similar to: How to read in this data format?

Hi, this should be an easy one, but I can't figure it out. I have a vector of tests, with their units between brackets (if they have units). eg tests <- c("pH", "Assay (%)", "Impurity A(%)", "content (mg/ml)") Now I would like to hava a function where I use a test as input, and which returns the units like: f <- function (x) sub("\\)",

Hi, I have to search in an online db for registered manufacturers of raw materials. Can I use R for the following: I have a list with monograph numbers eg: l <- c(198, 731,355) Now I want to make a dataframe, containing the monograph number and the information listed under COS: Certificate holder, certificate number, Status, Type Is this possible with R? kind regards Bart -- View this

Hi, I'm a database admin for a database which manage chromatographic results of products during stability studies. I use R for the reporting of the results in MS Word through R2wd. But now I think I need your help: suppose we have the following data frame: ID rrt Mnd Result 1 0.45 0 0.10 1 0.48 0 0.30 1 1.24 0 0.50 2 0.45 3 0.20 2 0.48 3 0.60 2 1.22 3 0.40 3

Hi, I'm trying to fit a model which has a response bias, but also a day to day bias. If I try to simulate the data, I don't get the right values with optim, and also I can't use the function to give a prediction interval. My simulated data are: DF <- as.data.frame(cbind(x=rep(1:10,2),dag=rep(1:2,each=10))) bias <- c(-0.2,0.5) DF$y <- ((DF$x-0.1) * 5)+2 +

Hi, I have a problem with fitting a model: I made a dataframe with this data: a <- 1:3 b <- 1:3 c <- c(3, 2, 3, 2, 1, 2, 3, 2, 3) df <- expand.grid(a,b) df$result <- c names(df) <- c("A","B", "result") Although I can make a graph of the data: require(lattice) wireframe(result~A*B, data=df) I can't get a model to

Hi, I have an integer which is extracted from a dataframe, which is sorted by another column of the dataframe. Now I would like to remove some elements of the integer, which are near to others by their value. For example: integer: c(1,20,2,21) should be c(1,20). I tried to write a function, but for some reason, somethings won't work x <- 1:20 near <- function(x,th) { nr <-

Hi, I have the following dataframe: ID Dates 1 16-07-01 06-10-95 2 24/01/02 06-10-95 3 16/01/02 16/08/94 12/01/91 And I would like to extract the dates, but couple the ID's to the right dates, eg: ID Dates 1 16-07-01 1 06-10-95 2 24-01-02 2 .... I have no clue about how to get started, looks something for the

I have a data set like the following: subject visit x1 1 1 0.5 1 2 1.2 1 3 0.7 2 1 0.4 2 2 0.6 2 3 1.0 ..... where x1 is the interval between the two visits. Now I want to calculate the cumulative intervals since the beinging, for example subject visit x1 cum 1 1 0.5 0.5 1 2 1.2 0.5+1.2 1 3 0.7 0.5+1.2+0.7 2 1 0.4 0.4 2 2 0.6 0.4+0.6 2 3 1.0 0.4+0.6+1.0 ..... is there an easy to generate the

Hi, Maybe this is more a programming questions than a specific R-project question, but maybe there is someone who can point me in the right direction. I have a picture of cirkels which I took with a digital camera. Now I want to use the diameter of the cirkels on the picture for analysis in R. I can use pixmap to import the picture, but how do I find the outside cirkels and calculate the

Hi, I want to make a data frame which contains the positions of some searched values in another data frame. Like: Dataframe 1: 1 2 3 4 1 2 3 4 2 3 4 1 2 3 4 2 4 1 2 3 2 3 4 1 Let's say I searched on "4", then Dataframe 2 should contain: x y 1 4 1 8 2 3 2 7 3 1 3 7 I have written a routine, but it seems to me that it isn't that perfect: x<- 0

Hi, I want to use Maximum likelihood to estimate the parameters from my regression line. I have purchased the book "Applied linear statistical models" from Neter, Kutner, nachtsheim & Wasserman, and in one of the first chapters, they use maximum likelihood to estimate the parameters. Now I want to tried it for my self, but couldn't find the right function. In the book, they give

Hi, I have constructed a dataframe as follows: Oil <- rep(c("Oil1","Oil2","Oil3"),8) Comp <- rep(rep(c("C1","C2"),c(4,4)),3) Mth <- rep(c("M1","M1","M2","M2"),6) Meas <- rep(c(1,2),12) Result <- rnorm(24,mean=100, sd=5) df <- data.frame(Oil, Comp, Mth, Meas, Result) The same compound

All Is there an R command to produce error bars around a plotted point. Crawley's book uses the command error.bar() but my version of R rejects it. Must be an S+ command(?). Thanks REX [[alternative HTML version deleted]]

Hi, I'm currently doing some analyses on time of failure of a product. I found on the internet some article about the Arrhenius equation, and I can calculate the results with R. Equation: k=A*exp(-Ea/R*T) I can fit a model with lm for this purpose, so far no problem. But for the confidence interval, how can I use the Weibull distribution? Or should I use the weibull distribution at all? Or

Hi, I'm trying to match peaks between chromatographic runs. I'm able to match peaks when they are chromatographed with the same method, but not when there are different methods are used and spectra comes in to play. While searching I found the ALS package which should be usefull for my application, but I couldn't figure it out. I made some dummy chroms with R, which mimic my actual

Dear R experts, I've realized that it might not be possible to define a negative SELCET statement in a SQL call so now I'm looking for the smoothest way to generate a list of what I would like from my large database by first pulling all the names with a query like this "SELECT top 1 * FROM your_table" (thank you Bart Joosen for the idea) and then subtract the variables I am not

Hi r-users,   I would like to extract the data that match.  Attached is my data: I'm interested in matchind the value in column 'intg' with value in column 'rand_no' > cbind(z=z,intg=dd,rand_no = rr)             z  intg rand_no    [1,]  0.00 0.000   0.001    [2,]  0.01 0.000   0.002    [3,]  0.02 0.000   0.002    [4,]  0.03 0.000   0.003    [5,]  0.04 0.000   0.003    [6,] 

Hi All, recently I used Design Expert for some Design Of Experiment work. I was happy with the interface to select which effects I want to see in my experiment, and which not. For example: I can select of course my main effects, but also if I want to see interaction A:B, B:C, A:B:C,but not A:C. This was very interessting as you can end up with fewer runs, especially in cases of 10 factors with

Hi, I have a function of the second grade, with 2 parameters: y~A^2 + A + B^2 + B The response y is a measurement for the precision of the analytical method, where A en B are method parameters. As its neccesary to keep the precision of the analytical methad as good as possible, its usefull to optimize A en B to keep y as low as possible. But how can I do this with R? I have searched the

Hi, I tried on this, but couldn't figure it out: Suppose I have a dataframe as follows: dat <- data.frame(Day=rep(rep(c(1,2), each=4),2), Animal = rep(c(1,2), each=8), Count=c(rnorm(8, 100), rnorm(8,90))) 2 animals are being examined on 2 different days. Count is the result. Now I need to point out whether or not there is a difference between the days. I did this by an ANOVA test, while