similar to: Discriminant Function 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

Hi list, I'm looking about lda function. I'd like to know how calcolate the value of the discriminant functions for the original datas. I see that in the result object "lda" there is $scaling a matrix which transforms observations to discriminant functions, normalized so that within groups covariance matrix is spherical. I'd like to have the value of the discriminant

Dear R user, I'm using qda (quadratic discriminant analysis) function (package MASS) to classify 58 explanatory variables (numeric type with different ranges) using a grouping variable (factor 2 levels "0" "1"). I'm using the qda method for class 'data.frame' (in this way I don't need to specify a formula). Using the function:

Kindly let me know the process to carry out a Linear discriminant analysis...thanks in advance Arup -- View this message in context: http://www.nabble.com/Linear-Discriminant-Analysis-tp22199424p22199424.html Sent from the R help mailing list archive at Nabble.com.

Hello everyone, I am totally new to the R program. I have had a look at some pdf documents that I downloaded and that explain how to do many things in R; however, I still cannot figure out how to do what I want to do, which is to perform Discriminant Correspondence Analysis on a rectangular matrix of data that I have in an Excel file. I know R users frown upon Excel and recommend converting Excel

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,

Hello, I've been playing with the manova() function to do some pretty straightforward multivariate analyses, and I can't for the life of me figure out how to get at the discriminant functions used. When predicting several variables simultaneously, it's important to be able to gauge how much each variable is contributing to the analysis...a simple p-value isn't really enough. I

Hi everyone, I intend to do a discriminant analyse for 2 measures(eye diameter and body length) and for different areas to show differences between those areas if there are any. The raw data (eye diameter, body length) make one cloud of points so it seems there aren't any differences between those areas. If I take the mean values (eye diameter) for length classes, I nearly get linear functions

Sir, I am working with multiclass discriminant analysis.(say response variable has 3classes).In R, using lda(), I get 2 sets of coefficients for the discriminant function.Now, I want to put a new x-vector(vector of independent variables) and want to check it corresponds to which class of y.Is there any formula for doing this? or how can I do this? Regards, Suman Dhara [[alternative HTML

Hello, I am using the mda package and in particular the fda routine to classify in term of gear a set of 20 trips. I preformed a flexible discriminant analysis (FDA) using a set of 151 trips. FDAT1 <- fda(as.factor(gear) ~ . , data =matrizR) A total of 22 predictors were considered. 20 of the predictors are "numeric" and 2 are "factors/discrete". The resulting FDA

Hi Alejo, According to my knowledge the two plots are different because in the first one a point belongs to a group depending on its group in the data whereas in the second plot a point belongs to the group predicted by the linear discriminant analysis. I hope somebody will correct me if I am wrong. Alain Alejo C.S. wrote: > Hi Alain, this is the code: > > > library(MASS) >

Hello, I might have missed it in the help pages, but I cannot find if something exits in a package to make discriminant analysis. Any help, or hint about where to look for it, is welcome, Laurent -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help",

I have the Rexcel package. Which of the functions do I want to run a discriminant function analysis? Or, how would I do it in R? Thanks. [[alternative HTML version deleted]]

Dear members, I am wondering if there are any functions to perform the Kernel Fisher Discriminant method, especially for multi-class problems, in R. I would appreciate any kind of information on this. Thanks for your time. Seungho Huh, Ph.D. Research Statistician RTI International North Carolina, USA [[alternative HTML version deleted]]

Dear All, I am using a specific approach for my master thesis. In essence, a supervised reclassification is used as an intermediate step to find chemical parameters which are able to reclassify defined groups. These variables will be used in a next step where location and scale estimators of the groups are important. Traditionally linear discriminant analysis is used for reclassification which

Hello, I am switching from SPSS-Windows to R-Linux. My university is very SPSS-oriented so maybe that's the cause of my problems. I am a beginner in R and my assignments are SPSS-oriented, so I hope I don't annoy anyone with my questions... Right now I've got 2 problems: -I have to evaluate discriminant functions I have calculated with lda(MASS). I can't find a measure that

How can I extract the linear discriminant functions resulting from a LDA analysis? The coefficients are listed as a result from the analysis but I have not found a way to extract these programmatically. No refrences in the archives were found. Thank you very much, Stefan

Hi all, I ran a discriminant analysis with some data and want to get a general idea of prediction error rate. Some have suggested using X-fold cross validation procedure. Anyone know if there is a function for this in R? Thanks, Wade [[alternative HTML version deleted]]

Hello R list, I'm looking to do some stepwise discriminant function analysis (DFA) based on the minimization of Wilks' lambda in R to end up with a composite signature (of metals "Al","Sb","Bi","Cr","Ba") capable of discriminating 100% of the source factors (LANDUSE: "A","B","C"). The Wilks' lambda

Shuji, I suspect that bruto blows up because your data are linearly separable. To see this (if you didn't already know), try library(lattice) splom(~x, groups = y) and look at the first row. If you are trying to do classification, there are a few methods that would choke on this (logistic regression) and a few that won't (trees, svms etc). I would guess that bruto is in the latter