References - J

A B C D E F G H I J K L M N O P Q R S T U V W Y Z

Jaccard, J., Weber, J., & Lundmark, J. (1975). A multitrait-multimethod factor analysis of four attitude assessment procedures. Journal of Experimental Social Psychology, 11, 149-154.

Jacobs, D. A. H. (Ed.). (1977). The state of the art in numerical analysis. London: Academic Press.

Jacobs, R. A. (1988). Increased Rates of Convergence Through Learning Rate Adaptation. Neural Networks 1 (4), 295-307.

Jacoby, S. L. S., Kowalik, J. S., & Pizzo, J. T. (1972). Iterative methods for nonlinear optimization problems. Englewood Cliffs, NJ: Prentice-Hall.

Jambu, M. (1978). Classification automatique pour l'analyse des donnees. Dunod, Paris.

Jambu, M. (1991). Exploratory and multivariate data analysis. Academic Press. Orlando, FL.

James, L. R., Mulaik, S. A., & Brett, J. M. (1982). Causal analysis. Assumptions, models, and data. Beverly Hills, CA: Sage Publications.

Jardine, N., & Sibson, R. (1971). Mathematical taxonomy. New York: Wiley.

Jastrow, J. (1892). On the judgment of angles and position of lines. American Journal of Psychology, 5, 214-248.

Jenkins, G. M., & Watts, D. G. (1968). Spectral analysis and its applications. San Francisco: Holden-Day.

Jennrich, R. I. (1970). An asymptotic test for the equality of two correlation matrices. Journal of the American Statistical Association, 65, 904-912.

Jennrich, R. I. (1977). Stepwise regression. In K. Enslein, A. Ralston, & H.S. Wilf (Eds.), Statistical methods for digital computers. New York: Wiley.

Jennrich, R. I., & Moore, R. H. (1975). Maximum likelihood estimation by means of nonlinear least squares. Proceedings of the Statistical Computing Section, American Statistical Association, 57-65.

Jennrich, R. I., & Sampson, P. F. (1968). Application of stepwise regression to non-linear estimation. Technometrics, 10, 63-72.

Jennrich, R. I., & Sampson, P. F. (1976). Newton-Raphson and related algorithms for maximum likelihood variance component estimation. Technometrics, 18, 11-17.

Jennrich, R. I., & Schuchter, M. D. (1986). Unbalanced repeated-measures models with structured covariance matrices. Biometrics, 42, 805-820.

Jennrich. R. I. (1977). Stepwise discriminant analysis. In K. Enslein, A. Ralston, & H.S. Wilf (Eds.), Statistical methods for digital computers. New York: Wiley.

Johnson, L. W., & Ries, R. D. (1982). Numerical Analysis (2nd ed.). Reading, MA: Addison Wesley.

Johnson, N. L. (1961). A simple theoretical approach to cumulative sum control charts. Journal of the American Statistical Association, 56, 83-92.

Johnson, N. L. (1965). Tables to facilitate fitting SU frequency curves. Biometrika, 52, 547.

Johnson, N. L., & Kotz, S. (1970). Continuous univariate distributions, Vol I and II. New York: Wiley.

Johnson, N. L., Kotz, S., Balakrishnan, N. (1995). Continuous univariate distributions: Volume II. (2nd Ed). NY: Wiley.

Johnson, N. L., & Leone, F. C. (1962). Cumulative sum control charts - mathematical principles applied to their construction and use. Industrial Quality Control, 18, 15-21.

Johnson, N. L., Nixon, E., & Amos, D. E. (1963). Table of  percentage points of pearson curves. Biometrika, 50, 459.

Johnson, N. L., Nixon, E., Amos, D. E., & Pearson, E. S. (1963). Table of percentage points of Pearson curves for given 1 and 2, expressed in standard measure. Biometrika, 50, 459-498.

Johnson, P. (1987). SPC for short runs: A programmed instruction workbook. Southfield, MI: Perry Johnson.

Johnson, S. C. (1967). Hierarchical clustering schemes. Psychometrika, 32, 241-254.

Johnston, J. (1972). Econometric methods. New York: McGraw-Hill.

Jones, Bradley; Goos, Peter.- (2007) A candidate-set-free algorithm for generating D-optimal split-plot designs.- Journal of the Royal Statistical Society: series C: applied statistics, 56:3, p. 347-364

Jöreskog, K. G. (1973). A general model for estimating a linear structural equation system. In A. S. Goldberger and O. D. Duncan (Eds.), Structural Equation Models in the Social Sciences. New York: Seminar Press.

Jöreskog, K. G. (1974). Analyzing psychological data by structural analysis of covariance matrices. In D. H. Krantz, R. C. Atkinson, R. D. Luce, and P. Suppes (Eds.), Contemporary Developments in Mathematical Psychology, Vol. II. New York: W. H. Freeman and Company.

Jöreskog, K. G. (1978). Structural analysis of covariance and correlation matrices. Psychometrika, 43, 443-477.

Jöreskog, K. G., & Lawley, D. N. (1968). New methods in maximum likelihood factor analysis. British Journal of Mathematical and Statistical Psychology, 21, 85-96.

Jöreskog, K. G., & Sörbom, D. (1979). Advances in factor analysis and structural equation models. Cambridge, MA: Abt Books.

Jöreskog, K. G., & Sörbom, D. (1982). Recent developments in structural equation modeling. Journal of Marketing Research, 19, 404-416.

Jöreskog, K. G., & Sörbom, D. (1984). Lisrel VI. Analysis of linear structural relationships by maximum likelihood, instrumental variables, and least squares methods. Mooresville, Indiana: Scientific Software.

Jöreskog, K. G., & Sörbom, D. (1989). Lisrel 7. A guide to the program and applications. Chicago, Illinois: SPSS Inc.

Judge, G. G., Griffith, W. E., Hill, R. C., Luetkepohl, H., & Lee, T. S. (1985). The theory and practice of econometrics. New York: Wiley.

Juran, J. M. (1960). Pareto, Lorenz, Cournot, Bernoulli, Juran and others. Industrial Quality Control, 17, 25.

Juran, J. M. (1962). Quality control handbook. New York: McGraw-Hill.

Juran, J. M., & Gryna, F. M. (1970). Quality planning and analysis. New York: McGraw-Hill.

Juran, J. M., & Gryna, F. M. (1980). Quality planning and analysis (2nd ed.). New York: McGraw-Hill.

Juran, J. M., & Gryna, F. M. (1988). Juran's quality control handbook (4th ed.). New York: McGraw-Hill.