similar to: Fisher's method in discriminant analysis

Hi everyone, I'm trying to solve a problem about how to get the Fisher's discriminant functions of a "lda" (linear discriminant analysis) object, I mean, the object obtained from doing "lda(formula, data)" function of the package MASS in R-project. This object gives me the canonical linear functions (n-1 coefficients matrix of n groups at least), and only with this

I am making a battery of levelplots and wireframes for several fitted models. I wrote a function that takes the fitted model object as the sole argument and produces these plots. Various strange behavior ensued, but I have identified one very concrete issue (illustrated below): when my figure-drawing function includes the addition of points/lines to trellis plots, some of the

Hi, I'm a newbie in R and don't much aobut all the modules and their capabilities, but I'm interested in solving a problem about a discriminant analysis done with SPSS tool. The thing is that I would like to make a discrimant analysis similar to the one done with SPSS, but I can't find the way to solve it. I've been playing with R and I can handle more or less my data,

Hi, I am trying to solve a discriminant analysis in the same way as SPSS does it. I mean, given an amount of data, to train the discriminant analysis I obtain the Fisher's discriminant functions, an array of coefficients per group, so if I have 8 groups I get 8 linear functions, that allow me to operate with them easily and without a great cost of time. My main problem is that I need to

Hi all, I'm fitting GLM's using the step or stepAIC procedures and I would like to save the AIC of the intermediate models. I would appreciate very much information about how todo this. Best wishes Germ??n L??pez

For a private package ("soon" to be on CRAN), I started looking at and thinking about the function confusion() from the mda package and wondered if it wouldn't make sense to provide the generic function in base R and also think about making the default for the `true' argument equal to fitted(object). One could write methods for confusion() for almost all classifiers which

Hi to all is there a fisher's post hock test or fisher's combination test in R available? Maybe not -- its very easy to do it in excel ... Kind regards Knut

Dear all I have an experiment where plots either have or have not regrown (in 40 plots) after receiving 12 different herbicide treatments and a control (no treatment). The data are significant with a Chi2, but to later distinguish if the differences are significant between each of the 12 treatments apart I need to do multiple Chi2 s between each. Is there a way to run those multiple Chi2 or

Hi there, ============================= x=c(145,40,40,120,180, 140,155,90,160,95, 195,150,205,110,160, 45,40,195,65,145, 195,230,115,235,225, 120,55,50,80,45 ) y2=c( rep(as.character(1),5), rep(as.character(2),5), rep(as.character(3),5), rep(as.character(4),5), rep(as.character(5),5), rep(as.character(6),5) ) crd2=data.frame(x,y2) model1=aov(x~y2,data=crd2) TukeyHSD(model1)

Hi, I have a table of observed counts for various genetic markers. Instead of doing Fisher's exact test for each marker one at a time and recording the P value manually, is there a script to go through the whole list and generate the P value column automatically? An example of my data: Counts_CHB and Counts_AA are the observed counts for one allele. 2N_CHB and 2N_AA are the total number

Hi I was wondering whether anyone can help me with this problem....it's been driving me nuts, I've been trying to figure it out for months and months without success!! Basically I have a group of participants who attended 2 experimental sessions a few months apart. I took measures of the way they approach two tasks at Time 1 and the same two tasks at Time 2. I have categorical data (a

I have a matrix with 2 columns and I want to do fishers exact test for these with the totals for each row being 100 say. The data has the form: 23 12 32 21 12 2 and these represents the tables: 23 12 77 88 32 21 78 79 12 2 88 98 How do I use apply to speed up aclculation of the fisher.exact test? -- Thanks, Jim. [[alternative HTML version deleted]]

I have a matrix say, 1 4 23 30 and I want to find the previously attainable fisher's exact test p-value. Is there a way to do this in R? -- Thanks, Jim. [[alternative HTML version deleted]]

Hi there, Is there a function that can do a Fisher's LSD multiple comparisons in a two-way ANOVA? I hope to get a result similar with TukeyHSD(). Especially, I hope to know the significance of comparisons between the interactions of two factors. In the following example: x <- c(76, 84, 78, 80, 82, 70, 62, 72, 71, 69, 72, 74, 66, 74, 68, 66, 69, 72, 72, 78, 74, 71, 73, 67, 86, 67, 72,

Hi, I'm trying to run Fisher's Exact test on the data below, but I'm not sure how interpret the data shown. Can someone tell me what this is saying? Looking at the numbers it should be that there's no significant difference between the HDL and LDL, but a p-value of 1 seems high. Is the low value in the LDL unbound making the test unstable and should I be using an alternative? Best

Full_Name: Martha Nason Version: 2.0.1 OS: Windows XP Submission from: (NULL) (137.187.154.154) I am running simulations using fisher's test on 2 x c tables and a very small p.value from fisher's test (<2.2e-16) is returned as a negative number. Code follows. > set.seed(0) > nreps.outer <-7 > pvalue.fisher <- rep(NA,nreps.outer) > > population1 <- c(

Dear all, how can I "reshape"/"cast" the following matrix 00;01;10;11 John.Mike;123;313;12;31 John.Jim;54;57;39;36 John.Steve;135;47;47;74 Mike.Jim;63;37;27;16 Mike.Steve;15;15;5;61 Jim.Steve;6;10;34;35 into a set of stacked 2x2 contingency tables 0;1 John;123;12 Mike;313;31 John;54;39 Jim;57;36 John;135;47 Steve;47;16 ... so that the "fisher.test" and

Hi folks, Forgive me if this question is a trivial issue. I was doing a series of Fishers' exact test using the fisher.test function in stats package. Since the counts I have were quite large (c(64, 3070, 2868, 4961135)), R suggested me to use *other algorithms* for the test which can be specified through the 'control' argument of the fisher.test function as I understood. But where

Timothy, I believe you are mistaken. Fisher's exact test give the correct answer even in the face of small expected values for the cell counts. Pearson's Chi-square approximates Fisher's exact test and can give the wrong answer when expected cell counts are low. Chi-square was developed because it is computationally "simple". Fisher's exact test, particularly with tables

Hi All, Can somebody tell me how to use R to combine p values using Fisher's method? thanks. Jiong The email message (and any attachments) is for the sole use of the intended recipient(s) and may contain confidential information. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply email and