similar to: Capture of iterative integration output

Hi All, I've gotten a number of reports from users about gplots::heatmap.2 generating 'node stack overflow' errors. As it turns out, these errors originate in stats:::plotNode, and are triggered when it is passed a dendrogram that is too deeply nested. While increasing the stack size (which is a compile-time option for byte coded functions) can allow a particular instance to

Hi, We have some sample data from the US census, and we know the marginal totals for the population. We need to make the population estimates add up to the correct sums. I have two questions: Is there some package in R which does this adjustment, by any means? Is there some more modern reference for this problem than Deming's 1943 monograph, ``Statistical Adjustment of Data''?

Dear all, I wonder if there are some function or package in R which can do the iterative proportional fitting. In the exponential model f(y1,...yn)=exp(a'yi+b'(yi*yj)+.....+c'(y1*...*yn)+constance), instead of the canonical parameters, I use maginal probability instead of a and log odds ratio instead of b. and for the order higher than 3, I use the canonical way or even assume

I've been asked, and interested myself: Has anybody implemented the above in R or another S language dialect? We are talking about the algorithms / methodology by Wellner, Groeneboom and Jongbloed, e.g., from the following article @Article{Jongbloed:1998:ICM, author = "Geurt Jongbloed", title = "The Iterative Convex Minorant Algorithm for

I have a function that generated list and then from those I need to do some repeated calculation. So I was thinking to put them in another list and call them one after the other. Given that I have 20 of those it was a bit annoying to typing all of them in one command. So I need something to do a recursive addition of a list objet to a list here a small size example A<-list()

I can't for the life of me figure out how to get the roots for this simple (but sovable only iteratively) equation in R: x = z*(1-(1-2/z)^y where x and y are known, and z is unknown. In Matlab, this amounts to: [my.solution] = solve('x = z*(1-(1-2/z)^y') my.solution.real = solution(y-1,y) % bottom line displays non-imaginary solution (last element) Obviously, I'm deeply

Possibly of limited use to the original poster, but of interest more generally, there are a number of tools developed in the 70s for updating the matrix decompositions. There's at least one in my 1979 book "Compact numerical methods for computers" (still in print apparently) -- we didn't have enough space to keep all the data in the HP9830A machine. If there's sufficient

Hi R-helpers, Is it possible that I have the estimates from each step/iteration shown on the computer screen in order to monitor the process while I am using Optim or MaxLik? Thanks for your help. Maomao [[alternative HTML version deleted]]

Dear All, I am trying to iterate an iterative process (i know R is not the best place for so much looping but i have to so tough!) and store the resulting data from each iteration to then be graphed. In simple form the script looks like this for(i in tracks) { a <- (subset(data, data$Id==i)) result.dataset <- function(a, other.arguements) ### this function is the other

Dear all, I have a data frame of 2160 rows and 4320 columns, which I hope to condense to a smaller dataset by finding averages of 6 by 6 blocks of values (to produce a data frame of 360 rows by 720 columns). How would I go about finding the mean of a 6 x 6 block, then find the mean of the next adjacent 6 x 6 block, and so on, until the whole data frame has been covered? One slight twist is that

Hello, How can an interative unit root test be implemented in R? More specifically, given a time series, I wish to perform the Dickey Fuller Test on a daily basis for say the last 100 observations. It would be interative in the sense that this test would be repeated each day for the last 100 observations. Given the daily Dickey Fuller estimates of delta for the autoregressive process d(Y(t))

Hello Instead of reading in group1.txt I want to read in groups1 for the first iteration of i, then groups2 for the second and so on. Obviously I can't use groups(i) but assume there is a way to do this. group<-read.table("C:/Data/April 2005/group1.txt",header=T) thanks in advance Meredith

Dear all I am intrested in making iterative estimation (thro' loop statements) of, say, linear regression model. For this purpose, I have written the following programme and that I have made use of a sample data (viz., exp.txt): ? Programme: ? # Linear regression modelling with sample data (try5.txt) # Repeated estimation through loop statement

Hi, I am pretty new to R. I'm trying run a regression repeatedly, adding a new data point each time, and then storing the predicted Y values. For example, let's say I have 500 data points and I run the regression. I would then like to store the Y value, run the regression again using 501 data points, store the new Y, run the regression with 502 data points, store the Y, and so on. What I

Hi, I'm trying to assign iterative names to variable, but all my attempts have failed. I have a loop, and for every iteration, I need to create a variable, and I'd like to name them iteratively, such as: for(i in 1:10) { x_i <- c(values) } I need it to return ten variables: x_1, x_2, ..., x_10 How can I do it? Thank you very much! Beatriz -- View this message in context:

Hi, I need help! I am trying to iterate an iterative process to do cross vadation and store the results each time. I have a Spatial data.frame, called Tmese > str(Tmese) Formal class 'SpatialPointsDataFrame' [package "sp"] with 5 slots ..@ data :'data.frame': 14 obs. of 17 variables: .. ..$ ID : int [1:14] 73 68 49 62 51 79 69 77 57 53 ... .. ..$

Dear R experts, I have been trying to run an iterative procedure in R and am having some sort of memory build up problem. I am using R1.8.0 on Windows XP. One single iteration of my procedure is coded into a function. This function creates an extremely large matrix of simulated values (actually calls WinBugs which returns simulations), does some calculations with it and returns a single number

Hi, I'm sort of a newbie to using R to deal with array data. I'm trying to create a simple filtering function, which outputs only the rows of a data frame that satisfies a specific criterion. I've set up an iterative loop to apply the condition to each row. I can create a new matrix and use rbind to fill it in row by row in the loop, before writing the whole matrix to file. But

Dear all, The function f() below is a function of m1 and m2, both of which are matrices with 3 rows. The function works sequentially one row after another. So altogether there are three stages. I am trying to update the coding to write a generic function that will work for arbitrary k stages. I am hoping to get some suggestion and help. Thanks so much! Hanna ##x, y are two

Hi, I would like to create data.frame and increment their name to finally merge them. Does anybody has a solution ? Something like that ? n<-6 for (i in 1:n) { m[i]<-data.frame(name,value) m<-merge(m[i]:m[n]) } Nolwenn ******************************************** Nolwenn Le Meur INSERM U533 Facult? de m?decine 1, rue Gaston Veil 44035 Nantes Cedex 1 France Tel: