Archive for the ‘Fragments’ Category

About the Statomics Lab

2 April 2017 Leave a comment

The Complexity and Statistics Research Lab was called “The Statomics Lab” until 4 February 2017. The word statomics abbreviates statistical inference and computation in genomics. David Bickel launched the lab in June of 2007 at the Ottawa Institute of Systems Biology.

Categories: Fragments

Mathematical Reviews

1 November 2015 Leave a comment
Categories: Fragments

Meeting: information theory & statistics

22 July 2011 Leave a comment
Categories: Fragments

Local false discovery rate

31 January 2011 Leave a comment

Efron clearly explains important recent advances in estimating the local false discovery rate. He also contrasts the methodology with more conventional multiple comparison procedures.

Categories: Fragments

Bayesian posterior as approximate confidence

22 December 2010 Leave a comment
Categories: Fragments

Statomics on Web 2.0

11 December 2010 Leave a comment
Categories: Fragments

Was the loss function a mistake?

28 August 2010 Leave a comment

Laplace’s “introduction of a loss function proved to be a serious mistake, which came to hamper the development of an objective theory of statistical inference to the present day” (Hald, 2007, pp. 3-4).

Categories: Fragments

Fisherian alternatives to conventional statistics

22 August 2010 Leave a comment

Novel developments in statistics and information theory call for a reconsideration of important aspects of two of R. A. Fisher’s most controversial ideas: the fiducial argument and the direct use of the likelihood function. Some key features of observed confidence levels, the direct use of the likelihood function, and the minimum description length principle are summarized here:

  1. Like the fiducial distribution, a probability measure of observed confidence levels is in effect a posterior probability distribution of the parameter of interest that does not require any prior distribution. Derived from sets of confidence intervals, this probability distribution of a parameter of interest is traditionally known as a confidence distribution. When the parameter of interest is scalar, the observed confidence level of a composite hypothesis is equal to its fiducial probability. On the other hand, observed conference levels do not suffer from the difficulties of constructing a fiducial distribution of a vector parameter.
  2. The likelihood ratio serves not only as a tool for the construction of point estimators, p-values, confidence intervals, and posterior probabilities, but is also fruitfully interpreted as a measure of the strength of statistical evidence for one hypothesis over another through the lens of a family of distributions. Modern versions of Fisher’s evidential use of the likelihood overcome multiplicity problems that arise in standard frequentism without resorting to a prior distribution.
  3. A related approach is to select the family of distributions using a modern information-theoretic reinterpretation of the likelihood function. In particular, the minimum description length principle extends the scope of Fisherian likelihood inference to the challenging problem of model selection.
Categories: Fragments, MDL

Information Theoretic Methods

11 August 2010 Leave a comment
Categories: Fragments, MDL

New links

18 June 2010 Leave a comment
Categories: Fragments