Draft:Iman-Conover method

  • Comment: One of the two sources are from the people who made the method. Is there any coverage on the method itself? Tavantius (talk) 14:08, 6 November 2024 (UTC)

The Iman-Conover (IC) method or transformation is a statistical method for generating a sample with a specified rank-correlation.[1]

Description of full method

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The IC method takes as input a set of data and a target correlation matrix. The method works by rearranging the data to achieve a rank correlation close to the target correlation matrix.

Let   be a data matrix and let   be a target rank-correlation matrix. the IC method rearranges the rows of   to form a new data matrix   with rank correlation close to  .

The method works as follows:

  1. Create normal scores,   from  
  2. Uncorrelate the scores, define these as  
  3. Transform   to match the correlation matrix  , for example by the Cholesky decomposition, define these as  
  4. Reorder the elements of   to match the ordering from  

Strong uniform consistency of the estimated sum distribution function is prooved[2].

A simpler version involves simulating directly from a specified copula and using the resulting output to reorder as in step 4 above.

References

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  1. ^ Iman, Ronald L.; Conover, W. J. (Jan 1981). "A distribution-free approach to inducing rank correlation among input variables". Communications in Statistics - Simulation and Computation. 11 (3). Taylor & Francis: 311–334. doi:10.1080/03610918208812265.
  2. ^ Mainik, Georg (2015). "Risk aggregation with empirical margins: Latin hypercubes, empirical copulas, and convergence of sum distributions". Journal of Multivariate Analysis. 141. Elsevier: 197–216. doi:10.1016/j.jmva.2015.07.008.