search for: xtx

...X^T)X , but I keep getting the error message like: no b argument and no default value for sprintf(gettext(fmt, domain = domain), ...) . -------------------------------------------------------------------------------------------- # my code X<-Matrix(rep(1,500),100,5) X[lower.tri(X)]<-1-10^-7 XtX<- t(X)%*% X XtXu<-lu(XtX) InverseXtX<-solve(XtXu) --------------------------------------------------------------------------------------------- The cause suggested for this error is that the lower.tri function returns a matrix of logicals. If so, is trying to fix this by using sprintf fu...

Here's a skeletal example. Embellish as needed: p <- 5 n <- 300 set.seed(1) dat <- cbind(rnorm(n), matrix(runif(n * p), n, p)) write.table(dat, file="c:/temp/big.txt", row=FALSE, col=FALSE) xtx <- matrix(0, p + 1, p + 1) xty <- numeric(p + 1) f <- file("c:/temp/big.txt", open="r") for (i in 1:3) { x <- matrix(scan(f, nlines=100), 100, p + 1, byrow=TRUE) xtx <- xtx + crossprod(cbind(1, x[, -1])) xty <- xty + crossprod(cbind(1, x[, -1]), x[,...

I'd like to fit linear models on very large datasets. My data frames are about 2000000 rows x 200 columns of doubles and I am using an 64 bit build of R. I've googled about this extensively and went over the "R Data Import/Export" guide. My primary issue is although my data represented in ascii form is 4Gb in size (therefore much smaller considered in binary), R consumes about

...? ? ? ? ? ? ? ? ? ? ? ? ? ? ?1 LDDPdensity.f:291: (continued): ? ? ? ? ?open(unit=1,file='dppackage1.out',status='unknown', ? ? ? ? ?2 Invalid declaration of or reference to symbol `randsave' at (2) [initially seen at (1)] LDDPdensity.f:15: ? ? ? ? & ? ? ? ? ? ? ? ? ? ? ? ?xtx,xtx2,xty,xty2,fs,fm,worksam,workcpo) ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?1 LDDPdensity.f:291: (continued): ? ? ? ? ?open(unit=1,file='dppackage1.out',status='unknown', ? ? ? ? ?2 Invalid declaration of or reference to symbol `worksam' at (2) [initially seen...

i am trying to use matinv from the Design package to compute the generalized inverse of the normal equations of a 3x3 design via the sweep operator. That is, for the linear model y = ? + x1 + x2 + x1*x2 where x1, x2 are 3-level factors and dummy coding is being used the matrix to be inverted is X'X = 9 3 3 3 3 3 3 1 1 1 1 1 1 1 1 1 3 3 0 0 1 1 1 1 0 0 1 0 0 1 0 0 3 0 3 0 1 1 1 0 1 0 0 1

...0817 0.34630946 -0.3162278 [9,] 0.24706215 -0.31886828 -0.13294196 -0.25401667 -0.42308063 -0.38135353 0.482282448 0.24225089 -0.19843310 -0.3162278 [10,] -0.62111060 -0.32779019 -0.48541562 -0.14413474 0.25188193 -0.06825162 0.012492037 -0.28278192 0.04634233 -0.3162278 I also calculate: xtx=t(adjusted_dummyset) %*% adjusted_dummyset > xtx [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [1,] 9.0000000 -3.1796310 2.0417037 3.9514142 2.7275520 -1.66571377 1.5629736 -0.9104748 -4.8506341 0.68480373 [2,] -3.1...

...9 6.000000e+00 1 [4,] 4 16 1.200000e+01 1 [5,] 5 25 2.000000e+01 1 [6,] 6 36 3.000000e+01 1 [7,] 7 49 4.200000e+01 1 [8,] 8 64 5.600000e+01 1 [9,] 9 81 7.200000e+01 1 [10,] 10 100 9.000000e+01 1 # Note: column names of last two columns have been interchanged > XtX <- t(X)%*%X > U <- chol(XtX, pivot=T) > oo <- order(attr(U, "pivot")) > XtX A B C D A 385 3025 2640 55 B 3025 25333 22308 385 C 2640 22308 19668 330 D 55 385 330 10 > t(U[,oo])%*% U[,oo] D A B C D 385 30...

...hers. the long and short of it is that I would recommend ols.crossprod = function (y, x) { x <- as.matrix(x) ok <- (!is.na(y))&(!is.na(rowSums(x))) y <- y[ok]; x <- subset(x, ok) x <- cbind( 1, x) XtX <- crossprod(x) Xty <- crossprod(x, y) solve(XtX, Xty) } for fast and stable coefficients. (yes, stable using double precision, even though not as stable as lm(). it works just fine with X variables that have >99.99% correlation with as few as 100...

