If the textbook provides the equations, you can work through them directly. But without knowing more, it is hard to say. You could also contact the author of the textbook.
------------------------------------- David L Carlson Department of Anthropology Texas A&M University College Station, TX 77840-4352 -----Original Message----- From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Jens Koch Sent: Wednesday, March 2, 2016 9:19 AM To: r-help@r-project.org Subject: [R] discriminant analysis lda under MASS Hello all, I'd like to run a simple discriminant analysis to jump into the topic with the following dataset provided by a textbook: Gruppe Einwohner Kosten 1 1642 478,2 1 2418 247,3 1 1417 223,6 1 2761 505,6 1 3991 399,3 1 2500 276 1 6261 542,5 1 3260 308,9 1 2516 453,6 1 4451 430,2 1 3504 413,8 1 5431 379,7 1 3523 400,5 1 5471 404,1 2 7172 499,4 2 9419 674,9 2 8780 468,6 2 5070 601,5 2 5780 578,8 2 8630 641,5 The coefficients according to the textbook need to be -0.00170 and -0.01237. If I put the data into the lda function under MASS, my result is: Call: lda(Gruppe ~ Einwohner + Kosten, data = data) Prior probabilities of groups: 1 2 0.7 0.3 Group means: Einwohner Kosten 1 3510.429 390.2357 2 7475.167 577.4500 Coefficients of linear discriminants: LD1 Einwohner 0.0004751092 Kosten 0.0050994964 I also tried to solve it by an another software package, but there is also not the result I have expected. I know now, that the solution for the coefficients is standardized by R and the discrimination power is not different at the end of the day. But: How can I get (calculate) the results printed in the textbook with R? Thanks in advance, Jens. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
