このバージョンのヘルプはこれ以降更新されません。最新のヘルプは https://www.jmp.com/support/help/ja/15.2   からご覧いただけます。


Agrawal, R., and Srikant, R. (1994). “Fast Algorithms for Mining Association Rules.” In Proceedings of the 20th VLDB Conference. Santiago, Chile: IBM Almaden Research Center. Retrieved July 5, 2016 from http://rakesh.agrawal-family.com/papers/vldb94apriori.pdf.
Bates, D. M., and Watts, D. G. (1988). Nonlinear Regression Analysis and Its Applications. New York: John Wiley & Sons.
Box, G. E. P., Jenkins, G. M., and Reinsel, G. C. (1994). Time Series Analysis: Forecasting and Control. 3rd ed. Englewood Cliffs, NJ: Prentice-Hall.
Cleveland, W. S. (1994). Visualizing Data, Summit, NJ: Hobart Press.
Conover, W. J. (1999). Practical Nonparametric Statistics. 3rd ed. New York: John Wiley & Sons.
Hand, D. J., Mannila, H., and Smyth, P. (2001). Principles of Data Mining. Cambridge, MA: MIT Press.
Hastie, T. J., Tibshirani, R. J., and Friedman, J. H. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction. 2nd ed. New York: Springer-Verlag.
Hawkins D. M., and Kass G. V. (1982). “Automatic Interaction Detection.” In Topics in Applied Multivariate Analysis, edited by D. M. Hawkins, 267–300. Cambridge: Cambridge University Press.
Huber, P. J., and Ronchetti, E. M. (2009). Robust Statistics. 2nd ed. New York: John Wiley & Sons.
Jolliffe, I. T. (2002). Principal Component Analysis. New York: Springer-Verlag.
Lehman, E. L. (2006). Nonparametrics: Statistical Methods Based on Ranks. 2nd ed. New York: Springer.
Mason, R. L., and Young, J. C. (2002). Multivariate Statistical Process Control with Industrial Applications. Philadelphia: SIAM.
McCullagh, P., and Nelder, J. A. (1989). Generalized Linear Models. 2nd ed. London: Chapman & Hall.
Nelder, J. A., and Wedderburn, R. W. M. (1972). “Generalized Linear Models.” Journal of the Royal Statistical Society, Series A 135:370–384.
Parker, R. J. (2015). Efficient Computational Methods for Large Spatial Data. Ph.D. diss., Department of Statistics, North Carolina State University. Retrieved June 30, 2016 from http://repository.lib.ncsu.edu/ir/bitstream/1840.16/10572/1/etd.pdf.
Ramsay, J. O., and Silverman, B. W. (2005). Functional Data Analysis. 2nd ed. New York: Springer.
Ratkowsky, D. A. (1990). Handbook of Nonlinear Regression Models. New York: Marcel Dekker.
Santer, T., Williams, B., and Notz, W. (2003). The Design and Analysis of Computer Experiments. New York: Springer-Verlag.
SAS Institute Inc. (2017). SAS/ETS User’s Guide, Version 14.3. Cary, NC: SAS Institute Inc. http://support.sas.com/documentation/onlinedoc/ets/143/etsug.pdf
Shiskin, J., Young, A. H., and Musgrave, J. C. (1967). The X-11 Variant of the Census Method II Seasonal Adjustment Program. Technical Report 15, US Department of Commerce, Bureau of the Census.
Shmueli, G., Patel, N. R., and Bruce, P. C. (2010). Data Mining For Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner. 2nd ed. Hoboken, NJ: John Wiley & Sons.
Shmueli, G., Bruce, P. C., Stephens M. L., and Patel, N. R. (2017). Data Mining For Business Intelligence: Concepts, Techniques, and Applications with JMP Pro. Hoboken, NJ: John Wiley & Sons.
Westfall, P. H., Tobias, R. D., and Wolfinger, R. D. (2011). Multiple Comparisons and Multiple Tests Using SAS. 2nd ed. Cary, NC: SAS Institute Inc.