AndrewsD. F. (1971), “Significance Tests Based on Residuals,”Biometrika, 58, 139–48.
2.
AndrewsD. F., and PregibonD. (1978), “Finding the Outliers That Matter,”Journal of the Royal Statistical Society, B-40, 85–93.
3.
AnscombeF. J. (1960), “Rejection of Outliers,”Technometrics2, 123–47.
4.
AnscombeF. J. (1961), “Examination of Residuals,”Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, 1, 1–36.
5.
AnscombeF. J. (1973), “Graphs in Statistical Analysis,”The American Statistician, 27, 17–22.
6.
AnscombeF. J., and TukeyJ. W. (1963), “The Examination of Residuals,”Technometrics, 5, 141–160.
7.
BardY. (1974), Nonlinear Parameter Estimation.New York: Academic Press.
8.
BatsellR. (1980), “Reviewof Introduction to Mathematical Modeling,” Journal of Marketing Research, 17(May), 272–3.
9.
BellmanR., and RothR. (1969), “Curve Fitting by Segmented Straight Lines,”Journal of the American Statistical Association, 64, 1079–84.
10.
CookR. D. (1977), “Detection of Influential Observations in Linear Regression,”Technometrics, 19, 15–18.
11.
CookR. D. (1979), “Influential Observations in Linear Regression,”Journal of the American Statistical Association, 74, 169–74.
12.
CoxD. R., and SnellE. J. (1974), “The Choice of Variables in Observational Studies,”Applied Statistics, 23, 51–9.
13.
DanielC., and WoodF. S. (1980), Fitting Equations to Data.New York: John Wiley & Sons, Inc.
14.
DraperN. R., and JohnJ. A. (1981), “Influential Observations and Outliers in Regression,”Technometrics, 23, 21–6.
15.
FarrarD. E., and GlauberR. R. (1967), “Multicollinearity in Regression Analysis: The Problem Revisited,”Review of Economics and Statistics, 49, 92–107.
16.
FederP. I. (1975), “On Asymptotic Distribution Theory in Segmented Regression Problems—Identified Case,”Technometrics, 16, 287–99.
17.
FurnivalG. M., and WilsonR. W. (1974), “Regression by Leaps and Bounds,”Technometrics, 16, 499–512.
18.
GarsideM. J. (1971), “Some Computational Procedures for the Best Subset Problem,”Applied Statistics, 20, 8–15.
19.
GoldfeldS. M., and QuandtR. E. (1972), Nonlinear Methods in Economics.Amsterdam: North-Holland.
20.
GraybillF. (1976), Theory and Application of the Linear Model.North Scituate, MA: Duxbury Press.
21.
GreenP. E. (1978), Analyzing Multivariate Data.Hinsdale, IL: The Dryden Press.
22.
GreenbergE. (1975), “Minimum Variance Properties of Principal Component Regression,”Journal of the American Statistical Association, 70, 194–7.
23.
HartleyH. O., and JayatillakeK. S. E. (1973), “Estimation for Linear Models with Unequal Variances,”Journal of the American Statistical Association, 68, 189–92.
24.
HawkinsD. M. (1973), “On the Investigation of Alternative Regressions by Principal Component Analysis,”Applied Statistics, 22, 275–86.
25.
HoerlA. E., and KennardR. W. (1970), “Ridge Regression: Applications to Non-Orthogonal Problems,”Technometrics, 12, 55–67.
26.
HudsonD. J. (1966), “Fitting Segmented Curves Whose Joint Points Have to be Estimated,”Journal of the American Statistical Association, 61, 1097–129.
27.
LaMotteL. R. (1972), “The SELECT Routines: A Program for Identifying Best Subset Regression,”Applied Statistics, 21, 92–3.
28.
LundI. A. (1971), “An Application of Stagewise and Stepwise Regression Procedures to a Problem of Estimating Precipitation in California,”Journal of Applied Meteorology, 10, 892–902.
29.
MahajanV., and JainA. K., and BergierM. (1977), “Parameter Estimation in Marketing Models in the Presence of Multicollinearity: An Application of Ridge Regression,”Journal of Marketing Research, 14(November), 586–91.
30.
MallowsC. L. (1973), “Some Comments on Cp,”Technometrics, 15, 661–75.
31.
MantelN. (1970), “Why Stepdown Procedures in Variable Selection,”Technometrics, 12, 621–5.
32.
McGeeV. E., and CarletonW. T. (1970), “Piecewise Regression,”Journal of the American Statistical Association, 65, 1109–24.
33.
MendenhallW. (1968), Introduction to Linear Models and the Design and Analysis of Experiments.Belmont, CA.: Wads worth Publishing Co., Inc.
34.
NeterJ., and WassermanW. (1974), Applied Linear Statistical Models.Homewood, IL.: Richard D. Irwin, Inc.
35.
SearleS. (1971), Linear Models.New York: John Wiley & Sons, Inc.