Bayesian Local Extremum Splines

Details

• Alternative Title:
  Biometrika
• Personal Author:
  WHEELER, M. W. ; DUNSON, D. B. ; HERRING, A. H.
• Description:
  We consider shape restricted nonparametric regression on a closed set [Formula: see text], where it is reasonable to assume the function has no more than | local extrema interior to [Formula: see text]. Following a Bayesian approach we develop a nonparametric prior over a novel class of local extremum splines. This approach is shown to be consistent when modeling any continuously differentiable function within the class considered, and is used to develop methods for testing hypotheses on the shape of the curve. Sampling algorithms are developed, and the method is applied in simulation studies and data examples where the shape of the curve is of interest.
• Subjects:
  Article Constrained Function Estimation Isotonic Regression Monotone Splines Nonparametric Shape Constraint
• Source:
  Biometrika. 104(4):939-952.
• Pubmed ID:
  29422695
• Pubmed Central ID:
  PMC5798493
• Document Type:
  Journal Article
• Funding:
  CC999999/Intramural CDC HHS/United States
• Volume:
  104
• Issue:
  4
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:de34ecb28763010eade3ccd488a3f7d486b648a54a4cd1b46b37f58cf052af81
• Download URL:
  https://stacks.cdc.gov/view/cdc/51822/cdc_51822_DS1.pdf
• File Type:
  [PDF - 912.59 KB ]