Dear all, My double for loop as follows, but it is little efficient, I hope all friends can give me a "vectorized" program to replace my code. thanks x: is a matrix 202*263, that is 202 samples, and 263 independent variables num.compd<-nrow(x); # number of compounds diss.all<-0 for( i in 1:num.compd) for (j in 1:num.compd) if (i!=j) { S1<-sum(x[i,]*x[j,])

I am estimating Value at Risk using PerfomanceAnalytics package. The?variables are stored in a data frame. I formated the data variables using zoo() and as.xtx() but it is not working. The working example is below. ##########################################################? reguire(zoo) require(PerformanceAnalytics) reguire(xts) ? year<- c(1991-12-30, 1992-12-30, 1993-12-30, 1994-12-30) R1 <- c(12, 9, 8, 13) R2 <- c(5,2,9, 13) d? <- data.frame...

I have the following problem: I am using igraph and entering a graph from an external (.txt) file using read.graph("a.txt","ncol") In a.xtx the name of the nodes contains special characters (such Polish names, etc). In the R console, the visualization of the names is not correct and I am loosing some of the special characters. Any help will be greatly appreciate. Renato De Leone (Professor) Universit? di Camerino Sc...

...work for all the data frames and I get the following message or a similar message to this: iter imp variable 1 1 Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q19 Q36 Q47 Q52 Q79 Q80 Q94 Q97 Q104 Q108 Q122 Q131 Q134 P1 P2 P3 P4 P5 P6Error in solve.default(xtx + diag(pen)) : system is computationally singular: reciprocal condition number = 1.83044e-16 In addition: Warning messages: 1: In sqrt((sum(residuals^2))/(sum(ry) - ncol(x) - 1)) : NaNs produced ... 7: In sqrt((sum(residuals^2))/(sum(ry) - ncol(x) - 1)) : NaNs produced Note: warnings 2 to 6 supp...

Hi, Im using the lm() function where the formula is quite big (300 arguments) and the data is a frame of 3000 values. This is running in a loop where in each step the formula is reduced by one argument, and the lm command is called again (to check which arguments are useful) . This takes 1-2 minutes. Is there a way to speed this up? i checked the code of the lm function and its seems that its

Dear R experts: I just tried some simple test that told me that hand computing the OLS coefficients is about 3-10 times as fast as using the built-in lm() function. (code included below.) Most of the time, I do not care, because I like the convenience, and I presume some of the time goes into saving a lot of stuff that I may or may not need. But when I do want to learn the properties of an

I can't find a way to retrieve z values and p-values from the output from lmer in the lme4 package. How is this done? Rick B.

Hello, Could somebody please tell me what the following is about? I try to run BMS function for quite a small dataset (400 rows and 50 columns) to get model suggestions, but I end up getting following error message: > bms<-bms(dat) Error in chol.default(XtX.start) : the leading minor of order 36 is not positive definite I've done it before, it worked for some other data set but not this time. I can't find any info about leading minors from anywhere. Jukka

Hi, I have been having a tedious issue with lmer models with lots of factors and lots of levels. In order to get the basic information at the beginning of the print out I also have to generate these enormous tables as well. Is there a method command to leave off all of the effects and correlations? Or, do I have to go to string commands?

Hello All, I would like to retrieve some of the results from the lmer(...) function in library lme4. If I run a model, say fm.1 <- lmer(y ~ 1 + (1 | x), data = dog) and try names(fm.1), I get NULL. Is there anyway to retrieve the information? Thanks

...the default boot VGA, successfully override by ast2400 with ast.modeset=10 append at the kernel cmd line. $ lspci | grep VGA 00:02.0 VGA compatible controller: Intel Corporation CoffeeLake-S GT2 [UHD Graphics 630] 01:00.0 VGA compatible controller: Advanced Micro Devices, Inc. [AMD/ATI] Caicos XTX [Radeon HD 8490 / R5 235X OEM] 04:00.0 VGA compatible controller: ASPEED Technology, Inc. ASPEED Graphics Family (rev 30) 05:00.0 VGA compatible controller: NVIDIA Corporation GK208B [GeForce GT 720] (rev a1) $ sudo dmesg | grep vgaarb pci 0000:00:02.0: vgaarb: setting as boot VGA device pci...