similar to: discriminant function analysis

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Dear All, would you please provide your thoughts on the following: let us say I have: a <-c(1,5,8,15,32,69) b <-c(8.5,33) and I would like to extract from "a" the two values that are closest to the values in "b", where the length of this vectors may change but b will allways be shorter than "a". So at the end based on this example I should have the result

Hello, I am brand new in this site as well as in R. Please accept my early apology if it's not the right place to ask such a question. I have the following equation: b=[2(1-a)(1+2a)^0.5]/(1+3a) How can I solve the above equation for 'a' using R? Thanks in advance. KD [[alternative HTML version deleted]]

Dear all, I am a R beginner, and I am looking for a way to do the same thing for all levels of a column in a table. Basically, I have a bunch of protein sequences composed of different amino acid residues, and each residue is represented by an uppercase letter. I want to calculate the ratio of different amino acid residues at each position of the proteins. Here is an example table: Proteins

I have a data in the following form : CIN TRN_TYP 9079954 1 9079954 2 9079954 3 9079954 4 9079954 5 9079954 4 9079954 5 9079954 6 9079954 7 9079954 8 9079954 9 9079954 9 . . . . . . there are 100 types of CIN (9079954,12441087,15246633,...) and respective TRN_TYP first of all, I want this data to be

suppose I have two sets of vectors: x1,x2,...,xN and y1,y2,...,yN. I want N correlations: cor(x1,y1), cor(x2,y2), ..., cor(xN,yN). my sets of vectors are arranged as data frames x & y (vector=column): x <- data.frame(a=rnorm(10),b=rnorm(10),c=rnorm(10)) y <- data.frame(d=rnorm(10),e=rnorm(10),f=rnorm(10)) cor(x,y) returns a _matrix_ of all pairwise correlations: cor(x,y)

Hello all, I cannot seem to figure out this seemingly simple procedure. I want to sort a data frame by a specified character vector. So for : df.. <- data.frame(Season=rep(c("Summer","Fall","Winter","Spring"),4),Obs= runif(length(rep(c("Summer","Fall","Winter","Spring"),4)))) I want to sort the data frame

I have a stupid problem that is currently driving me crazy... Let us suppose that I want to draw a big red square in the middle of my current device (say X11) I tried the following code : pushViewport(viewport(xscale=c(0,1), yscale=c(0,1)), just=c("center", "center")) vp1 <- viewport(x=unit(0.5, "native"), y=unit(0.5, "native"), width=unit(0.4,

Hello, Does the (core) designation in the CRAN Task View indicate packages that provide basic/recommended functionality in that domain? I don't see it documented anywhere on the site. Thanks for your help.

Following the beginning tutorial, I typed help.start() and was given a choice of browsers. I picked chrome but got back that chrome is not found. I cannot seem to change or get rid of it now. I looked at /etc/R/Renviron but don't see anywhere to set browser (R_BROWSER = ${R_BROWSER ...etc) - nothing about chrome. I tried starting as "R_BROWSER= R" - same thing. How do I change the

Hi all, I am looking for a command for doing 2D filtering (rectangular or Gaussian) in R... I have looked at ksmooth, filter and convolve but they seem to be 1D... Any thoughts? Thanks a lot! [[alternative HTML version deleted]]

Hi, is there a way to replicate a data.frame like you can replicate the entries of a vector (with the repeat-function)? I want to do this: x <- data.frame(x, x) (where x is a data.frame). but n times. And it should be as cpu / memory efficient as possible, since n is pretty big in my case. thanks for any suggestions!

Hello :) I'm just starting out with R and would appreciate your help with a couple of problems I am running into. I have used Sys.glob to get a list of all filenames having a particular file extension (in my case, *.txt) I would now like to use this list in the following manner: I would like to use each filename from the list and open that file into a tab separated matrix and proceed. How can

Hi everybody, I would be very grateful if you could give me your thoughts on the following issue. I need to perform Box-Cox (bcPower€) transformation on my data. To do this, I calculated lambda using the function '€powerTransform'€. powerTransform(data) However, I got an error message when performing this function: Convergence failure: return code = 52 I was told by John Fox

WARNING: COMPLETELY OFF TOPIC -- Nothing to do with R. I thought readers of this list might enjoy the following. The link to the full article is at the bottom. I hope this is not "too" inappropriate. ------- Overconfidence in crime statistics doesn?t pay. In a new study, a team of criminologists makes the case that reported crime rates should acknowledge uncertainty in the data. The

1. Minimum Mean Square Estimation (for Multi-Dimensional Linear Regression) 2. Two-Sample Kolmogorov-Smirnov Tests 3. Empirical ANOVA Methods All this to be done on empirical data. I am new to the R world, any help would be appreciated. Thank You, Bill Gilliland Lead Sensor Systems Engineer E303, Tactical Communications, Transport, and Sensors Group: Tactical

Hi! Yesterday I accidentally discovered this: > a <- LETTERS[1:5] > a [1] "A" "B" "C" "D" "E" > > a[1] <- factor(a[1]) > a [1] "1" "B" "C" "D" "E" BUT: > b <- factor(LETTERS[1:5]) > b [1] A B C D E Levels: A B C D E > b[1] <- factor(b[1]) > b [1] A B C D E

Dear Group, I am working with a large dataset where I need to select for each unique id the the unique lastpk row. Here is a sample subject: id wtdt wt lastpk 64050256 2010-09-18 275 2010-09-16 64050256 2010-09-19 277 2010-09-18 64050256 2010-09-20 272 2010-09-18 64050256 2010-09-21 277 2010-09-18 I want the result as:

dear all, I am a student in cs college. I would like to know how to plot infinte number of genes after using the svm. the data set i have consists of x which is a matrix of 39 cancer patients [rows] and 2000 gene names [colmns]. each cell is the value of the gene for a particular patient. there are two types of cancer people representedas factor y. here is the code: library(e1071) #load

Hi there, I am trying to write a tool which involves implementing logistic regression. With the batch gradient descent method, the convergence is guaranteed as it is a convex problem. However, I find that with the stochastic gradient decent method, it typically converges to some random points (i.e., not very close to the minimum point resulted from the batch method). I have tried different ways