search for: b22

I want to change the type to factor of all variables in a data frame whose names match a certain pattern. So here I am trying to change the type to factor of all variables whose name begins with?namestub?in the dataframe?df. attach(df)sapply(grep(glob2rx("namestub*"),names(df)),as.factor) But this doesn't work since >levels(df$namestub1)NULL

Is there an element-by-element multiplication in R, like the .* operator in Matlab? eg: A (2x3) B (2x3) C=A.*B C (2x3) C = [[a11*b11 a12*b12 a13*b13]; [a21*b21 a22*b22 a23*b23]] I can't find one... Thanks -Mike Gates

Dear all: I'm trying to fit the optimal Box-Cox transformation related to nls (see the code below) for the demand of money data in Green (3th Edition) but in the last step R gives the next error message. Error en `[.data.frame`(eval(object$data), , as.character(formula(object)[[2]])[2]) : undefined columns selected. ?Any idea to solve the problem? Thanks in advance,

...at uea.ac.uk *************************************** Here is an example with 3 equations and 2 exogenous variables: ----- start code ------ N <- 1000 # number of observations library(MASS) ## parameters ## # eq. 1 b10 <- 7; b11 <- 2; b12 <- -1 # eq. 2 b20 <- 5; b21 <- -2; b22 <- 1 # eq.3 b30 <- 1; b31 <- 5; b32 <- 2 # exogenous variables x1 <- runif(min=-10,max=10,N) x2 <- runif(min=-5,max=5,N) # residual covariance matrix sigma <- matrix(c(2,1,0.7,1,1.5,0.5,0.7,0.5,2),3,3) # residuals r <- mvrnorm(N,mu=rep(0,3), Sigma=sigma) # endogenous v...

Hi, I have a function of the second grade, with 2 parameters: y~A^2 + A + B^2 + B The response y is a measurement for the precision of the analytical method, where A en B are method parameters. As its neccesary to keep the precision of the analytical methad as good as possible, its usefull to optimize A en B to keep y as low as possible. But how can I do this with R? I have searched the

...ted using as.character, looses its last part: ``diagonal = 1e-12)'' Shorter formula is ok though. Best, H??vard ************ Browse[2]> formula.str y ~ -1 + b1 + b2 + b3 + b4 + b5 + b6 + b7 + b8 + b9 + b10 + b11 + b12 + b13 + b14 + b15 + b16 + b17 + b18 + b19 + b20 + b21 + b22 + b23 + b24 + b25 + b26 + b27 + b28 + b29 + b30 + b31 + b32 + b33 + b34 + b35 + b36 + b37 + b38 + b39 + b40 + b41 + b42 + b43 + b44 + b45 + b46 + b47 + b48 + b49 + elevation + f(idx, model = "sphere", sphere.dir = "global_temperature_80s", T.order = 2, K....

...nput of file has been a problem for me. Take this case for example (http://code.google.com/codejam/contest/dashboard?c=agdjb2RlamFtchALEghjb250ZXN0cxjRzBQM), the files are usually of the form: A(number of lines for group 1) a11 a12 a13 a21 a22 a23 ... B(number of lines for group 2) b11 b12 b13 b21 b22 b23 ... I guess SAS may work pretty well in this kind of situation with data step. But I don't know how to handle them using R. Any suggestions? Thanks a lot. Best wishes, -- ??? Hesen Peng http://hesen.peng.googlepages.com/

...7*(X17*x1+X27*x2)^2+C17)A18*(X18*x1+X28*x2)+1*sqrt(B18*(X18*x1+X28*x2)^2+C18)A19*(X19*x1+X29*x2)+-1*sqrt(B19*(X19*x1+X29*x2)^2+C19)A110*(X110*x1+X210*x2)+1*sqrt(B110*(X110*x1+X210*x2)^2+C110)" > cum2 [1] "A21*(X11*x1+X21*x2)+1*sqrt(B21*(X11*x1+X21*x2)^2+C21)A22*(X12*x1+X22*x2)+1*sqrt(B22*(X12*x1+X22*x2)^2+C22)A23*(X13*x1+X23*x2)+-1*sqrt(B23*(X13*x1+X23*x2)^2+C23)A24*(X14*x1+X24*x2)+-1*sqrt(B24*(X14*x1+X24*x2)^2+C24)A25*(X15*x1+X25*x2)+1*sqrt(B25*(X15*x1+X25*x2)^2+C25)A26*(X16*x1+X26*x2)+1*sqrt(B26*(X16*x1+X26*x2)^2+C26)A27*(X17*x1+X27*x2)+1*sqrt(B27*(X17*x1+X27*x2)^2+C27)A28*(X18*x...

Hi, Is there any package that I can use to simulate the Gaussian Mixture Model , which is a mixture modeling method that is widely used in statistical learning theory. I know there is a mclust, however, I think it is a little bit different from my problem. Thanks very much.. regards. -------------------------- Peng Jiang ?? Ph.D. Candidate Antai College of Economics &

...peech_lumenvox.so: undefined symbol: ast_speech_register --------------------------------------------------------------------------------------------------------------------------------------------------------- My system: Centos 5.2, asterisk 1.4.22, asterisk-1.4.x-lumenvox-support-linux-i686-32bit-b22-engine8.5, lumenvox was installed using yum So if you could give me any idea I really will appreciated it Thanks your time Regards Yelson -- Yelson E Vivas C MPC (571) 6500-800 -------------- next part -------------- An HTML attachment was scrubbed... URL: http://lists.digium.com/pipermail/aster...

...0) b11 <- c(0,0,0,0,0,0,0) b12 <- c(0,0,0,0,0,0,0) b13 <- c(0,0,0,0,0,0,1) b14 <- c(0,0,0,0,0,0,1) b15 <- c(0,0,0,0,0,1,0) b16 <- c(0,0,0,0,1,0,0) b17 <- c(0,0,0,1,0,0,0) b18 <- c(0,0,1,0,0,0,0) b19 <- c(0,1,0,0,0,1,0) b20 <- c(0,1,0,0,0,1,0) b21 <- c(0,0,0,1,0,1,1) b22 <- c(1,0,0,1,0,1,1) b23 <- c(1,0,1,1,0,1,0) bb <- rbind (b1,b2,b3,b4,b5,b6,b7,b8,b9,b10,b11,b12,b13,b14,b15,b16,b17,b18,b19,b20, b21,b22,b23) a <- array(0, c(161,3), list(NULL,c("Subject","Item","Response"))) for (s in c(1:23)) for (i in c(1:7)) a[...

...- c(0,0,0,0,0,0,0) b12 <- c(0,0,0,0,0,0,0) b13 <- c(0,0,0,0,0,0,1) b14 <- c(0,0,0,0,0,0,1) b15 <- c(0,0,0,0,0,1,0) b16 <- c(0,0,0,0,1,0,0) b17 <- c(0,0,0,1,0,0,0) b18 <- c(0,0,1,0,0,0,0) b19 <- c(0,1,0,0,0,1,0) # differs b20 <- c(0,1,0,0,0,1,0) b21 <- c(0,0,0,1,0,1,1) b22 <- c(1,0,0,1,0,1,1) b23 <- c(1,0,1,1,0,1,0) bb <- rbind(b1,b2,b3,b4,b5,b6,b7,b8,b9,b10,b11,b12,b13,b14,b15,b16,b17,b18,b19,b20,b21,b22,b23) a <- array(0, c(161,3), list(NULL, c("Subject","Item","Response"))) for (s in c(1:23)) for (i in c(1:7)) a...

...0) b11 <- c(0,0,0,0,0,0,0) b12 <- c(0,0,0,0,0,0,0) b13 <- c(0,0,0,0,0,0,1) b14 <- c(0,0,0,0,0,0,1) b15 <- c(0,0,0,0,0,1,0) b16 <- c(0,0,0,0,1,0,0) b17 <- c(0,0,0,1,0,0,0) b18 <- c(0,0,1,0,0,0,0) b19 <- c(0,1,0,0,0,1,0) b20 <- c(0,1,0,0,0,1,0) b21 <- c(0,0,0,1,0,1,1) b22 <- c(1,0,0,1,0,1,1) b23 <- c(1,0,1,1,0,1,0) bb <- rbind (b1,b2,b3,b4,b5,b6,b7,b8,b9,b10,b11,b12,b13,b14,b15,b16,b17,b18,b19,b20, b21,b22,b23) a <- array(0, c(161,3), list(NULL,c("Subject","Item","Response"))) for (s in c(1:23)) for (i in c(1:7)) a...

...determinants of the diagonal blocks. If a diagonal block is of dimension 1x1, then the determinant of the block is simply the value of the single element in the block. If the diagonal block is of dimension 2x2 then the determinant of the block may be computed according to the well-known formula b11*b22-b12*b21, where bij is the value in the i'th row and j'th column of the block. int i, q, info, *ipiv, one = 1; double *b, *A, *D, det; /* ** A and D are upper triangular matrices in packed storage ** A[] = a00, a01, a11, a02, a12, a22, a03, a13, a23, a33, ... ** use the follow...

For my problem I have #Constraints b11<-0 b21<-0 b12<-0 b22<-0 n1>=0 n2>=0 n1<=1 n1<=1 n1+n2=1 In order to use spg I set Amat<-matrix(rbind(c(rep(0,10)),c(rep(0,10)),c(rep(0,2),1,rep(0,7)), c(rep(0,3),1,rep(0,6)),c(rep(0,10)),c(rep(0,10)), c(rep(0,6),1,rep(0,3)),c(rep(0,7),1,rep(0,2)), c(rep(0,8),1,rep(0,1)),c(rep(0,9),1,rep(0,0)), c(rep(...

...)), c(xgrid, list(...))), dim = sapply(x, length), dimnames = x) } Here's an example: > example(gouter) gouter> gouter(list(letters[1:2], 1:3, 2:4), paste, sep = "") , , 2 1 2 3 a "a12" "a22" "a32" b "b12" "b22" "b32" , , 3 1 2 3 a "a13" "a23" "a33" b "b13" "b23" "b33" , , 4 1 2 3 a "a14" "a24" "a34" b "b14" "b24" "b34" Andy > > &g...

...> > different timestamp, and even if I add --checksum or --ignore-times, > > the old file in dest won't be modified (overwritten by a newer file). > > I can't reproduce the problem. I ran the script in your original > message, except I changed "b2" to "b22" and waited a few seconds > before running that line so the file would get a later mtime. Both > rsync 2.6.9 and the latest development rsync correctly replaced b.txt > with the version from new/ on the second run. Am I missing something? I don't know. Somtimes it works and...

Hello R users, For the last few days I am struggling with the following task: my data.frame: A1 A2 A3 B1 B2 B3 58.81 53.292 54.501 13.013 17.39 19.407 56.02 56.251 54.033 20.099 13.15 10.411 55.376 53.099 57.625 13.396 21.031 13.22 58.584 53.194 54.218 13.038 16.854 19.289 55.7 55.921 53.847 19.942 13.153 9.828 55.093 52.934