seems to be saying something similar.) Is there a concrete reason we can't be naive and just bootstrap confidence intervals for example? Of course I defer to the physicists here – but I'm curious whether there's some simple high-level reason the usual tricks don't work.
- nabla9 5y ago
  Don't worry. High energy physics has been at the bleeding edge of statistical methods forever.
  - spekcular 5y ago
    Sure, but I'm not talking about high energy physics in general, I'm talking about the estimates in this specific paper. Which the guy who is doing bleeding edge stuff seems a little suspicious of (see tweet). See also: https://twitter.com/pietrovischia/status/1512174848558219270 https://twitter.com/pietrovischia/status/1512174848558219270 This does not seems like bleeding edge, it seems like "Gaussian approximations for everything." In fact, this is the reference for the technique they used: https://cds.cern.ch/record/183996/files/OUNP-88-05.pdf https://cds.cern.ch/record/183996/files/OUNP-88-05.pdf. (Although the criticism seems to be leveled at the way they estimate the correlations, not that linear estimator specifically?)