search for: la_dgesv

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 'La_dgesv' ***.c:37: warning: assignment makes pointer from integer without a cast I tried using: #include <Rmodules/Rla...

...06-23) While calculating partial correlation for a dataset ,i keep getting this error :-- *Error in solve.default(Szz) : system is computationally singular: reciprocal condition number = 4.90109e-18* On using the traceback() function i get this:-------------- > traceback() 10: *.Call("La_dgesv", a, b, tol, PACKAGE = "base")* 9: solve.default(Szz) 8: solve(Szz) 7: pcor.mat(firstvalue, secondvalue, third_var, method, na.rm = T) 6: PartialCorr_Calculation(value1, value2, third_var, method = "pearson", na.rm = T) 5: Partial(contrld_third_var(rowvalues$matrix1,...

...ckages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. *** caught segfault *** address 40b843f0, cause 'memory not mapped' Traceback: 1: .Call("La_dgesv", a, b, tol, PACKAGE = "base") 2: solve.default(rgb) 3: solve(rgb) 4: drop(whitexyz %*% solve(rgb)) 5: make.rgb(red = c(0.625, 0.34), green = c(0.28, 0.595), blue = c(0.155, 0.07), gamma = 1.8, white = "D65", name = "Apple RGB") 6: eval(expr, envir, enclos)...

Dear all, I need to compute the ACF (autocorrel) of an AR6 process, given the values of its parameters (w1,w2,w3,w4,w5,w6). First, I notice that there is an error as soon as the sum of the wi equals 1 : "Error in drop(.Call("La_dgesv", a, as.matrix(b), tol, PACKAGE = "base")) : system is computationally singular: reciprocal condition number = 1.00757e-18" Secondly, when the sum is greater than 1, some elements in the returned ACF vector do not belong to interval [-1,1], which looks a bit weird for...

...;- 0.05 > Aii <- rbind (c(1,2,-1,-delta.I), c(1,3,delta.I, 1), c (1,4,-1,-delta.I), + c(2,3, delta.I,1), c(2, 4,-1,-delta.I), c(3,4,delta.I, 1)) > > > gls <-ls.ranking.capa.ident(4,2,C, rk.proto,0.5, A.Shapley.preorder = Asp, A.interaction.interval = Aii) Error in drop(.Call("La_dgesv", a, as.matrix(b), tol, PACKAGE = "base")) : system is computationally singular: reciprocal condition number = 4.68861e-18 [[alternative HTML version deleted]]

...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. > survdiff(Surv(f2$days.alive , f2$censored)~group, data=f2) Error in drop(.Call("La_dgesv", a, as.matrix(b), tol, PACKAGE = "base")) : Lapack routine dgesv: system is exactly singular > head(f2) group days.alive censored 1 PRI_CAS_5_NODU 1826 1 2 PRI_CAS_5_NODU 1488 0 3 PRI_CAS_5_NODU 1826 1 4 PRI_CAS_5_NODU...

Dear R-help, I'm very sorry to ask 2 questions in a week. I am using the package 'crr' and it does exactly what I need it to when I use the dataset a. However, when I use dataset b I get the following error message: Error in drop(.Call("La_dgesv", a, as.matrix(b), tol, PACKAGE = "base")) : system is computationally singular: reciprocal condition number = 1.28654e-24 This is obviously as a result of a problem with the data but apart from dataset a having 1674 rows and dataset b having 701 rows there is really no difference...

...spc$ tail -16 rOut.txt /Library/Frameworks/R.framework/Resources/bin/BATCH: line 60: 5461 Segmentation fault ${R_HOME}/bin/R -f ${in} ${opts} ${R_BATCH_OPTIONS} > ${out} 2>&1 *** caught segfault *** address 0x3f095116, cause 'memory not mapped' Traceback: 1: .Call("La_dgesv", a, b, tol, PACKAGE = "base") 2: solve.default(iV0) 3: solve(iV0) 4: standardGeneric("solve") 5: solve(iV0) 6: w0.fullCond(curr.sample, x@internals@values, x@priors@values) 7: gsSampler(down.univ.gs) 8: standardGeneric("gsSampler") 9: gsSampler(down.univ....

