A test for linear versus convex regression function using shape-restricted regression

Biometrika

Volumn 90, Issue 1, 2003, Pages 223-232

  Meyer, Mary C ^a  

^a UNIVERSITY OF GEORGIA   (United States)

Author keywords

Convex regression; Effective dimension; Likelihood ratio test

Indexed keywords

EID: 3843089284     PISSN: 00063444     EISSN: None     Source Type: Journal    
DOI: 10.1093/biomet/90.1.223     Document Type: Article

References (7)

1. COHEN, A., KEMPERMAN, J. H. B. & SACROWITZ, H. B. (1993). Unbiased tests for normal order restricted hypotheses. J. Mult. Anal. 46, 139-53.
2. COHEN, A., SACROWITZ, H. B. & SAMUEL-CAHN, E. (1995). Constructing tests for normal order-restricted inference. Bernoulli 1, 321-33.
3. FRASER, D. A. S. & MASSAM, H. (1989). A mixed primal-dual bases algorithm for regression under inequality constraints. Application to convex regression. Scand. J. Statist. 16, 65-74.
4. MEYER, M. C. (1999). An extension of the mixed primal-dual bases algorithm to the case of more constraints than dimensions. J. Statist. Plan. Infer. 81, 13-31.
5. MEYER, M. & WOODROOFE, M. (2000). On the degrees of freedom in shape-restricted regression. Ann. Statist. 28, 1083-104.
6. RAUBERTAS, R. F., CHU-IN, C. L. & NORDHEIM, E. V. (1986). Hypotheses tests for normal means constrained by linear inequalities. Commun. Statist. 15, 2809-33.
7. ROBERTSON, T., WRIGHT, F. T. & DYKSTRA, R. L. (1988). Order Restricted Statistical Inference. New York: Wiley.