similar to: Calculation of Covariance Matrix Calculation

Hi, Anyone know anything about Asterisk's support for door phones? Receiving the call from the door intercom system, opening the door, etc? Any hardware recommendations? I understand that the equipment we have now is Panasonic proprietary and came with the currently deployed Panasonic TD12-32 pbx. We intend to deploy Asterisk in a 72 extensions + 16 trunks in a while, so any info will be

Doug, I thought perhaps that you might be interested in the comparison of lme to the results for the same models fitted by Richard Jones' carma (I just wrote the R interface to his Fortran code). The code to run the example from the lme help and for the equivalent with carma is in the file below. The two main differences in results are 1. the random coefficients covariance matrix is quite

I have a question regarding bootstrap coverage. I am trying to understand the benefits of using the bootstrap for small sample sets. To do this I created a normal population and then picked 10 from the populations and applied both traditional statistical methods and the Bootstrap (bcanon, 5000 bootstrap samples) to calculate a 95% confidence interval of on the mean. I saved the width of the

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,

Le 06/05/2015 21:05, Renato Golin a écrit : > On 6 May 2015 at 19:15, Sanjoy Das <sanjoy at playingwithpointers.com> wrote: >> I could not easily locate this on http://llvm.org/reports/coverage/ so >> asking here: what workload is the coverage computed over? IOW, what >> all does the bot run to get this coverage information? > Nothing is clear in that page. No

Dear list-member, I am currently developing a package with S4 classes. The NAMESPACE and DESCRIPTION is printed below. Within this package I have set a method "residuals" for two classes. In version 2.8.1 these two are reported whereas in R-Devel (2009-01-28 r47766). What have I missed? What has changed and how can I rectify the issue? Your help and pointers are welcome. For 2.8.1:

Doug, I have been attempting to learn a little bit about nlme without too much documentation except the online help. The Latex file in the nlme directory looks interesting but uses packages that I do not have so that I have not been able to read it. I have run the example from gnls to compare it with the results I get from my libraries (code below - I have not included output as it is rather

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

Dear R-experts, I am trying to fit my model but I couldn't because of this error. here is the error "Error in solve.default(dial(m) -A) : Lapack routine dgesv: system is exactly singular" thank you all. sonam

I have written a function which returns an "incorrect number of subscriptions error" and am unable to identify why this should happen. Any help would be gratefully received. The problem: I would like to generate combinations/permutations across different selections - for example all the combinations of "3 chosen from 6" combined with "5 chosen from 8" combined with

Dear list, I am a little puzzled by computing time in connection with calling C functions. With the function mysolve1 given below I solve Ax=B, where the actual matrix operation takes place in mysolve2. Doing this 5000 times takes 3.51 secs. However, if I move the actual matrix inversion part into mysolve1 (by uncommenting the two commented lines and skip the call to mysolve2) then the

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. >

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 <-

Hey Everyone, I'm running R 2.4.0 on Debian etch 4.0, and I'm trying to call some LAPACK functions from the C code in my package. Actually, to be honest I'm not really having trouble using commands such as La_dgesv from within my C code, but I do get warning when compiling the package saying: ***.c: In function '***': ***.c:37: warning: implicit declaration of function

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

An executable version 0.6 of my libraries is now available at www.luc.ac.be/~jlindsey/rcode.html This works with MS R0.64.2 and appears possibly to work with R65.0. There is a serious problem with the Fortran compiler as some of the examples for elliptic and carma crash it. These same examples do not crash R63.0 with the library executables of Jan 99. I am releasing this anyway because of the

Dear All, While inverting a matrix the following error appears on my console: Error in solve.default(my_matrix) : Lapack routine dgesv: system is exactly singular With this respect, I have been replacing the solve() function with ginv(): the Moore-Penrose generalized inverse of a matrix. These are the questions I would like to ask you: 1. Would you also replace solve() with ginv() in

Hi. I tried running the following code. I don't understand the error. mydata <- read.table("C:/dataForR/radiology/wordFrequencies.csv", header=TRUE, sep=",") > dim(mydata) [1] 982 924 mydataN<-mydata[,-923] > dim(mydataN) [1] 982 923 cor(mydataN) factanal(mydataN, factors=3) Error in solve.default(cv) : Lapack routine dgesv: system is exactly singular

Hello all- I have two time series, Index1stdiff and Comps1stdiff. I regressed the first on the second and R returned the summary stats I expected. Then I looked at and plotted the residuals. I then wanted to assess autocorrelation characteristics and tried to run a Durbin-Watson using: library(lmtest) dwtest(formula=Index1stdiff~Comps1stdiff,alternative=c("greater")) I am

Hi, I'm using e1071 package to do fuzzy cluster analysis. My dataset (ra) has 5237 observations and 2 variables - depth and velocity. I used fuzzy cmeans to create 6 fuzzy classes. >ra.flcust6<-cmeans(ra,6,iter.max=100,verbose=F,dist="euclidean",method="cmea ns",m=1.7,rate.par=NULL,weights=1) I would like to calculate the value of all the fuzzy validity