similar to: Fit non-lineair 3D Data

Dear R specialists, I'm working with time series and want to investigate the relationship between two time series by correlation analysis or by fitting a gen. lineair model to the plot of x(timeserie1) and y(timeserie2). Lin1 <- data.frame( Nr = c(1:lengte), NDII = window(ts.mNDII,c(1998,10),c(2003,11)), InvERC = window(Inv.ERC,c(1998,10),c(2003,11)) )

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

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 recieved an ascii file, containing following information: $$ Experiment Number: $$ Associated Data: FUNCTION 1 Scan 1 Retention Time 0.017 399.8112 184 399.8742 0 399.9372 152 .... Scan 2 Retention Time 0.021 399.8112 181 399.8742 1 399.9372 153 ..... I would like to import this data in R into a dataframe, where there is a column time, the first numbers as column names, and the

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 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 <-

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, 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

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, 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

With this example set.seed(123) A <- matrix(runif(40), nrow = 8) y <- 1:nrow(A) A.laqr <- qr(A, LAPACK=TRUE) both qr.qy(A.laqr,y) and qr.qty(A.laqr,y) give the respective error messages Error in qr.qy(A.laqr, y) : 'b' must be a numeric matrix Error in qr.qty(A.laqr, y) : 'b' must be a numeric matrix However when Lapack is not used as in A.liqr <- qr(A,

Dear R people, I do not have much knowledge about linear algebra but currently I need to understand what the function qr.qty is actually doing. The documentation states that it calculates t(Q) %*% y via a previously performed QR matrix decomposition. In order to do that, I tried following basic example: m<-matrix(c(1,0,0,0,1,0,0,0,1,0,0,1),ncol=3) # 4x3 matrix

Hello, I'm using MySQL realtime Call Queues (table /queues/ and table /queue_members/). I would like to ring the members of the call queue in a certain order. Therefore I use ring strategy /lineair /and I put the members into the table /queue_members/ in the order in which they have to be rang. So I have the queue : | name | musicclass | announce | context | timeout |

I am having some difficulty understanding the implication of lazy evaluation mixed with DUP=F in a .Fortran call. In qr.qty from base DUP is not used as an argument so defaults to T. I am calling qr.qty with a very large array and would like to set DUP=F in the .Fortran call so that qr.qty would be defined as copied below. Is there some risk that a variable used as the argument in the original

Hi list, I tried to use nls to do some nonlinear least square fitting on my data with 340 observations and 10 variables, but as I called nls() function, I got this error message: Error in qr.qty(QR, resid) : 'qr' and 'y' must have the same number of rows Then I traced back a little bit into nls() function, the error seemed to happen when calling nlsiter() internal function, but

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

Dear R-experts! I have y(x) data, dim(y) == dim(x) == c(2000, 2) I'd like to fit them with nls: fit.result <- nls ( y ~ f(x, p1, p2, p3), start = list(p1 = ... , p2 = .. , p3 = ..) ) Actually I want to fit y[,1] ~ x[,1] and y[,2] ~ x[,2] *simulaneously*, with the same parameters set {p1, p2, p3}. I tried to feed R tha above formula, R errors with: