similar to: eval and assign in loop problem

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 +

Using S+ 6 for Linux and R 1.4.1 Taking verbatim some lines from S-Plus that work perfectly, and running them on R, I get an unexpected error message: R : Copyright 2002, The R Development Core Team Version 1.4.1 (2002-01-30) > library(MASS) > data <- read.table("/usr/local/data/mcmanus.dat",header=T) > mcmanus.frm <-

Hi, You might need to check library(boot).? I have never used that before.? So, I can't comment much.? It is better to post on R-help list.? I had seen your postings on Nabble in the past.? Unfortunately those postings were not accepted in R-help.? You have to directly post at ? r-help at r-project.org after registering at: https://stat.ethz.ch/mailman/listinfo/r-help ?

We have a wireless network that uses 802.1x authentication, in which domain joined computers use their machine credentials to connect. Windows machines do this automatically, and until recently Linux computers could join using wicd, wpa-supplicant, and a simple script that would retrieve the machine password with tdbdump. ( specifically tdbdump -k SECRETS/MACHINE_PASSWORD/DOMAIN

Hi, Using S=1000 and simdata <- replicate(S, generate(3000)) #If you want both "m1" and "m0" #here the missing values are 0 res1<-sapply(seq_len(ncol(simdata.psm1)),function(i) {x1<-merge(simdata.psm0[,i],simdata.psm1[,i],all=TRUE); x1[is.na(x1)]<-0; x1}) res1[,997:1000] #????? [,1]???????? [,2]???????? [,3]???????? [,4]??????? #x1??? Numeric,3000 Numeric,3000

Hi, I am trying to fit a 4p logistic to this data, using nls function. The function didn't freely converge; however, it converged if I put a lower and an upper bound (in algorithm port). Also, the b1.A parameter always takes value of the upper bound, which is very strange. Has anyone experienced about non-convergent of nls and how to deal with this kind of problem? Thank you very much.

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;

Hello, I have a vector {a, b1, b2, b3, b4}. How can I calculate the following matrix: var(a) cov(a, b1) cov(a, b2) cov(a, b3) cov(a, b4) cov(a, b1) var(b1) cov(a, b2) cov(a, b3) cov(a, b4) ... ... cov(a, b1) cov(a, b2) cov(a, b3) cov(a, b4) var(b4) I would very appreciate your inputs. Thank you very much. Sincerely, Jialin Huang [[alternative HTML version deleted]]

Jonathan Lennox wrote: > +opus_int32 silk_noise_shape_quantizer_short_prediction_neon(const opus_int32 *buf32, const opus_int32 *coef32) > +{ > + int32x4_t coef0 = vld1q_s32(coef32); > + int32x4_t coef1 = vld1q_s32(coef32 + 4); > + int32x4_t coef2 = vld1q_s32(coef32 + 8); > + int32x4_t coef3 = vld1q_s32(coef32 + 12); > + > + int32x4_t a0 = vld1q_s32(buf32 -

I would like to code the following in R: a1(b1+b2+b3) + a2(b1+b3+b4) + a3(b1+b2+b4) + a4(b1+b2+b3) or in summation notation: sum_{i=1, j\neq i}^{4} a_i * b_i I realise this is the same as: sum_{i=1, j=1}^{4} a_i * b_i - sum_{i=j} a_i * b_i would appreciate some help. Thank you. -- View this message in context: http://r.789695.n4.nabble.com/summation-coding-tp4646678.html Sent from the R

Dear R users, Basically, from the following arbitrary data set: a <- data.frame(id=c(c("A1","A2","A3","A4","A5"),c("A3","A2","A3","A4","A5")),loc=c("B1","B2","B3","B4","B5"),clm=c(rep(("General"),6),rep("Life",4))) > a

Dear list, I have a list of matrices : i1 <- matrix(1:10, nrow = 2, ncol = 5) i2 <- matrix(11:20, nrow = 2, ncol = 5) j <- list(i1 = i1, i2 = i2) I would like to attribute names to each dimension, for each matrix, as follows : $i1 B1 B2 B3 B4 B5 A1 1 3 5 7 9 A2 2 4 6 8 10 $i2 B1 B2 B3 B4 B5 A1 11 13 15 17 19 A2 12 14 16 18 20 However, I have to use lapply function and attribute

Hello R users, Given a linear (in the parameters) regression model where one predictor x interacts with time and time*time (ie, a quadratic effect of time t): y = b0 + b1(x) + b2(t) + b3(t^2) + b4(x*t) + b5(x*t^2) + e, I would like to construct 95% confidence bands (optimally, shaded) around this function: *dy* = b1 + b4(t) + b5(t^2) *dx* That is, the partial effect of x on y changing over

Hi All, I have data on the sequence of births for families with completed fertility cycle (in a data frame); the relevant variables are called b1, b2, b3, b4, b5, b6 and record the birth of the first, second, ..., sixth child. So, b1=1 if the first birth is male, b1=2 if the first birth is female, and b1=NA if the family did not record any first birth. Similarly for b2, b3, b4, b5 and b6. I

Hi, I have a problem with fitting a nonlinear mixed-effects model to my data. I was able to fit quite simple exponential model but now I?m trying to fit the following Gompertz model: > gomp<-nlme(paino~b0+b1*exp(-exp(-b2*(daydeg.scale-b3))), data=group1, fixed=b0+b1+b2+b3~1, start=c(b0=150, b1=3000, b2=0.6, b3=2500)) I?m getting the following error: Error in chol((value + t(value))/2) :

Hi all, I am struggling to work out how to use the rownames from an edited dataframe rather than the row names from the original dataframe. In my data set i'm trying to extract several rows of data on particular individuals, i don't doubt i'm using the long way round but what i have in the way of a script is this: ##selecting the IDs from the dataframe individually

Hi all, I have 4 matrices, each having 5 columns and 4 rows .....denoted by B1,B2,B3,B4. I have generated a vector of 7 indices, say (1,2,4,3,2,3,1} which refers to the index of the matrices to be chosen and then appended one on the top of the next: like, in this case, I wish to have the following mega matrix: B1over B2 over B4 over B3 over B2 over B3 over B1. 1> How can I achieve this?

I have a dataset that is basically structureless. Its dimension varies from row to row and sep(s) are a mixture of tab and semi colon (;) and example is HEADER1 HEADER2 HEADER3 HEADER3 A1 B1 C1 X11;X12;X13 A2 B2 C2 X21;X22;X23;X24;X25 A3 B3 C3 A4 B4 C4 X41;X42;X43 A5 B5 C5 X51 etc., say. Note that a blank

Hi, Can anyone help to write a more elegant version of my code? I am sure this can be put into a loop but I am having trouble creating the objects b1,b2,b3,...,etc. b1 <- rigamma(50,1,1) theta1 <- rgamma(50,0.5,(1/b1)) sim1 <- rpois(50,theta1) b2 <- rigamma(50,1,1) theta2 <- rgamma(50,0.5,(1/b2)) sim2 <- rpois(50,theta2) b3 <- rigamma(50,1,1) theta3 <-

Hi, I have a column (V4) in a midi event list which includes tone pitch names, i.e. "A4, E4, C#4, A3...": > compo[1:10,] V1 V2 V3 V4 V5 V6 V7 1 1 1 0 A4 96 2 0 2 1 1 0 E4 96 2 0 3 1 1 0 C#4 96 2 0 4 1 1 0 A3 96 2 0 5 1 3 0 B4 96 1 0 6 1 3 0 E4 96 1 0 7 1 3 0 B3 96 1 0 8 1 3 0 G#3 96 1 0 9 1 4 0 C#5 96 1 0 10