similar to: how to change legend size in a figure

Dear All, I tried to plot a variety of lines(curves) on same figure. What I did is, plot(x=x1,y=y1) lines(x=x2,y=y2) lines(x=x3,y=y3) ... In my data, the maximum of y1 is much smaller than those maximums of other y vectors. So, in the figure I got, there are some curves which are not complete, I mean, they were cut off at the maximum of y1 at the y axis. Could anybody point out some right

Dear All, I have a data, suppose it is an N*M matrix data. All I want is to classify it into, let see, 3 classes. Which method(s) do you think is(are) appropriate for this purpose? Any reference will be welcome! Thanks! Best, Baoqiang Cao

Dear All, I am using wilcox.test to test two samples, data_a and data_b, earch sample has 3 replicates, suppose data_a and data_b are 20*3 matrix. Then I used the following to test the null hypothesis (they are from same distribution.): wilcox.test(x=data_a, y=data_b, alternative="g") I got pvalue = 1.90806170863311e-09. When I switched data_a and data_b by doing the following:

Hi there, I really couldn't find out how to plot histogram with point/line instead of rectangle for each bin? Any help please? Thanks! Best, -Cao

Dear All, I'm learning to train a neural network with my training data by using nnet package, then evaluate it with a evaluation set. My problem here is that, I need the trained network to be used in future, so, what should I store? and How? Any other options other than nnet package? Any example will be highly appreciated! Best, Baoqiang Cao

Hi Everyone, I'm trying to use cutree to get the clusters after hclust. What I used is: mycluster<-cutree(cnclust,h=0.5) Now, my problem is, how can I get the actual clusters? Thanks! Best, Baoqiang Cao

Dear All, I was trying to format a numeric vector (100*1) by using outd <- format(x=m, sci=F, digits=2) > outd[1:10] [1] " 0.01787758" "-0.14760306" "-0.45806041" "-0.67858525" "-0.64591748" [6] "-0.05918100" "-0.25632276" "-0.15980138" "-0.08359873" "-0.37866688" >m[1:10] [1]

Hi, I'd like to download some data files from a remote server, the problem here is that some of the files actually don't exist, which I don't know before try. Just wondering if a function in R could tell me if a file exists on a remote server? I searched this mailing list and after read severals mails, still clueless. Any help will be highly appreciated. B.C.

Hi R-Helpers, Sorry to bother you, but I have a simple task that I can't figure out how to do. For example, I have some names in two columns NamesWide<-data.frame(Name1=c("Tom","Dick"),Name2=c("Larry","Curly")) and I simply want to get a single column

Just to repeat: you have NamesWide<-data.frame(Name1=c("Tom","Dick"),Name2=c("Larry","Curly")) and you want NamesLong<-data.frame(Names=c("Tom","Dick","Larry","Curly")) There must be something I am missing, because NamesLong <- data.frame(Names = c(NamesWide$Name1, NamesWide$Name2)) appears to

I have a simple script: #!/bin/bash # index=0 total=0 names=() ip=() while read -r LINE do NODENAME=` echo $LINE | cut -f 1 -d ','` IP=` echo $LINE | cut -f 2 -d ','` names[index]="$NODENAME" ip[index]="$IP" index=`expr index+1` total=`expr total+1` done <<< $(cat list.txt) simple file: more list.txt name1,ip1 name2,ip2 name3,ip3 output when

Hi! I suspect there must be an easy way to access components of a data frame by name, i.e. the input should look like "name1 name2 name3 ..." and the output be a data frame of those components with the corresponding names. I ´ve been trying for hours, but only found the long way to do it (which is not feasible, since I have lots of components to select):

Hi, I have a question about using lm on matrix, have to admit it is very trivial but I just couldn't find the answer after searched the mailing list and other online tutorial. It would be great if you could help. I have a matrix "trainx" of 492(rows) by 220(columns) that is my x, and trainy is 492 by 1. Also, I have the newdata testx which is 240 (rows) by 220 (columns). Here is

Dear All, I need some help arranging data that was imported. The imported data frame looks something like this (the actual file is huge, so this is example data) DF: IDKey X1 Y1 X2 Y2 X3 Y3 X4 Y4 Name1 21 15 25 10 Name2 15 18 35 24 27 45 Name3 17 21 30 22 15 40 32 55 I would like to create a new data frame with the following NewDF: IDKey X Y Name1 21 15 Name1

Hi, I am trying to write a function to automate multiple graph generation. My data looks like: Table of numeric values with the following headers: timeM1 statusM1 xM1 timeM2 statusM2 xM2 timeM3 statusM3 xM3 1 2 3 4 5 6 Where M1,M2, M3 hve no similarity except they have a max string length of 7. Examples are mcw0045, adl0003, lei0101. Now, what I want to do is Function(M1, M2,

I may be missing something but using the plain old c() combine function seems to work fine: df <- data.frame(left = 1:5, right = 6:10) df.combined <- data.frame(comb = c(df$left, df$right)) df left right 1 1 6 2 2 7 3 3 8 4 4 9 5 5 10 df.combined comb 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 -----Original

Hi, You were on the right track using stack(), but you just pass the entire data frame as a single object, not the separate columns: > stack(NamesWide) ? values ? ind 1 ? ?Tom Name1 2 ? Dick Name1 3 ?Larry Name2 4 ?Curly Name2 Note that stack also returns the index (second column of 'ind' values), which tells you which column in the source data frame the stacked values originated

Dear All, Just start to use the long expected R, my focus will be doing clustering on microarray data, just wonder, anyone can show me any references to conquer the steep learning curve? Thanks! Best regards, Baoqiang Cao

Hi I have a character vector with thousands of names which looks like this: > V=c("Fred", "Mary", "SAM") > V [1] "Fred" "Mary" "SAM" > class(V) [1] "character" I would like to change it to a list: > L=as.list(V) > L [[1]] [1] "Fred" [[2]] [1] "Mary" [[3]] [1] "SAM" but I need to

Here is a small reproducible example: data <- structure(list(V1 = structure(1:3, .Label = c("Name1", "Name2", "Name3"), class = "factor"), V2 = structure(c(1L, 3L, 2L), .Label = c("nam1", "name-1", "name_12"), class = "factor"), V3 = structure(1:3, .Label = c("nam2", "nam_34",