similar to: How to see how a function is written

Dear list, As can be seen below, adding a NA to the y values in a call to isoreg results in a segfault. ir4 <- isoreg(1:10, y4 <- c(5, 9, 1:2, 5:8, NA, 8)) Adding missing values to the x values, on the contrary, gives an error, but maybe the error message could be tailored to this particular situation. y <- c(5, 9, 1:2, 5:8, 3, 8) x <- c(1:9, NA) isoreg(x, y) ## error message:

Before re-inventing the wheel I would like to ask: does anyone know about an optimizer in R which can reliably identify which value of X (Xopt) leads to Y (Yopt) closest to Ytarget in Y <- MonotoneStepFun(X) optionally with the restriction that Yopt <= Ytarget (at least if any Y <= Ytarget, otherwise any Yopt > Ytarget would be the preferred answer) If none is known, I will write

Full_Name: Petr Klasterecky Version: 1.8.1 OS: Windows XP, Linux Submission from: (NULL) (195.113.27.212) The isoreg() function causes R to crash when called repeatedly. Consider the following simple script: { library(modreg) N <- 10 x <- rnorm(N) print("Original x values:") print(x) for(n in (1:N)){print(y <- isoreg(x[1:n])$yf)} } I am able to run (call) it several

I believe there is a memory leak in isoreg in the current version of R, as I believe the following shows > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 120405 3.3 350000 9.4 350000 9.4 Vcells 78639 0.6 786432 6.0 392463 3.0 > for(k in 1:100) { + + y <- runif(10000) + isoreg(x,y) + } > rm(x) > rm(y) > gc() used (Mb) gc

Hello everyone, I have a plot and I want to but a (formatted) box containing text and numbers, say: Mean: 0.1 St.Deviation: 1.1 Skewness: 1.1 Kurtosis: 0.5 I know there is a way to do this, there is a function in some library, but it's been years since I used this function, and I do not remember where I found it. Could anyone help out? Thank you in advance! Sergey -- Kniven sk?rpes bara

Hello, everyone I wonder if there is in R somewhere a function similar to cumsum(). The function calculates a statistic (say mean or standard deviation) buy adding consequtively one more data point. So, say I have a timeseries of 100 observations. I start by calculating mean of first 30 observations Then I add one observation and calculate mean of 31 observations Then I add one more observation

Hello, For my functions I want to create output similar in appearance to that of what you get when you print a summary of lm model: Residuals: Min 1Q Median 3Q Max -0.209209 -0.043133 0.001793 0.044105 0.234750 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.981762 0.004089 240.103 < 2e-16 *** Factor 1

Hello, I have an Excel file on a drive and I extract data from it into R session. Once I have extracted the data, I want to delete that Excel file from the drive. Can I do that from within R, please? Thank you for help! Regards, Sergey

Dear members of R forum, Say I have a list: L <- list(1:3, 1:3, 1:3) that I want to turn into a matrix. I wonder why if I do: do.call(cbind, L) I get the matrix I want, but if I do cbind(L) I get something different from what I want. Why is that? How does do.call() actually work? I've read in do.call() help file this sentence: "The behavior of some functions, such as

Hello everyone, I have versions 2.7.2 and 2.10.1 installed on a machine that has no access to internet. In 2.7.2 I can use ? to get help on functions, which in 2.10.1 that does not work, all I see is "starting httpd help server...done" and then nothing. Have I downloaded 2.10.1 incorrectly (=forgot to tick some box for local help file repository) or is the internet help now the

Hello, everyone I wonder if it is possible to PHYSICALLY open an Excel file from R. The reason I ask is, I produce regularly an Excel file in R, and then I want to make it look good, so I have a VBA routine in another Excel file that works on the regular Excel file. This formatting file executes VBA code on open, so all I need to do is physically open it (no reading/writing at all). I wonder if

Hello, everyone I have a question. Assume I have the following zoo object: me.la <- structure(c(1524.75, 1554.5, 1532.25, 1587.5, 1575.25, 1535.5, 1550, 1493.5, 1492.5, 1472.25, 1457.5, 1442.75, 1399, 1535.75, 1565.25, 1543.5, 1598.5, 1586.5, 1547, 1561.5, 1504.75, 1503.75, 1483.75, 1468.75, 1453.75, 1410, 1546.75, 1575.25, 1554, 1609, 1597.5, 1558.5, 1573, 1516.25, 1515.5, 1495, 1480, 1465,

Hello, everyone F# is now public. Compiled code should run? faster than R. Anyone has opinion on F# vs. R? Just curious Best, S -- ------- Kniven sk?rpes bara mot stenen.

Hello, everybody Two questions: 1) I am new to maillists, and particularly to r-help maillist. Where specifically do I go online to see my question and answers to it??? If I use the searchable archives, or archives by Robert King, I see my question but not the answers, though I know that at least one persion posted the answer to r-help. Why do not I see the answers? 2) I need to produce 104

Hello, everyone I run Eclipse Ganymede and R 2.7.2 at work. I have one R script file where I open in memory a new xls file (using xlsReadWritePro), call other R scripts, which are in the same folder as the main R script, which get data from an existing xls file, process data, and output results in the xls file which is in memory. That is the idea. But I cannot make it work. First, I do not

Hi, I am trying to use R to mimic what I did in SAS. proc transreg data=x ; model identity(GSI)=monotone(group1); output out=d2 pprefix=M; run; Accroding to SAS documentation, the MONOTONE transfomation algorithm comes from (Kruskal 1964, secondary approach to ties). I have tried ace. it does provide some kind of monotone transformation, but it is not what I expected. Here is how

Hello, everyone I have a piece of code that looks like this: mrets <- merge(mrets, BMM.SR=apply(mrets, 1, MyFunc, ret="BMM.AV120", stdev="BMM.SD120")) mrets <- merge(mrets, GM1.SR=apply(mrets, 1, MyFunc, ret="GM1.AV120", stdev="GM1.SD120")) mrets <- merge(mrets, IYC.SR=apply(mrets, 1, MyFunc, ret="IYC.AV120",

Hello, fellow R-users. Let me describe the setup first. I have a data.frame, a sample of which is reported below: Company.Name Periods Returns MFR.Factor 350 Wartsila Oyj A 1996-07-31 6.82 0.02 351 Custodia Holding AG 1996-07-31 4.15 -0.02 352 Wartsila Oyj 1996-07-31 7.73 0.09 353 GEA Group AG

Hello, everyone! Assume you have this data: data <- structure(c(66.609375, 67.09375, 66.40625, 66.734375, 67.109375, 66.875, 66.09375, 65.921875, 66.546875, 66.140625, 66.140625, 65.65625, 65.875, 65.59375, 65.515625, 66.09375, 66.015625, 66.140625, 66.109375, 66.421875, 1702.7, 1647.7, 1649.4, 1639.9, 1696.4, 1710.9, 1690.2, 1677.9, 1694.4, 1713.9, 1713.9, 1705.4, 1708.4, 1692.9, 1689.6,

Hello, everybody Say I have nm1 <- c(rep(1,10), rep(0,10)) then I can do: diff(nm1) to see where I have shift in value but what if I have nm2 <- c(rep("SPZ8", 10), rep("SPX9", 10)) how can I produce the same ouput as diff(nm1) does, that is zeros everywhere except for one place where SPZ8 changes to SPX9 (there should be 1 there)? What if I have a matrix of characters