similar to: another question: how to delete one of columes in two ones with high correlation(0.95)

e.g. a= a b c d e 1 1 1 3 1 1 2 1 2 3 4 5 3 1 3 3 8 3 4 1 4 3 3 5 5 1 1 3 1 1 I want to delete colume a and colume c, because they have the same values in every row, then ,I want to get this data.frame . b= b d e 1 1 1 1 2 2 4 5 3 3 8 3 4 4 3 5 5 1 1 1 the following is my code but it's wrong. rm(list=ls()) a=c(1,1,1,1,1); b=c(1,2,3,4,1); c=c(3,3,3,3,3);

Hi, I have a vectors x and z, for example, x <- 0:20 z <- round(runif(20,1,7)) y <- 0.5 and I want to display z as an image. However if I then call image() with a vector image(x,y,t(z),zlim=c(1,7),col=heat.colors(7),xlab="Year",ylab="Action",yaxt="n",xaxs="r",yaxs="r") then I get the error Error in image.default(x, y, t(z), zlim =

Each Timesheet has an employee. An employee has a division and a location. I want to find all the timesheets with a status of 2. I then iterate over the timesheet collection and print the timesheet name, employee name, employee divison name, and employee location name. Like so: for t in Timesheet.find(:all,:conditions=>"status=2",:include=>:employee) puts timesheet.date

violating.runs I read from the news cran.r-project.org/doc/Rnews/Rnews_2004-1.pdf that the criteria for the violating is 5 but 1)I cannot find "5" in the code of the function. Where is the "5" ? 2)What is the easiest way to change it ? 3)Is there any more criterias made somewhere ? Yours sincerelly, Tommi Viitanen

Dear all, I have two different data frames, that have two common variables: date and sample. Here is a small extract of both of them > head(traffic) datet sessiont samplet buddleiat 1 07-08-2012 1 1 1 2 07-08-2012 1 1 1 3 07-08-2012 1 1 1 4 07-08-2012 1 2 3 5 07-08-2012 1 2

In my disk C:/ have a a.csv file, I want to read it to R, importantly, when I use x=read.csv("C:/a.csv") ,the x format is data.frame, I want to it to become matrix format, how can I do it ? thank you! -- View this message in context: http://old.nabble.com/how-can-I-convert-.csv-format-to-matrix----tp26156643p26156643.html Sent from the R help mailing list archive at Nabble.com.

I want to get the plot like this, http://n4.nabble.com/file/n1839303/%25E9%25A2%2591%25E7%258E%2587%25E5%2588%2586%25E5%25B8%2583%25E5%259B%25BE%25E6%25A0%2587%25E5%2587%2586.jpg %E9%A2%91%E7%8E%87%E5%88%86%E5%B8%83%E5%9B%BE%E6%A0%87%E5%87%86.jpg not this, http://n4.nabble.com/file/n1839303/R.jpg R.jpg and the data here, thank you! http://n4.nabble.com/file/n1839303/y1.txt y1.txt can R

Dear all, My double for loop as follows, but it is little efficient, I hope all friends can give me a "vectorized" program to replace my code. thanks x: is a matrix 202*263, that is 202 samples, and 263 independent variables num.compd<-nrow(x); # number of compounds diss.all<-0 for( i in 1:num.compd) for (j in 1:num.compd) if (i!=j) { S1<-sum(x[i,]*x[j,])

I want to split my whole dateset to training set and test set, building model in training set, and validate model using test set. Now, How can I split my dataset to them reasonally. Please give me a hand, It is better to give me some R code. and I see some ways like using SOM to project whole independents to 2-dimensions and find some to be training set and others are test set. like below. I

