similar to: Turnpoints (pastecs): How to specify a limit on the number of tur npoints?

Hi I just installed the pastecs package and I am wondering: is there an english (or german) translation of the file pastecs.pdf? If not, is there an explanation somewhere of the object of type 'turnpoints' as a result of turnpoints(), especially the "info" field? Thanks, Rainer -- NEW EMAIL ADDRESS AND ADDRESS: Rainer.Krug at uct.ac.za RKrug at sun.ac.za WILL BE

Good evening to everybody. I have a data of four columns - three of the columns represent date while the fourth is counts. Setting 4000 as my minimum point/value, I wish to find out the number of counts that are less or equal to 4000 and the dates they occur. I have installed pastecs and have been trying to use turnpoints function to do this. I have not been much lucky. I am a still learning. I

Hello, I just notice this: > x <- c(1:4,0:5, 4, 11) > library(pastecs) Loading required package: boot > tp <- turnpoints(x) > extract(tp, no.tp = FALSE, peak = TRUE, pit = FALSE) [1] FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE Warning message: arguments after the first two are ignored in: UseMethod("extract", e, n, ...) >

Hi I have a large dataset which follows a multimodal distribution. And I would like to identify the maxima. As the data is obtained from a stochastic simulation, not all maxima in the data are "real maxima of the dirstribution" but rather small random fluctuations. Unfortunately, it is not possible for me to run more simulations to smooth the obtained distribution. What I am doing

Hi, Here's the problem I ran into: the gmp package has a method for apply() so it masks the base::apply function. With gmp installed, I tried to run the function turnpoints() from the pastecs package. It fails because it calls apply() internally, like this: apply(mymatrix,1,max,na.rm=TRUE) , but the code in the gmp package which sets up the operator overload for apply() strictly

Happy New Year, r-helpers! I am using lowess to smooth a scatter plot, xx<-lowess(xinput,f=.04) #defaults for other args followed by turnpoints(xx$y) #defaults for other args I plot the smoothed result as well as turnpoints (using yy$tppos) on top of raw data plot. Result is exactly as expected, graphically. For another purpose, I calcuate the difference between turnpoints (representing

Hello, To me as a beginner, every problem looks big. Below is what I was asked to do as part of a code that will solve my problem. I have used read.table to read my data into R and assigned the column names with colnames(dat)<- ... . But to go from txt<-" to the last " at the bottom of the table below is what I am unable to do. Could anybody please tell me how to type or arrive at

Good morning once more. My problem of yesterday has been addressed. Having learned a few tricks from that, I wish to ask another question in connection with that. My data is a cosmic ray data consisting of dates and counts. When I plot a graph of counts versus dates, the resultant signal shows a number of maximum and minimum points. These minimum points (turning points) are of interest to me.

In function daystoyears in package pastecs, I get this (wrong?) result with 1995: > daystoyears(1,datemin="1/1/1997",dateformat="m/d/Y") 1997.001 > daystoyears(1,datemin="1/1/1995",dateformat="m/d/Y") 1994.999 Any insights? Thanks Angel

Hi, I'm trying to analyse some time series data on dissolved organic nitrogen. Because it has gaps in it, I try to interpolate (linear) with the regul method from the pastecs package. I have a number of stations with measurement series in a matrix constructed from a data frame with the unstack method (temp) I also used the unstack method to make a similar matrix for the time points

My goal is to remove signals trend without any a-priori knowledge of the trend type, if any. Some signals are very noisy and non-stationary (example attached). I have experimented with a number of techniques. Staring at the results, I can hardly tell which method is best. I am attaching the result of function "local.trend" as I cannot understand it. Nor I can make a sense of the returned

Tom Blackwell wrote: >... >I summarized this to myself as "computed subscripts need explicit >rounding in R, but not in S". Here's the sample code which gave >me different results with R than with Splus. I no longer have >Splus available, so I can't check it again. >look <- (10 * seq(14)) - 76 >chk.1 <- seq(1420)[ 10 * (73.1 + look) ] #

On 10 May 2011 16:10, "Jamie Landeg Jones" <jamie@bishopston.net> wrote: > > > It used to confuzzle sysadmins on SUNos when the mount point was > > 0700. The underlying mode disapeared when the mount was made, but it > > was still being enforced. Suddenly no one but root could use say /usr > > even though it was apparently 0755 > > I remember that

Hello, Could someone help me to explain the VERY big difference in applying two tests on multivariate normality: library(mvnormtest) data(EuStockMarkets) mshapiro.test(t(EuStockMarkets[15:29,1:4])) Shapiro-Wilk normality test data: Z W = 0.8161, p-value = 0.005955 and library(energy) mvnorm.etest( EuStockMarkets[15:29,1:4] ) Energy test of multivariate normality:

Hi I have a few problems with tail/head when applied to multiple time series. I'm not sure as whether I did not understand the function or whether it correspond to an unexpected behavior. When head(a,n) is applied on data.frame or matrix, it returns a data-frame or matrix with first n obs of *each* variable. When applied to a mts object, it returns first n obs of *first* variable only,

I'm trying to use garchFit from fSeries, with Student or Skewed Student conditionnal distribution. Let's say that eps (vector) is my series of daily log-returns: data(EuStockMarkets) eps = diff(log(EuStockMarkets[,"CAC"])) library(fSeries) g = garchFit(series = eps, formula.var = ~garch(2,2), cond.dist = "dstd") s = g at fit$series All the coefficients are ok

Hi, I have a question to post. But I have a problem finding the appropriate forum. Some of the FAQ on pastecs are answered by R-help@stat.math.ethz.chmailing list. I searched to see if this mailing list requires registration or not. There was no information about that. I am a registered member of R- help general mailing list but I am aware it is better to post my question to a specific group in

Dear R users, I need to estimate an ARCH(1,0) model with t-residuals. To do this I use garchFit function from fGarch library. However, I get the following error message: Error in.garchInitParameters (formula.mean = formula.mean, formula.var = formula.var, ): object "alpha" not found I tried to estimate this model with different series, but I always get this error message. For example,

Sorry for entering late in the thread, but I was absent last week. I am developping an alternate GUI for R (and also Splus, Octave, Scilab, Matlab, Ox & Mathematica). The project started 3 years ago, but it is progressing slowly, since I am currently the only developer on the project and had to do it during my extra time. Now, it is going a little faster because I got some time and money

Dear list-reader, by running the following script: library(zoo) sessionInfo() search() packageDescription("zoo") data(EuStockMarkets) dax <- as.zoo(EuStockMarkets[1:10, "DAX"]) daxr <- diff(log(dax)) identical(as.vector(qnorm(daxr)), qnorm(coredata(daxr))) qqnorm(coredata(daxr)) qqnorm(daxr) qqnorm() produces an error: > qqnorm(daxr) Fehler in if (xi == xj) 0L