similar to: LDA cutoff value

Hello everyone, I am working on a linear discriminant analysis and am having issues finding the full output of my lda. Specifically, there is no reporting of the Proportion of Trace that is a normal output of the procedure. I'm using a csv file and everything is reading in correctly. I've looked and looked and can't figure out why my output is not complete. Is it something simple that

Dear R folks, Thanks to all your help before I have loaded a 1-D toy data set into R and did LDA on it. The toy data has Class=0 if value>0. > XY <-- read.table ("test.xy",header=T ) > XY X.Class value 1 0 60.4897262 2 0 32.9554489 3 -1 -53.6459189 4 0 44.4450579 . . . 998 -1 -43.4183157 999 0

Fellow R Users: I'm not extremely familiar with lda or R programming, but a recent editorial review of a manuscript submission has prompted a crash cousre. I am on this forum hoping I could solicit some much needed advice for deriving a classification equation. I have used three basic measurements in lda to predict two groups: male and female. I have a working model, low Wilk's lambda,

Thanks David, Yes, I am talking about the MASS package.Thank you for pointing out that these scale the same. My question is, how do I get from the V1 data: V1 1 164.4283 2 166.2492 3 170.5232 4 156.5622 5 127.7540 6 136.7704 7 136.3436 to the other set of data: + 1 -2.3769280 + 2 -2.7049437 + 3 -3.4748309 + 4 -0.9599825 + 5 4.2293774 + 6 2.6052193 + 7 2.6820884 On Mon, Sep 28, 2009

I'm sory for my weak english. I need to analyze this subject : x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 y 0 0 1 0 0 1 0 0 1 0 czarne 1 1 0 0 0 0 1 0 0 0 rude 0 0 1 0 0 1 1 0 0 0 braz 0 0 1 0 1 0 1 0 0 0 blond 1 0 0 0 0 1 0 0 0 1 rude 1 1 0 0 0 0 0 0 0 1 blond 0 0 1 1 0 0 0 0 1 0 czarne 1 0 0 1 0 0 1 0 0 0 blond 0 0 1 0 0 1 1 0 0 0 blond 1 0 0 0 0 1 1 0 0 0 czarne 0 0 1 0 0 1 0 0 0 1 czarne 1 0 1 0 0 0

Dear Help-list, How can I do a multiple comparison test (mct) on selected contrasts from a linear model while using packages lme4 and multcomp? I am running R 2.13.0 under Windows 7. The following linear model and mct produces a global mct of 15 paired contrasts of the combined (Site, Position) factor SitePos of which only 9 are of interest. Model.G = lmer(log10(SrCa) ~ SitePos + (1 | Eel),

I'm confused on how is the right way to plot a discriminant analysis made by lda function (MASS package). (I had attached my data fro reproduction). When I plot a lda object : X <- read.table("data", header=T) lda_analysis <- lda(formula(X), data=X) plot(lda_analysis) #the above plot is completely different to: plot(predict(lda_analysis)$x,

I am having a problem understanding the lda package. I have a dataset here: [,1] [,2] [,3] [1,] 2.95 6.63 0 [2,] 2.53 7.79 0 [3,] 3.57 5.65 0 [4,] 3.16 5.47 0 [5,] 2.58 4.46 1 [6,] 2.16 6.22 1 [7,] 3.27 3.52 1 If I do the following; "names(d)<-c("y","x1","x2") d$x1 = d$x1 * 100 d$x2 = d$x2 * 100 g<-lda( y ~ x1 + x2, data=d) v2

Hi, it seems that the lda function in MASS library doesn''t give out the constant for the linear discriminant function under the situation that we don''t use standardized variable, anyone knows how to obtain the constant in order to construct the linear discriminant function? I understand that if the priors are set to be 1/2, the threshold of the discriminant score used to

R-help, I recently updated R from 2.13.0 to 2.13.1 (32-bit Windows version) and now have a problem updating packages. I am running Windows 7 as operating system. As the FAQ suggests, I uninstalled 2.13.0 before installing 2.13.1. On first opening R, I ran "update.packages(checkBuilt=TRUE, ask=FALSE) ras also recommended and selected the NS Cran mirror. On doing this the following error

Dear R Help Members, I am aware how to plot the LD1 vs LD2 from a lda in R, using the code: plot(baseline.systat.hat$x, col=baseline.systat.hat$class,pch=as.numeric(baseline.systat.hat$class)) However, I need to use the quadratic discriminant function, qda due to data properties. Is there a way to obtain the same sort of plot for from a qda object (and the output of predict qda). I have not

Dear r-help, I would like to select a subset of levels from a factor variable in a data frame and return a data frame. The data set consists of 3 variables, 2 of which are factors (Site, Fish) and one numeric (Datavalue) as follows: Site Fish Datavalue AB 2-1 2.3 AB 2-1 2.4 AB 2-1 2.2 AB 2-2 2.6 AB 2-2 2.5 AB 2-2 2.7 AB 2-3

Hello all- I am a relatively new user of R and am working through a graduate course in Statistics that uses Minitab, SAS and some Matlab. I like using R but am having some trouble lining up the output from lda() to that of the other programs' results. The dataset below is a modified set of wine data from the Pinot Noir data set as an illustration of the 2 group LDA scenario. Mo Ba

Hi there, I am a master student in Denmark, and apply R to analyze the drug data. I use the function 'lda' to obtain a linear discriminant object, and then wish to use 'plot.lda' to do the plot on this object like below. drug.lda <- lda(Inhibition ~ NET_CHARGE + PKA_1 + MW + MLOGP, data = drug.class, method = "moment") plot.lda(drug.lda,

Dear help list: I am trying to reshape a data frame from long to wide format and with a reduced variable list using reshape2. The original data frame format is: Site Obs_no LengthSite 1 Obs 1 10Site 1 Obs 2 13Site 1 Obs 3 14.........Site 2 Obs 1 5Site 2 Obs 2 7Site 2 Obs 3 9 Site and Obs_no are factors and Length is a numeric variable. There are 15

Hello, I am using WinXP, R version 2.3.1, and SAS for PC version 8.1. I have mostly used SAS over the last 4 years and would like to compare the output of PROC DISCRIM to that of lda( ) with respect to a very specific aspect. My data have k=3 populations and there are 3 variates in the feature space. When using using the code PROC DISCRIM DATA = FOO OUT = FOO_OUT OUTSTAT = FOOSTAT

Friends Briefly... In the documentation for lda in MASS it describes the value 'scaling' as 'a matrix which transforms observations into discriminint functions...'. How? Verbosely... I have a matrix of data. 9 independent variables and describing 3-classes. About 100 observations in total. A 10x100 matrix of data. I am trying to generate two discriminant functions and i

Hi, I am using the lda function from the MASS library. I would to find the decision boundaries of each class and subsequently plot them. I wonder if anybody can offer any help on this topic? Below I applied the lda function on a small dataset of mine. Any help will be much appreciated. > library(MASS) >

Hi All, I've encountered an issue where tail merging MIs is causing a problem with the post-RA MI scheduler dependency analysis and I'm not sure of the best way to address the problem. In my case, the branch folding pass (lib/CodeGen/BranchFolding.cpp) is merging common code from BB#14 and BB#15 into BB#16. It's clear that there are 4 common instructions (marked with an *) in BB#14

Hi, Having dipped my toe into R a few times over the last year or two, in the last few weeks I've been using it more and more; I'm now a thorough convert. I've just joined the list, because although it's great, I do have this problem... I'm using linear discriminant analysis for binary classification, and am happy with the classification performance using predict(). What