Dear Sir I have successfuly downloaded R package. Kindly let me know where i will get _/*user mannual*/_ for the same. awaiting a prompt reply with regards Pankaj @#@#@#@#@#@#@#@#@#@#@#@#@#@#@#@#@#@#@#@#@#@#@ Pankaj Kumar Research Scholar Climatology & Hydrometeorology Divison Indian Institute Of Tropical Meteorology Homi Bhabha Road, Pune-411008 India Phone No. +91-20-5893600 Ext. 361

Dears, [Rails 1.0.0] I''m working with a legacy schema, and around my 20+ models i''ve used some AR constructs. They are based on a finder_sql doing some dirty sql and using #{id} from the ''pivot'' model for extracting data in other tables. like : class Division < ActiveRecord::Base set_table_name "legacy_division" set_primary_key

This topic refer to independent variables reduction, as we know ,a lot of method can do with it,however, for pre-processing independent varibles, a method like the sentence below can reduce many variable, How can I understand it? what is significant correlation at 5% level, what is the criterion? P value?or what? "Independent variables whose correlation with the response variable was not

http://r.789695.n4.nabble.com/file/n3060425/fig_1.png fig. 1 http://r.789695.n4.nabble.com/file/n3060425/fig_2.png fig. 2 I want to the picture like the above one, the origin crossover together, while the following picture can be obtained by default and the origin is detached, but throgut pulling the window, I can get the one like fig_1. Now, I want to know how to use the code to obtain

hello, my problem is like this: now after processing the varibles, the remaining 160 varibles(independent) and a dependent y. when I used PLS method, with 10 components, the good r2 can be obtained. but I donot know how can I express my equation with the less varibles and the y. It is better to use less indepent varibles. that is how can I select my indepent varibles. Maybe GA is good

now I am learining random forest and using random forest package, I can get the OOB error rates, and test set rate, now I want to get the training set error rate, how can I do? pgp.rf<-randomForest(x.tr,y.tr,x.ts,y.ts,ntree=1e3,keep.forest=FALSE,do.trace=1e2) using the code can get oob and test set error rate, if I replace x.ts and y.ts with x.tr and y.tr,respectively, is the error rate

Usage data(gasoline) Format A data frame with 60 observations on the following 2 variables. octane a numeric vector. The octane number. NIR a matrix with 401 columns. The NIR spectrum and I see the gasoline data to see below NIR.1686 nm NIR.1688 nm NIR.1690 nm NIR.1692 nm NIR.1694 nm NIR.1696 nm NIR.1698 nm NIR.1700 nm 1 1.242645 1.250789 1.246626 1.250985 1.264189 1.244678 1.245913

I am learning the package "caret", after I do the "rfe" function, I get the error ,as follows: Error in `[.data.frame`(x, , retained, drop = FALSE) : undefined columns selected In addition: Warning message: In predict.lm(object, x) : prediction from a rank-deficient fit may be misleading I try to that manual example, that is good, my data is wrong. I do not know what

Hi?all friends, Please help me understand this sentence below: ?From this set, 858 columns not significantly correlated with the response variable TBG at the 5% level were removed, leaving a set of 390 columns.? and ? the F-test's value for the one-parameter correlation with the descriptor is below 1.0? is equal?? I want to perform this above sentence with R, how can I do? I just try

Dear R experts: I have following data structure: student id, exam time and score. I want to create three new columes: 1 st before, 2nd before and 3rd before. For example, for student 1's 4th exam score is assumed to be influenced by his previous three cloest scores, which are 6, 9, and 10 in that order. For student 2's 5th exam score is assumed to be inflenced by her previous cloest

rm(list=ls()) yx.df<-read.csv("c:/MK-2-72.csv",sep=',',header=T,dec='.') dim(yx.df) #get X matrix y<-yx.df[,1] x<-yx.df[,2:643] #conver to matrix mat<-as.matrix(x) #get row number rownum<-nrow(mat) #remove the constant parameters mat1<-mat[,apply(mat,2,function(.col)!(all(.col[1]==.col[2:rownum])))] dim(yx.df) dim(mat1) #remove columns with numbers of