similar to: plotting lda results

I work on Windows, R version 2.4.1 I need to leave out many rows and columns when reading a matrix. The 'skip' commands in read.table, seem to be just for skipping rows, if I understand well, but I need to skip many columns as well. I tried something very simple and left one row and one column out, but I don't know how to do it for many rows and columns at a time. Example: zzz #

I am trying to get a random matrix based on an original matrix called disperser.mx, with dimensions 30x73 When I write the following code: >scramble = sample (disperser.mx) >newmat = matrix(scramble, nrow=30) I get the following warning message and a very weird matrix with 30 rows but only 3 columns shown below: Warning message: data length [73] is not a sub-multiple or multiple of the

Hi, I am new to R...a recent convert from SAS. I have a dataset that looks like this: SEQ A1 A2 A 532.5 554.5 B 25.5 35.5 C 265.2 522.2 D 245.55 521.56 E 546.52 141.52 F 243.25 32.56 G 452.55 635.56 H 15.14 16.54 I 543.4 646.56 J 54.4 654.5 K 646.5 64.54 L 645.4 614.46 M 646.54 634.46 I want to make a histogram

Hello, Does anyone knows how to do the plots from discriminant analysis (lda and qda)? Is there any computed function to do the stepwise procedure? thank you in advance Marta

I work with Windows and use R version 2.4.1. I am JUST starting to learn this program... I get this warning message 'NAs introduced by coercion' while trying to build a distance matrix (to be analyzed with NMDS later) from a 336 x 100 data matrix. The original matrix has lots of zeros and no missing values, but I don't think this should matter. I searched this forum and people have

Hi R-community, I am doing a PCA and I need plots for different combinations of axes (e.g., PC1 vs PC3, and PC2 vs PC3) with the arrows indicating the loadings of each variables. What I need is exactly what I get using biplot (pca.object) but for other axes. I have plotted PC2 and 3 using the scores of the cases, but I don't get the arrows proportional to the loadings of each variables on

Hi all, Can anyone please tell me how to start R from Tinn-R's "Toogle start/close Rgui" button, after I've updated to a new version of R? It seems like Tinn-R keeps looking for the previous version of R. I have updated R twice already since I started using Tinn-R and I haven't been able to make that button work again. It tells me "The specified file was not

I work with Windows, R version 2.4.1 I'm trying to do a discriminant analysis and, in trying to figure out how to do it following the example from R help, I'm getting an error that says 'subscript out of bounds'. I don't know what this means and how to solve it (I'm very new with R) I'm doing everything in this made-up test matrix: group var1 var2 var3 1 1

# lda.r > # > # Author: Amsha Nahid, Jairus Bowne, Gerard Murray > # Purpose: Perform Linear Discriminant Analysis (LDA) > # > # Input: Data matrix as specified in Data-matrix-format.pdf > # Output: LDA plot > # > # Notes: Missing values (if any) are replaced by the half of the lowest > # value in the entire data matrix. >

hello, i already include the error in blue color word. i hope it can help you to understand my question. if not burden you, please give me a guide how to correct the error or maybe you can correct the coding cause error. thank you. > # lda.r > # > # Author: Amsha Nahid, Jairus Bowne, Gerard Murray > # Purpose: Perform Linear Discriminant Analysis (LDA) > # > #

Hi, I am trying to do a PCA on my data but I keep getting the error message svd(x, nu=0) infinite or missing values >From the messages posted on the subject, I understand that the NAs in my data might be the problem, but I thought na.omit would take care of that. Less than 5% of my cells are missing data. However, the NAs are not regularly distributed across my matrix: certain cases and

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,

I use Windows, R version 2.4.1. I have a dataset in which columns 1-3 are replicates, 4-6, are replicates, etc. I need to calculate an average for every set of replicates (columns 1-3, 4-6, 7-9, etc.) AND each set of replicates should be averaged every 14 rows (for more detail, to measure fruit color using a spectrometer, I recorded three readings per fruit -replicates- that I need to average to

Hi, I have done different discriminant function analysis of multivariat data. With the CV=True option I was not able to perform the predict() call. What do I have to do? Or is there no possibility at all? You also need the predicted values to produce a plot of the analysis, as far as I know. Here my code: pcor.lda2<-lda(pcor~habarea+hcom+isol+flowcov+herbh+inclin+windprot+shrubcov+baregr,

Hi !! I am trying to analyze some of my data using linear discriminant analysis. I worked out the following example code in Venables and Ripley It does not seem to be happy with it. ============================ library(MASS) library(stats) data(iris3) ir<-rbind(iris3[,,1],iris3[,,2],iris3[,,3]) ir.species<-factor(c(rep("s",50),rep("c",50),rep("v",50)))

I work on Windows, R version 2.4.1. I'm very new with R! I am trying to build a classification tree using rpart but, although the matrix has 108 variables, the program builds a tree with only one split using one variable! I know it is probable that only one variable is informative, but I think it's unlikely. I was wondering if someone can help me identify if I'm doing something

I use Windows, R version 2.5.1 When I try to run stepclass (klaR) I get an error message/warning saying: 1: error(s) in modeling/prediction step in: cv.rate(vars = c(model, tryvar), data = data, grouping = grouping, ... Actually, I look 16 warnings of this type. Can anyone tell me what this means? Also, it returns only 2 out of the 79 variables as important, however these variables

Hi, When I am using ldahist function I would like to specify different colors for each of the groups in the data I am using. Is it possible? If not does anybody know of another function to plot multiple histograms on one plot for different groups. Thanks ===== Thanks Fairouz Makhlouf

Hi all. I would like to understand what are the units defined on the y-axis when you plot the one-dimensional predictions (histograms) from lda() (MASS) discriminant function objects? While the helpfile suggests that a histogram is returned by default, the presumably proportion-like values for each group seem to add up to more than 1, and I'm not sure how to interpret the code from ldahist(),

HELLO, anybody... could you help me to check the below coding for volcano. what is the mistake? what the plot could not display? # volcano_plot.r # # Author: Amsha Nahid, Jairus Bowne, Gerard Murray # Purpose: Produces a volcano plot # # Input: Data matrix as specified in Data-matrix-format.pdf # Output: Plots log2(fold change) vs log10(t-test P-value) # #