search for: backsolve

I've added a "backsolve" method to the bdsmatrix library. Per the Extending manual section 7.1 I've also added the following 3 lines along with my setMethod definitions for 2 classes. backsolve <- function(r, ...) UseMethod("backsolve") backsolve.default <- base:::backsolve formals(backsolve.defa...

This issue ties loosely into other recent S4 topics on this board. The methods package defines a number of implicit generics for linear algebra related functions (rcond, norm, backsolve) that, when used, interfere with base package operations. Here is the cut-and-paste version of the code the illustrates the problem: # rcond x1 <- cbind(1, 1:10) rcond(x1) setGeneric("rcond") rcond(x1) # norm example(norm) setGeneric("norm") example(norm) # backsolve exa...

I'm hoping that someone with deeper insight into S4 than I, that is to say virtually everyone reading this list, could help resolve the following problem in SparseM. We have setGeneric("backsolve", function(r, x, k = NULL, upper.tri = NULL, transpose = NULL, twice = TRUE, ...) standardGeneric("backsolve"), useAsDefault= function(r, x, k = ncol(r), upper.tri = TRUE, transpose = FALSE, twice = TRUE, ...) b...

I get the following error from one of my Rd files in R CMD check (R 2-14.0) * checking Rd files ... WARNING Error in switch(attr(block, "Rd_tag"), TEXT = if (!grepl("^[[:space:]]* $", : EXPR must be a length 1 vector problem found in ?backsolve.Rd? This is likely something that will be glaringly obvious once it's pointed out, but without a line number I can't seem to find it. I've been counting braces but don't see a mismatch. FYI, the file is below. (It is modeled on chol.Rd from the Matrix package.) Terry Therneau ---...

Hi, I am hoping some one can help with this. I am using nlme to fit a random coefficients model. It ran for hours before returning Error: Singularity in backsolve at level 0, block 1 The model is > plavix.nlme<-nlme(PLX_NRX~loglike(PLX_NRX,PD4_42D,GAT_34D,VIS_42D,MSL_42D,SPE_ROL,XM2_DUM,THX_DUM,b0,b1,b2,b3,b4,b5,b6,b7,alpha), + data=data, + fixed=list(b0 + b1+b2+b3+b4+b5+b6+b7+alpha~1), + random=b0+b1+b2+b3+b4+b5+b6+b7~1|menum, + + start=c(b0=0,b1=0...

...y, I have `solve' JonR> methods for triangular matrices and variance matrices -- would JonR> you be interested? { Jonathan, I hope it's okay if I CC this to R-devel; this must be of a wider interest } Ye.e..s; for triangular ones, there's the 4 different ways of backsolve()/forwardsolve().. Well, we (R core) have discussed matrix classes months and years ago.. and haven't really started doing anything about it. I think we then agreed to follow Splus' Matrix library and use class "Matrix" (and classes inheriting from "Matrix", i.e. cl...

Hi, I am trying to convert the following NLMIXED code to NLME, but am running into problems concerning 'Singularity in backsolve'. As I am new to R/S-Plus, I thought I may be missing something in the NLME code. NLMIXED *********** proc nlmixed data=kidney.kidney; parms delta=0.03 gamma=1.1 b1=-0.003 b2=-1.2 b3=0.09 b4=0.35 b5=-1.43 varu=0.5; eta=b1*age+b2*sex+b3*gn+b4*an+b5*pkn+u; hazard=eta+log(delta)+log(gamma)+(gamma...

...uot;, see e.g. <http://www.enseeiht.fr/hmf/travaux/CD0001/travaux/optmfn/hi/01pa/hyb74/node24.html>. This is very easy to code, but much more difficult to "vectorize". Is anyone aware of a library that contains a fast implementation of this algorithm? Another alternative is to use backsolve. I can easily eliminate the lower diagonal a, but I'm still left with b and c, whereas backsolve requires a matrix. Again, I can write a function to read b and c into a matrix, but this requires loops, and is too slow. Is there a vectorized way of doing it? Of course, the diag command works for...

Hi I'm trying to use ouch's hansen and brown functions but I get the error: > brown(logflatnodes,archotreeouch) Error in backsolve(l, x, k = k, upper.tri = upper.tri, transpose = transpose) : NA/NaN/Inf in foreign function call (arg 1) and with hansen also: Error in optim(par = c(sqrt.alpha, sigma), fn = function(par) { : function cannot be evaluated at initial parameters I'm not sure what I'm supposed to put...

Hi, For another trainingset I get this error message, which again is rather cryptic to me: Setting default kernel parameters Error in array(0, c(n, p)) : 'dim' specifies too large an array RMate stopped at line 0 of selection Calls: rvm ... .local -> backsolve -> as.matrix -> chol -> diag -> array thanks for any suggestions!

