similar to: Why a list of NULL's are reduced to NULL?

I don't find a function to print a string to file. Would somebody let me know what function I should use?

You are right that there are no NAs in the practice data. But there are NAs in the moving average data. To see this, break your work into two separate steps, like this: tnr.ma <- ma(dat3[1:28], order=3) TNR_moving_average <- forecast(tnr.ma, h=8) I think you will find that the warning comes from the second step. Print tnr.ma and you will see some NAs. -Don -- Don MacQueen Lawrence

Luca, If speed is important, you might improve performance by making d0 into a true matrix, rather than a data frame (assuming d0 is indeed a data frame at this point). Although data frames may look like matrices, they aren?t, and they have some overhead that matrices don?t. I don?t think you would be able to use the [[nm]] syntax with a matrix, but [ , nm] should work, provided the matrix has

Is there a package or a command that does window aggregation like select sum(col1) over (partition by col2, col3 order by col4 rows between unbounded preceding and current row) as sum1 from table1 ; the above is Netezza syntax, but Postgre has same capability. Stephen B [[alternative HTML version deleted]]

Some years ago, if I recall correctly, I learned of a package that included a function that would write a plot to a file so that one could associate hyperlinks with elements of the plot, such as points. Then, when the plot was displayed in a browser, one could click on (for example) a point, and jump to wherever the hypelink pointed. I don't remember then name of the package or function,

Hi I have a vector like that readCsvFile$V1  [1]  30  31  32  33  34  35  36  37  38  39 310 311 312 313 314 315 316 317 318 [20] 319 320 321  20  21  22  23  24  25  26  27  28  29 210 211 212 213 214 215 [39] 216 217 218 219 220 221 222 223  40  41  42  43  44  45  46  47  48  49 410 [58] 411 412 413 414 415 416 417 418 419 420 421 and I am looking to find where the number 31 is located. So I

Hi Don, wow, you are so right. I picked that piece up from the bloggers tutorial and since I am R naive yet, I thought it was all one step moving_average = forecast(ma(tdat[1:31], order=2), h=5) Truly, I usually print and check at every step I can, as painful as it is sometimes. Great lesson for this novice usR. So the first and last values are NA in each case? Do you know why? Should I replace

My guess would be that if you inspect the output from ma(dat3[1:28], order=3) you will find some NAs in it. And then forecast() doesn't like NAs. But I can't check, because I can't find the ma() and forecast() functions. I assume they come from some package you installed; it would be helpful to say which package. -Don -- Don MacQueen Lawrence Livermore National Laboratory 7000

Hello Don, thank you for your response. I appreciate your help. I am using the forecast package, originally I found it following a forecasting example on bloggers.com https://www.r-bloggers.com/time-series-analysis-using-r-forecast-package/ And subsequently located the complete pdf https://cran.r-project.org/web/packages/forecast/forecast.pdf Since I created this practice data using the

Does R have a comparison operator similar to the Like function, for example: a<-"Is a Fish" b<-"Fish" if(b in a){c<-TRUE} Michael R Howard Micron Technology Inc. Boise ID. Fab C Engineering Software (FCES) Software Engineer

I have found that order() fails in a rather arcane circumstance, as in this example: > foo <- I( c('x','\265g') ) > order(foo) Error in if (xi > xj) 1L else -1L : missing value where TRUE/FALSE needed > foo <-c('x','\265g') > order(foo) [1] 1 2 > sessionInfo() R version 3.1.1 (2014-07-10) Platform: x86_64-apple-darwin13.1.0 (64-bit)

Hi R users, I have some data points (Xi, Yi), and they may follow such a pattern Yi = cCOS(Xi) + d, how to find the c and d in R? which function to use? Also, how to get the R2 and p value for this correlation? Thanks for any kind of help. [[alternative HTML version deleted]]

Thank you for both replies Don & Rui, The very issue here is that there is a search that needs to be done within a text field and I agree with Rui later comment that regexpr might indeed be the time consuming piece of code. I might try to optimise this piece of code later on, but for the time being I am working on the following part of building a neural network to try indeed classifying some

I have written a series of C modules that produce various custom (technical analysis) graphs when presented with a financial time series. The code was developed on the Win2K and so makes many now level function calls to the GDI etc, and is very tightly wedded to the Win2k windowing system. I notice however, that most of the graphing functionality in R (at least on the Windows OS) is handled

Hi, I use a vector of data to draw the histogram, but it is different from the graph by SAS. Can you check it for me please? b is a column vector of 4332 hist(b,probability=T,breaks=30,col='lightblue',ylim=c(0,1)) rug(b) When I used rug, I find the records are smaller than 4332. I don't know where I did wrong. Thanks. -- Yi Du [[alternative HTML version deleted]]

This looks like a bug? Unable to use scan(pipe()) while profiling. I have no idea whether this version of R violates the "do not use `Rprof' in an executable built for profiling" warning in ?Rprof. Thanks -Don > version _ platform powerpc-apple-darwin1.4 arch powerpc os darwin1.4 system powerpc, darwin1.4 status Patched major 1 minor 3.1 year

Hi All : I am attempting tomove a large amount of code from Splus to R and I was hoping that there was an equivalent in R of the Splus functions timeSeq and timeDate ? I did an RSiteSearch but nothing came up ? If the equivalent functions are part of some package, that's fine. Thanks a lot. Mark

Thanks it worked for me. I wanted to plot days since planting on x-axis 1 and years on x-axis 3. LAI_simulation$Date <- as.Date( LAI_simulation$Date, '%Y/%m/%d') LAI_simulation$Date <- as.integer(LAI_simulation$Date - as.Date("2009-10-07")) plot(LAI~Date,data=LAI_simulation,xlab="Days since Oct, 7,

I need to merge three datasets and don't know how. If I were using SQL, I would use df3, look up the characteristics of each date in df1 and the value for each observation in df2. df1 - unique list of Dates and characteristics of those dates Date, YYYYMM, YYYYWW, DOW df2 - the raw data Date, Place, Value df3 - all posibile combinations of Date + Place (via

I forgot to explain why my suggestion. The logical condition returns FALSE/TRUE that in R are coded as 0/1. So all you have to do is coerce to integer. This works because the ifelse will return a 1 or a 0 depending on the condition. Meaning exactly the same values. And is more efficient since ifelse creates both vectors, the true part and the false part, and then indexes those vectors in