Учебник по промышленной статистике


Список использованной литературы - часть 20


Harris, R. J. (1976). The invalidity of partitioned U tests in canonical correlation and multivariate analysis of variance. Multivariate Behavioral Research, 11, 353-365.

Hart, K. M., & Hart, R. F. (1989). Quantitative methods for quality improvement. Milwaukee, WI: ASQC Quality Press.

Hartigan, J. A. (1975). Clustering algorithms. New York: Wiley.

Hartigan, J. A. & Wong, M. A. (1978). Algorithm 136. A k-means clustering algorithm. Applied Statistics, 28, 100.

Harrison, D. & Rubinfield, D. L. (1978). Hedonic prices and the demand for clean air. Journal of Environmental Economics and Management, 5, 81-102.

Hartley, H. O. (1959). Smallest composite designs for quadratic response surfaces. Biometrics, 15, 611-624.

Harville, D. A. (1977). Maximum likelihood approaches to variance component estimation and to related problems. Journal of the American Statistical Association, 72, 320-340.

Haskell, A. C. (1922). Graphic Charts in Business. New York: Codex.

Haviland, R. P. (1964). Engineering reliability and long life design. Princeton, NJ: Van Nostrand.

Hayduk, L. A. (1987). Structural equation modelling with LISREL: Essentials and advances. Baltimore: The Johns Hopkins University Press.

Haykin, S. (1994). Neural Networks: A Comprehensive Foundation. New York: Macmillan College Publishing.

Hays, W. L. (1981). Statistics (3rd ed.). New York: CBS College Publishing.

Hays, W. L. (1988). Statistics (4th ed.). New York: CBS College Publishing.

Heiberger, R. M. (1989). Computation for the analysis of designed experiments. New York: Wiley.

Hemmerle, W. J., & Hartley, H., O. (1973). Computing maximum likelihood estimates for the mixed A.O.V. model using the W transformation. Technometrics, 15, 819-831.

Henley, E. J., & Kumamoto, H. (1980). Reliability engineering and risk assessment. New York: Prentice-Hall.

Hettmansperger, T. P. (1984). Statistical inference based on ranks. New York: Wiley.

Hibbs, D. (1974). Problems of statistical estimation and causal inference in dynamic time series models.


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