similar to: Please help

Hi, Excuse me for asking this silly question. But I really couldn't understand why cov() and ccov() don't work for my calculation of covariance matrix. a <- matrix(1:8, 2, 4) a [,1] [,2] [,3] [,4] [1,] 1 3 5 7 [2,] 2 4 6 8 > ccov(a) Error in solve.default(cov, ...) : Lapack routine dgesv: system is exactly singular I also tried colume bind, but it

Hi, I'm trying to use the solve() function in R to invert a matrix. I get the following error, "Lapack routine dgesv: system is exactly singular" However, My matrix doesn't appear to be singular. [,1] [,2] [,3] [,4] [1,] 0.99252358 0.93715047 0.7540535 0.4579895 [2,] 0.01607797 0.09616267 0.2452471 0.3088614 [3,] 0.09772828 0.58451468 1.4907090

There is a series of data contains time in fixed step and energy varying with time, how to test its periodicity?In R, it seems there is no direct tools since I have search the R manual with periodic and I have not found any related topic. Thanks a lot

Hi everybody! I am searching for an R implementation of multi-scale singular spectrum analysis (SSA), which was introduced by Yiou etal (2000) (Data-adaptive wavelets and multi-scale singular-spectrum analysis) and further described in Ghil etal (2002). For SSA alone I found an package recently published on r-forge: http://r-forge.r-project.org/projects/simsalabim/ I am happy about any

Hi everyone, > does any one knows how can I calculate mean for different samples > i.e. I have a data like this: > > s1 s2 s3 s4 > 1 0 0 0 1 > 2 1 0 1 0 > 3 0 0 0 0 > 4 0 0 0 0 > 5 0 1 0 1 > 6 1 0 0 0 > 7 0 0 0 0 > 8 0 0 0 0 > 9 0 0 0 0 > 10 0 0 0 1 > > I need to make 5 different sample with 5

R version 2.8.0 (2008-10-20) i386-pc-mingw32 locale: LC_COLLATE=English_United States.1252;LC_CTYPE=English_United States.1252;LC_MONETARY=English_United States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252 attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] StreamMetabolism_0.01 chron_2.3-24 zoo_1.5-4 loaded

Dear R-devel, I am trying to use Fortran DGESV subroutine into C. Here it is the relevant part of the C file I am currently writing #include<stdio.h> #include<R.h> #include<Rmath.h> #include<math.h> void F77_NAME(DGESV)( int*, int*, double*, int*, int*, double*, int*, int*); void solve( int *p, double *A, double *Ainv) { ... F77_CALL(DGESV)(p, p, Ain, p, ipiv,

Hi there! I´m a noob when it comes to R and I´m using it to run statisc analysis. With the code for ARIMA below I´m getting this error: Error in solve.default(res$hessian * n.used) :Lapack routine dgesv: system is exactly singular The code is: > s.ts <- ts(x[,7], start = 2004, fre=12) > get.best.arima <- function (x.ts, maxord=c(1,1,1,1,1,1)) + { + best.aic <- 1e8 + n <-

I have got a data set that is Gross Primary Productivity ~ Total Suspended Solids it is a hyperbola just like: plot(1/c(1:1000)) how do I model this relationship so that I can get all of the neat things that lm gives residuals etc. etc. so that I can see if my eyeball model stands up. Thanks for any help, pointers, or good things to read. -- Stephen Sefick Research Scientist Southeastern

mac osx 10.5.4 R 2.7.1 I have fit a model d<-lm(y~x) with an R^2 of 0.963 but when I issue the command abline(d) the line is below where it ought to be. Looks like the right slope, but not the right intercept. thanks -- Stephen Sefick Research Scientist Southeastern Natural Sciences Academy Let's not spend our time and resources thinking about things that are so little or so large

I would like to be able to reverse the xlim on qplot this is the code that I am using qplot(a[,"River.Mile"], a[,26] ,ylab=colnames(a)[26], xlab="RiverMile", xlim=rev(c(60, 216)))+geom_smooth()+scale_x_continuous(breaks=c(215,202,198,190,185,179,148,119,61),

Title says it all remember cast() with sum as the aggregation function -- Stephen Sefick Research Scientist Southeastern Natural Sciences Academy Let's not spend our time and resources thinking about things that are so little or so large that all they really do for us is puff us up and make us feel like gods. We are mammals, and have not exhausted the annoying little problems of being

##This is a function that I am trying to write to calculate sunrise and sunset and works "mostly", but returns nonsensical values. What am I #missing? Thanks in advance. ###remember to include maptools as dependence### library(maptools) sunrise.set <- function(lat, long, date, timezone="UTC", num.days=1){ #this needs to be long lat# lat.long <- matrix(c(long, lat),

a <- c(1:26) b <- rnorm(25) e <- rnorm(25) f <- rnorm(25) g <- data.frame(b,e, a,f) I would like to plot a agianst all possibilities and then shoot it out to a pdf one graph per page. I think it would be okay to have this as a lattice plot or a ggplot with many graphs per page. I can figure all of that out I think, but I need something like r <- as.matrix(g) plot(.~a, data=r)

Dear R group, I have to solve a hessian matrix 40*40, called M, in order to obtain the standart deviations of estimators. When I use the function solve(M), I have the following error message: "Error in solve.default(M) : Lapack routine dgesv: system is exactly singular" Do you know an alternative approach which could succeed? I have found some information about the function

I have insect data from twelve sites and like most environmental data it is non-normal mostly. I would like to preform an anova and a means seperation like tukey's HSD in a nonparametric sense (on some sort of central tendency measure - median?). I am searching around at this time on the internet. Any suggestions, books, etc. would be greatly appreciated. -- Stephen Sefick Research

We have a problem inverting a matrix which has the following eigenvalues: > eigen(tcross, only.values=TRUE) $values [1] 7.917775e+20 2.130980e+16 7.961620e+13 8.241041e+12 2.258325e+12 [6] 3.869428e+11 6.791041e+10 2.485352e+09 9.863098e+08 9.819373e+05 [11] 3.263408e+05 2.929853e+05 2.920419e+05 2.714355e+05 8.733435e+04 [16] 8.127136e+04 6.543883e+04 5.335074e+04

Hi I have a problem with this error, I have searched the archives and found previous discussion about this, can I cannot understand how the explanations apply to what I am trying to do. I am trying to do Log_rank Survival analysis, I have included tables and str command, is it a factor/integer problem? If so how do I correct this, as all my attempt to recode the data have failed. >

I am wondering if there is a better alternative than Excel for data storage that does not require database knowledge (I will eventually have to learn this, but it is not on my immediate todo list). I need something that is not limited to 256 columns... I don't need any of the built in functions in excel just a spreadsheet like program with cells that hold data in a data.frame format for a

Hi, I want to do ANOVA for nested designs like following. I don't understand why the matrix (t(X) %*% X) is singular. Can somebody help me understand it? Regards, Peng > a=2 > b=3 > n=4 > A = as.vector(sapply(1:a,function(x){rep(x,b*n)})) > B = as.vector(sapply(1:(a*b), function(x){rep(x,n)})) > cbind(A,B) A B [1,] 1 1 [2,] 1 1 [3,] 1 1 [4,] 1 1 [5,] 1 2 [6,] 1 2 [7,]