...else storage.mode(b) <- "double" storage.mode(a) <- "double" return(if (is.matrix(b)) { if (ncol(a) != nrow(b)) stop("'b' must be compatible with 'a'") rownames(b) <- colnames(a) .Call("La_dgesv", a, b, tol, PACKAGE = "base") } else drop(.Call("La_dgesv", a, as.matrix(b), tol, PACKAGE = "base"))) } a <- qr(a, tol = tol) nc <- ncol(a$qr) if (a$rank != nc) stop("singular matrix 'a' in 'solve'")...

I get this error while computing partial correlation. *Error in solve.default(Szz) : system is computationally singular: reciprocal condition number = 4.90109e-18* Why is it?Can anyone give me some idea ,how do i get rid it it? This is the function i use for calculating partial correlation. pcor.mat <- function(x,y,z,method="p",na.rm=T){ x <- c(x) y <- c(y)

...src/library/grDevices/src' *** caught segfault *** address 6f6c207761732096, cause 'memory not mapped' Traceback: 1: .Call("R_lazyLoadDBfetch", key, file, compressed, hook, PACKAGE = "base") 2: lazyLoadDBfetch(key, datafile, compressed, envhook) 3: .Call("La_dgesv", a, b, tol, PACKAGE = "base") 4: solve.default(rgb) 5: solve(rgb) 6: drop(whitexyz %*% solve(rgb)) 7: make.rgb(red = c(0.625, 0.34), green = c(0.28, 0.595), blue = c(0.155, 0.07), gamma = 1.8, white = "D65", name = "Apple RGB") 8: eval(expr, envir, encl...

...pectively, in the formula script. My model has both types of predictor variables. As the author of the script indicated in the mlogit helps, I am using the mixed model script example: m<-mlogit (mode ~ price + catch | income, data = Fish) but I obtain the next error: Error en drop(.Call("La_dgesv", a, as.matrix(b), tol, PACKAGE = "base")) :   rutina Lapack dgesv: sistema es exactamente singular The only syntax that I can run is: m<-mlogit (mode ~ 1 | income, data = Fish) which I don not understant really well what is going on but I understand that here just individual-...

hi everyone, ipop very quickly and accurately identifies the correct parameters in a toy dataset i built, but when i use ipop on the real dataset i get values for the parameters " primal(res) " that are less than zero, even though i specify zero for the lower bound : l = rep(0, length(c)) , where length(c) is the number of parameters i'm trying to identify. the parameters are

...../../../../library/grDevices/libs *** caught segfault *** address 61633346, cause 'memory not mapped' Traceback: 1: .Call("R_lazyLoadDBfetch", key, file, compressed, hook, PACKAGE = "base") 2: lazyLoadDBfetch(key, datafile, compressed, envhook) 3: .Call("La_dgesv", a, b, tol, PACKAGE = "base") 4: solve.default(rgb) 5: solve(rgb) 6: drop(whitexyz %*% solve(rgb)) 7: make.rgb(red = c(0.625, 0.34), green = c(0.28, 0.595), blue = c(0.155, 0.07), gamma = 1. 8, white = "D65", name = "Apple RGB") 8: eval(expr, envir...

...r an older version of SPlus. Can anyone give me some insights into where the problem is? Thanks R 2.4.1 on MAC OSX 2mb ram Mark Grant markg at uic.edu > attach(Aspirin.frame) > hblm(Diff ~ 1, s = SE) Error in solve.default(R, rinv) : 'a' is 0-diml > traceback() 6: .Call("La_dgesv", a, b, tol, PACKAGE = "base") 5: solve.default(R, rinv) 4: solve(R, rinv) 3: summary.blm(fit) 2: eb.calc(rho[i], X, Y, s.e., df.se, corrs, prior, ...) 1: hblm(Diff ~ 1, s = SE) > > hblm function(formula, s.e., df.se = Inf, corrs = F, prior = NULL, fast.calc = F, ...)...