...X+X*f(z) Where f is the smooth function and With random effects on X and on the intercept. So, I try to write it like this: gam.lme<- gamm(Y~ s(z, by=X) +X, random=list(groups=pdDiag(~1+X)) ) but I get the error message : Error in MEestimate(lmeSt, grps) : Singularity in backsolve at level 0, block 1 When I simply fit a gam model using the formula above, then it works ok. Is it possible to fit such a model with gamm? Thanks a lot! [[alternative HTML version deleted]]

...e binomial data. My fixed factors include 2 dichotomous variables, day, and distance. When I run the model: modelA<-glmmPQL(Leaving~Trial*Day*Dist,random=~1|Indiv,family="binomial") I get the error: iteration 1 Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 >From looking at previous help topics,( http://tolstoy.newcastle.edu.au/R/help/02a/4473.html) I gather this is because of the dichotomous predictor variables - what approach should I take to avoid this problem? Thanks, Elva. ______________________________________________...

...68560 <.0001 Variety:nitro 6 45 0.30282 0.9322 # Excellent! However --- > fit2 <- lme(yield ~ Variety*nitro, random=~1|Block/Variety, subset= + !(Variety == "Golden Rain" & nitro == "0")) Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 -- ************************************************ * I.White * * University of Edinburgh * * Ashworth Laboratories, West Mains Road * * Edinburgh EH9 3JT * * Fax: 0131 650 6564 Tel:...

...n-time measure (RT) and an activation maesure (betadlpcv). since we want to analyze the influence of (age-)group and RT on the activation, we call: lme(betadlpcv ~ RT*group, data=our.data, random=~ RT |subject) this yields: Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 In addition: Warning message: Fewer observations than random effects in all level 1 groups in: lme.formula(betadlpcv ~ RT * group, data = patrizia.data, random = ~RT | what's the problem here? thanks for your kind help christoph -- Lust, ein paar Euro nebenbei zu verdien...

Dear R-ers, I am having trouble understanding why I am getting an error using glmmPQL (library MASS). I am getting the following error: iteration 1 Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 The long story: I have data from an experiment on pairwise comparisons between 3 treatments (a, b, c). So a typical run of an experiment involves a rater choosing between a versus b, b versus c, or a versus c. The response is either 0 (not chosen) or 1 (chosen) for each treatm...

...t introduction > and overview of this package. > Help for individual functions is also obtained by adding the > suffix '.spam' to the function name, e.g. 'help( chol.spam)'. > Attaching package: ‘spam’ > The following object(s) are masked from ‘package:base’: > backsolve, forwardsolve > > x=read.MM("/Users/brad/Dropbox/graphchi/2008.csv_global_mean.mm") > Error in read.MM("/Users/brad/Dropbox/graphchi/2008.csv_global_mean.mm") > : > invalid mode (list) to pass to Fortran (arg 8) [[alternative HTML version deleted]]

...quad.PBMC.model(aL, aN, T0), + data = tissueData, + weights = varConstPower(form =~ Count), + start = list( fixed = c(rep(1000, 8), -2, -2) ), + fixed = list(T0 ~ TypeTissue-1, aL ~ 1, aN ~ 1), + random = aL + aN ~ 1|Tissue + ) Error in MEestimate(nlmeSt, grpShrunk) : Singularity in backsolve at level 0, block 1 > > --------------------------------------------- The above command clearly this doesn't work, but if I comment out the "weights = ..." line, it executes with no problem. I'd greatly appreciate any guidance on how to properly set up varConstPower. Sin...

...0.505 7.516 5.51e-14**** Treatment 3 0.2409 9.6704 0.359 0.719 Treatment 4 -0.2483 0.8661 -0.287 0.774 Correlation of fixed effects Intra T2 T3 T2 -0.989 T3 -0.745 0.737 T4 -0.577 0.570 0.430 > The p-values from mcmc are: > mcmcpvalue<-function(samp) { std<-backsolve(chol(var(samp)), cbind(0,t(samp))-colMeans(samp), transpose=TRUE) sqdist<-colSums(std*std) sum(sqdist[-1]>sqdist[1]/nrow(samp) } fitSI<-mcmcsamp(fit,50000) library(coda) HPDinterval(fitSI) lower upper Intercept -4.0778905 -3.1366836 Treatment2 3.4455972 4.319...

I'm trying to use stepAIC on sparse matrices, and I need some help. The documentation for slm.fit suggests: slm.fit and slm.wfit call slm.fit.csr to do Cholesky decomposition and then backsolve to obtain the least squares estimated coefficients. These functions can be called directly if the user is willing to specify the design matrix in matrix.csr form. This is often advantageous in large problems to reduce memory requirements. I need some help or a reference that will show how to cre...

Hi all, I'm having some difficulty with lme. I am currently trying to run the following simple model anova(lme(x ~ f1 + f2 + f1:f2, data=m, random=~1|r1)) Which is currently producing the error Error in MEEM(object, conLin, control$niterEM) : Singularity in backsolve at level 0, block 1 x is a numeric vector containing 194 observations. f1 is a factor vector containing two levels, and f2 is a different factor vector containing 5 different levels. R1 is a another factor vector containing 13 different levels, and it is again, unbalanaced. f1, f2 and r1 are un...