similar to: cbind'ing multivariate ts objects

Hello! Recently I got report that my package mar1s doesn't pass checks any more on R 3.0.2. I started to investigate and found the following difference in multivariate time series handling in R 3.0.2 compared to R 2 (I've checked on 2.14.0). Suppose I wish to calculate seasonal component for time series. In case of multivariate time series, I wish to process each column independently.

Hello! I use R 2.8.1 under Debian GNU/Linux. I've run into a problem including R pdf figures into LaTeX document. To reproduce: 1) Execute the following minimal R script: pdf('fig.pdf', family = 'URWTimes', width = 5, height = 5) plot(rnorm(10), main = '????', xlab = '????????', ylab = '????????') dev.off() embedFonts('fig.pdf') 2) Open

Hi group! Suppose I have 2 matrices A and B of equal dimensions. I want to apply a function f to all corresponding pairs of rows from A and B in an efficient manner. Basically, I want mapply(f, data.frame(A), data.frame(B)) but for rows. How do I do it? Thanks, Andrey

I am wondering if people on the list could recommend books that they have found helpful about programming concepts and style? I often find that students write R programs by copying existing code but could really benefit from the understanding of more general programming ideas. An example would be to avoid writing functions which attempt to modify their parameters. Another principle would be

Hello group! Is there a package that allows to fit smooth *periodic* splines to data? I'm interested in a function which combines the functionality of smooth.spline and splines::periodicSpline. Thanks, Andrey

In one of my scripts I used plot.acf function, but I had to modify it a little to suit my needs. Although my modifications are minor, I believe some people might benefit from it. The problem: currently, in cross-correlation plots main title captions are constructed of 2 names separated by '&' symbol. Such captions occupy too much horizontal space and usually don't fit in plot. A

Hi I'm having a problem using the zoo library and I can't see what I'm doing wrong. For example setting up the data > t1 = zoo (matrix (1:12, nrow = 3), order.by = as.Date (c("2008-08-01","2008-08-02","2008-08-03"))) > colnames (t1) = c ("A", "B", "C", "D") > t2 = zoo (matrix (1:12, nrow = 3), order.by =

Hello, I am trying to estimate a multivariate regression of Y on X with regression splines. Y is (nx1), and X is (nxd), with d>1. I assume the data is generated by some unknown regression function f(X), as in Y = f(X) + u, where u is some well-behaved regression error. I want to estimate f(X) via regression splines (tensor product splines). Then, I want to get the predicted values for some new

Dear R-help, I wonder if you could give me some suggestions in how to do a union join of two data frames as follow: -> union join the common column, and insert a 0 if one is missing. I made a function to perform the following, and I know it may not that quite welly written, but it works. Any suggestions are welcome, many thanks. Anthony > q1 =

Dear R-users I've simulated a longitudinal multivariate normal data set from which I've simulated missing-patterns such as MCAR MAR and a simple kind of non-MAR. I've imputated the values so I now have 'complete' data sets. I'm trying to perform a T2-test as done in the multivariate case under th enormal assumption. Is there something I've to think about when performing

I have a suggestion for kernapply for ts objects. When we choose the option circular=F, the returned series don't have the correct dates. The removed dates are all at the beginning instead of half at the beginning and half at the end. It is particularly useful when we need to smooth the series (or remove a trend using a filter) before estimating a model (like in macroeconomics) or simply

Hi all, I bumped into this awkward zoo behaviour. I'd be half tempted to call it a bug, what do you think? It's annoying to work around it :( I wonder if this was the behaviour of older zoo versions, I can't remember coming across this sort of thing... > version _ platform i386-pc-solaris2.10 arch i386 os solaris2.10 system i386,

I want to calculate the probability that a group will include a particular point using the squared Mahalanobis distance to the centroid. I understand that the squared Mahalanobis distance is distributed as chi-squared but that for a small number of random samples from a multivariate normal population the Hotellings T2 (T squared) distribution should be used. I cannot find a function for

Hello group! I mantain my own package cmrutils which is available under the GPL: http[s]://aparamon.msk.ru/svn/study/R-packages/cmrutils I don't want to put it to CRAN yet because it mostly consists of specialized helper functions which are presumably not valuable for other people. But I think 2 of the functions are general and useful enough to share the code. Do you think it is worth to

Full_Name: Yves Rosseel Version: 2.2.1 OS: Submission from: (NULL) (157.193.116.152) The code below sketches a possible implementation of a function 'mlh.mlm' which I think would be a good complement to the 'anova.mlm' function in the stats package. It tests a single linear hypothesis of the form H_0: LBT'= 0 where B is the matrix of regression coefficients; L is a matrix

The data set consists of two sets of matrices, as labelled by the columns, T's and C's. > xy x T1 T2 T3 T4 T5 C1 C2 C3 C4 C5 [1,] 50 0.00 0.00 33.75 0.00 0.00 0.00 36.76 0.00 35.26 0.00 [2,] 13 34.41 0.00 0.00 36.64 32.86 34.11 35.80 37.74 0.00 0.00 [3,] 14 35.85 0.00 33.88 36.68 34.88 34.58 0.00 32.75 37.45 0.00 [4,] 33 34.56

This seems like a FAQ, but I can't figure it out. I have a mv ts object: R > tsp(pg) [1] 1982 2003 1 R > dim(pg) [1] 22 12 and a univariate ts: R > tsp(rw) [1] 1690 1996 1 Yet, when I try to intersect them: R > tsp(ts.intersect(rw, pg)) [1] 1982 2176 1 the process goes awry. How to I get rw and pg to be one ts that runs from 1982 to 1996 and has 13 univariate time

Paul wrote to R-devel : PaulG> ts() is giving me problems on Solaris: PaulG> R : Copyright 1999, The R Development Core Team PaulG> Version 0.64.0 (April 8, 1999) PaulG> ... >> z <- ts(matrix(1:20,10,2), start=c(1969,1), frequency=12) >> max(abs(z-z)) PaulG> Error: invalid time series parameters specified >> traceback()

Dear all, Please suggest me how can I do it. I have a matrix which look like following: x1 x2 x3 t1 .01 0.3 0 t2 0 0.1 0.01 t3 0 .01 .01 t4 0 0 t5 5 0 0 t6 0 0 0 t7 0 0 0 t8 0 0 0 t9 0.6 0 0 t10 0 0 0.66 t11 0 0.6 0.11 t12 0 0.4 0 I want to sort decreasing order in each column based on rows. and then to display only those rows which has a value. The expected out put matrix will

This message is in MIME format --_=XFMail.1.3.p0.Linux:990702182137:16900=_ Content-Type: text/plain; charset=us-ascii There was some discussion a while back on R-devel between Ross Ihaka, Paul Gilbert and myself about row subsetting in time series. I think the consensus was that "[.ts" should not try to coerce its result back to a time series object (which is underlying the problem