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Symmetry and Unimodality in Linear Inference


  • Jensen, D. R.


Distribution-free results beyond Gauss-Markov theory are found under weak assumptions regarding the errors. Symmetry, unimodality, and location-scale families are studied in estimation; nonstandard versions of Gauss-Markov results are given; and distribution-free confidence sets are tightened under symmetry and unimodality of errors. Normal-theory approximate tests are seen to exhibit monotone power in certain classes of symmetric unimodal errors.

Suggested Citation

  • Jensen, D. R., 1997. "Symmetry and Unimodality in Linear Inference," Journal of Multivariate Analysis, Elsevier, vol. 60(2), pages 188-202, February.
  • Handle: RePEc:eee:jmvana:v:60:y:1997:i:2:p:188-202

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    Cited by:

    1. Jensen, D.R. & Ramirez, D.E., 2009. "Concentration reversals in ridge regression," Statistics & Probability Letters, Elsevier, vol. 79(21), pages 2237-2241, November.


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