Testing goodness-of-fit for the distribution of errors in regression models. Technical report No. 16

Technical Report · Thu Jun 08 00:00:00 EDT 1978

OSTI ID:6532594

Pierce, D A; Kopecky, K J

Asymptotic results are given for the problem of testing goodness-of-fit for any specified distribution of errors in multiple regression models. In particular, the results apply to the case of testing for normality in standard regression and experimental design models. For a very wide class of goodness-of-fit statistics, in particular those which depend only on the empirical distribution of the residuals, it is shown that the limiting distributions under the null hypothesis are precisely the same in regression models as in ordinary location-scale models. 10 references.

• Research Organization: Stanford Univ., CA (USA). Dept. of Statistics
• OSTI ID: 6532594
• Report Number(s): COO-2974-36
• Country of Publication: United States
• Language: English

Related Subjects

658000* -- Mathematical Physics-- (-1987)
71 CLASSICAL AND QUANTUM MECHANICS
GENERAL PHYSICS
ASYMPTOTIC SOLUTIONS
BOUNDARY CONDITIONS
DESIGN
DISTRIBUTION
ERRORS
LEAST SQUARE FIT
MATHEMATICS
MAXIMUM-LIKELIHOOD FIT
NUMERICAL SOLUTION
STATISTICS