similar to: function for the average or expected range?

Hi, All: ** My previous email on this subject seemed to contain an error; check the correction: Is there a function in R to compute the expected range of a sample of size n from some distribution? I ask, because I was recently asked about the control chart constant 'd2', which is the expected range for a sample of size n from a standard normal. There is a fairly simple

Hi, All: ** My previous email on this subject seemed to contain an error; check the correction below; please excuse my errors. Is there a function in R to compute the expected range of a sample of size n from some distribution? I ask, because I was recently asked about the control chart constant 'd2', which is the expected range for a sample of size n from a standard normal.

[my original message to s-news & r-help is attached ] No one possessed or knew of any S/R code for the sequential t-test. Also it doesn't appear in the SAS index. One or two suggested obtaining the S+ seqtrial software which may (or may not) cover this, but this seemed to be a bit of a "hammer to crack a nut". I have written a function based on the treatment in Wetheril

is there a way to use the actual index value for plotting zoo objects this is the way that the index is set up and a sample range of what I would like to plot 01/01/06 00:00:00 - 01/01/06 23:45:00 { library(zoo) # chron library(chron) fmt.chron <- function(x) { chron(sub(" .*", "", x), gsub(".* (.*)", "\\1:00", x)) }} x <- structure(c(15.57, 15.5,

This regards an old post that posed the question: Tom Hodgess wrote: "The problem is the (apparent?) inability to produce moving range process behavior (a.k.a. "control") charts with individuals data in the package "qcc" (v. 2.0). I have also struggled with the same limitation in package "IQCC" (v. 1.0). The package "qAnalyst" (v. 0.6.0) provides an

> library(Kendall) > Kendall(1:3,1:3) WARNING: Error exit, tauk2. IFAULT = 12 <<<<<< tau = 1, 2-sided pvalue =1 I believe Kendall tau is well-defined for this case and the reported value is correct; isn't it a bug to give a warning? (And if, e.g., the pvalue is not well-defined in this case, wouldn't it be better to return NA or NaN or something?) Also,

Hi every body: I need some help with kendall.global. The example in the manual seems not working well, and cannot used with my data, always the same error. data(mite) > mite.hel <- decostand(mite, "hel") > > # Reproduce the results shown in Table 2 of Legendre (2005), a single group > mite.small <- mite.hel[c(4,9,14,22,31,34,45,53,61,69),c(13:15,23)] >

Hi there, I'm trying to apply the Mann Kendall test for trend analysis of a time series. I have downloaded and installed the package Kendall and subsequently loaded it into the software. My time series is a .txt file with 2 columns - column 1 is the year (1985 - 2009) and column 2 is the corresponding entry variable. According to the R guidelines, the call should be: MannKendall(x)

Dear R users I want to compute Kendall's Tau between two vectors x and y. But x and y may have zeros in the same position(s) and I wrote the following function to be sure to drop out those "double zeros" "cor.kendall" <- function(x,y) { nox <- c() noy <- c() # for (i in 1:length(x)) if (x[i]!= 0 | y[i] != 0) nox[length(nox)+1]<- x[i] for (i in

Full_Name: Dirk Koschuetzki Version: 2.1.1 OS: source code Submission from: (NULL) (194.94.136.34) Hello, >From the source code (R-2.1.1, file: .../R-2.1.1/src/library/stats/R/) ****************************** cor.test.default <- function(x, y, alternative = c("two.sided", "less", "greater"), method = c("pearson", "kendall",

Colleagues, I ran some nonparametric regressions in R (run in RedHat Linux), then a colleague repeated the analyses in SAS. When we obtained different results, I tested S-Plus (same Linux box). And, got yet different results. I replicated the results with a small dataset: DATA: 37.5 23 37.5 13 25 16 25 12 100 15 12.5 19 50 20 100 13 100 10 100 10 100 16 50 10 87.5

Dear R-helpers, I'm fighting with the following problem : I want to do bootstrapping on a Kendall correlation with the following code : > cor.function <- function(data,i) cor(data[i, 1], data[i, 2],method="kendall") > boot.ci <- boot.ci(boot.cor <- boot(cbind(x,y),cor.function, R=1000),conf=c(0.95,0.99)) However, I've got problems because I've got ties

I have been having the same problem as poster Hodgess, below. It appears that her question was never answered, so I would like to share a solution with the community. The problem is the (apparent?) inability to produce moving range process behavior (a.k.a. "control") charts with individuals data in the package "qcc" (v. 2.0). I have also struggled with the same limitation in

Hi all, I am trying to write a script that will compute Kendall's tau for a 75 time series (using the Kendall package) and will then write the tau and p values from the Kendall test to a text file table that can be read into Excel. I am having no problem calculating Kendall's tau and the associated p value for each time series, but I am having trouble figuring out how aggregate the

Hi all, I would like to ask a question related to Kendall package. I ran Kendall (x,y) and saw the results. But I am not sure which tau values R reported. I have ties in my data set, so I want tau-b. Can anybody tell how Kendall package is calculating tau values? I have looked at the package PDF, but I could not find any useful information. As long as I see from the following link, there

Hello, I thougth that there is a function which does the kendall test in R, I writed on the console apropos("kendall") and I didn't found anything can you tell me how could I do to use the kendall test? Thanks. _____________________________________________________________________________ l [[alternative HTML version deleted]]

Hi, I am running a correlation analysis on a temporal dataset. I was wondering if you would receive the same tau and p values running the function: MannKendall(x), where x is the dependant variable that changes with time as you would running: Kendall(d,x), where x is the exact same dataset as the x entered into MannKendall and d is the date on which the observation was made (assuming that

Hi all, I'm not quite sure if this is a feature or a bug or if I just fail to understand the documentation: If I use cor() with pairwise.complete.obs and method=pearson, the result is a scalar: ->cor(c(1,2,3),c(3,4,6),use="pairwise.complete.obs",method="pearson") [1] 0.9819805 The documentation says that " '"pairwise.complete.obs"' only

Dear useRs, I've been trying to run a Mann-Kendall test in my data in order to detect trends. I studied the examples given at the Kendall package and I can understand pretty well how it works on time-series data. However, my data consists of values in different sites per year, as I display below;              Year 1 | Year 2 | Year 3 | ... Site 1        x           x          x       ...

Hi, I try to calculate Kendall's W coefficient and I have a bizarre error. little.app.mat<-matrix(c(1,3,4,2,6,5,2,4,3,1,5,6,3,2,5,1,5,4),nrow=3,byrow=TRUE) print(kendall.w(little.app.mat[-1,])) >>> Kendall's W for ordinal data >>> W = 0.7753623Error in if (is.na(x$p.table)) { : argument is of length zero