Учебник по промышленной статистике


Список использованной литературы - часть 38


Piatetsky-Shapiro, G. (Ed.) (1993). Proceedings of AAAI-93 Workshop on Knowledge Discovery in Databases. Menlo Park, CA: AAAI Press.

Piepel, G. F. (1988). Programs for generating extreme vertices and centroids of linearly constrained experimental regions. Journal of Quality Technology, 20, 125-139.

Piepel, G. F., & Cornell, J. A. (1994). Mixture experiment approaches: Examples, discussion, and recommendations. Journal of Quality Technology, 26, 177-196.

Pigou, A. C. (1920). Economics of Welfare. London: Macmillan.

Pike, M. C. (1966). A method of analysis of certain class of experiments in carcinogenesis. Biometrics, 22, 142-161.

Pillai, K. C. S. (1965). On the distribution of the largest characteristic root of a matrix in multivariate analysis. Biometrika, 52, 405-414.

Plackett, R. L., & Burman, J. P. (1946). The design of optimum multifactorial experiments. Biometrika, 34, 255-272.

Polya, G. (1920). Uber den zentralen Grenzwertsatz der Wahrscheinlichkeitsrechnung und das Momentenproblem. Mathematische Zeitschrift, 8, 171-181.

Porebski, O. R. (1966). Discriminatory and canonical analysis of technical college data. British Journal of Mathematical and Statistical Psychology, 19, 215-236.

Powell, M. J. D. (1964). An efficient method for finding the minimum of a function of several variables without calculating derivatives. Computer Journal, 7, 155-162.

Pregibon, D. (1997). Data Mining. Statistical Computing and Graphics, 7, 8.

Prentice, R. (1973). Exponential survivals with censoring and explanatory variables. Biometrika, 60, 279-288.

Press, William, H., Flannery, B. P., Teukolsky, S. A., Vetterling, W. T. (1986). Numerical recipies. New York: Cambridge University Press.

Press, W. H., Flannery, B. P., Teukolsky, S. A., Vetterling, W. T. (1992). Numerical recipies (2nd Edition). New York: Cambridge University Press.

Priestley, M. B. (1981). Spectral analysis and time series. New York: Academic Press.

Pyzdek, T. (1989). What every engineer should know about quality control. New York: Marcel Dekker.




Начало  Назад  Вперед



Книжный магазин