similar to: kmeans and plot labels

Hi, I would like to display inter-parameter scatter plots like those with the corrgram package (see upper triangle here: http://www.statmethods.net/advgraphs/images/corrgram2.png ), just that I would like to plot two datasets instead of one. Say one with black and one with red dots. Or a merged dataset where an indicator column is used to assign different colors to particular dots - with still

Hi, For my data, I followed the example of http://en.wikibooks.org/wiki/Data_Mining_Algorithms_In_R/Clustering/K-Means#Execution and got some very nice results. Despite the fact, that I want to achieve a bit more by clustering my data (stratification beyond case-control), the actual data-frame contains a column labeled "C" which holds a case-control indicator (here either "Z"

Hi, I would like to tabulate the likelihood for an affection. For this, I retrieve indices of affected people and controls for my data set and proceed as follows: flags <- c(rep(1, length(patient_indices)), rep(0, length(control_indices))) # dataset is a data.frame and param the parameter to be analysed: data1 <- dataset[,param][c(patient_indices, control_indices)] fit1 <- glm(flags ~

# 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) > # > #

This is a simple problem, but a mystery to me. I'm trying to grab $Family "Scelionidae" from one dataframe and put it into another dataframe occupied with NA in $Family. The result is a "158" ends up there instead of Scelionidae. Simply put fam$Family[1] <- least$Family[1] If I have made a mistake here, can somebody point it out. I've included the simple

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,

Your data frame fam contains factors. Turn it into character strings using fam$Family = as.character(fam$Family) and try again. It may be helpful if you read up on R's factors, see ?factor. HTH, Peter On Tue, Nov 21, 2017 at 2:14 PM, Glen Forister <gforister at gmail.com> wrote: > This is a simple problem, but a mystery to me. > I'm trying to grab $Family

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,

Well, ?factor does not say anything about this behaviour (assigning numeric code instead of level of factor). And actually if you do assignment for whole vector the result is different (vector in data frame is changed to factor). > temp2$fff[1]<-vec[1] > head(temp2,2) pokus minuty fff 1 T42 240 3 2 T42 300 <NA> > temp2$fff<-vec > head(temp2,2) pokus

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)))

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) >

With rw2010dev I get a strange protect(): protection stack overflow error with a small data frame which otherwise is usable: If anybody wants to have a look I can provide an RData file with the problematic data frame. Doesn't seem to be necessary, the following simulated example generates the error: > testmat <- matrix(1:80, 20,4) > dim(testmat) [1] 20 4 > str(testmat) int

Hello everyone, I have a 2 x 5 matrix: say 0.2 0.3 1 -1 3 0.2. 0.4 5 0.5 -1 I want to replace all the values greater than or equal to 1 with 1 and those less than or equal to 0 with 0. So I should end up with a mtrix looking like: 0.2 0.3 1 0 1 0.2. 0.4 1 0.5 0 Any ideas how to do this? -- Thanks, Jim. [[alternative HTML version deleted]]

I've writen this function (imagenrgb) to display a (m,n,3) array as a RGB image with ngris^3 colors and,optionally, stretching. If option ver=F, it does not display but saves a pseudocolor version of the image as a list (so that subsequent displays are faster). I'd appreciate feedback and improvements and hope that it's useful for others. Example of use: > dim(imatest) [1] 100

Hello All, I'm trying to run a maximum likelihood analysis using dmultinomial (i'm avoiding dmultinom as I'd like to run it with vectors for the ML stuff). However, I'm having a hard time getting even the simplest example running. Any help would be greatly appreciated. > library(mc2d) > dmultinomial(x=c(0,0,1),prob=c(1,1,1),size=1,log=TRUE) Error in if (ncol(x) != K)

> # >> # Generate the figures (on screen) >> # >> # Image generation - function definition >> pic_onscr<-function(matrix, title, cex_val=1) > + {x11() + par(mgp=c(5,2,0), # axis margins + # (title, > labels, line) + mar=c(7,4,4,2), # plot margins (b,l,t,r) + > las=1) # horizontal labels + plot(matrix, # data to plot + >

Here's the problem I'm trying to solve in R: I have a data frame that consists of about 1500 cases (rows) of data from kids who took a test of listening comprehension. The columns are their scores (1 = correct, 0 = incorrect, . = missing) on 140 test items. The items are numbered sequentially and are ordered by increasing difficulty as you go from left to right across the columns. I want

Dear All, It is a common problem to update R for distributors. My challenge is to maintain R module files for a cluster, using easybuild. My question is: Is there a way to derive a list of cran packages and their version for a given version of R? In case addressing the R-help list is addressing wrong list, any pointer is appreciated. Best regards, Christian Meesters

Hi. In a data set I have a variable that takes values from 1 to 14. For each subgroup of values of this variable, I would like to obtain some descriptive statistics of other variables present in the data set. I've been trying with a "for" loop but I couldn't get nothing. Could you please suggest me some lines? -- View this message in context: