similar to: Help with parsing a data file

Hi.. i have an expression of the form: model1<-nls(y~beta1*(x1+(k1*x2)+(k1*k1*x3)+(k2*x4)+(k2*k1*x5)+(k2*k2*x6)+(k3*x7)+(k3*k4*x8)+(k3*k2*x9)+(k3*k3*x10)+ (k4*x11)+(k4*k1*x12)+(k4*k2*x13)+(k4*k3*x14)+(k4*k4*x15)+(k5*x16)+(k5*k1*x17)+(k5*k2*x18)+(k5*k3*x19)+

*Problem-1* CASE-I---------(works fine) > var1<-"tom" > var1 [1"tom" > var1<-as.character(var1) > var1 [1] "tom" > var2<-c("tom","harry","kate") > logc<-(var1 %in% var2) > logc [1] TRUE > typeof(var1) [1] "character" > typeof(var2) [1] "character"

I have dataframe with 17factors variables (for example every factor have 3levels) I have maybe 5000 observation. And i need to do table where is in every raw 1 of possible combination of this factors and the numbur how many time is this combination in my dataset. I wrote one code, but this is very slow and dumb. it looks like this: i<-0 for(i1 in levels(hivdat$pohl)){

I would like to load ApoAI.RData. During the operation of reading this data an error occurs. There is also a problem with STF file. > library (limma) > load("ApoAI.RData") Warning message: 'RG' looks like a pre-2.4.0 S4 object: please recreate it > objects() [1] "RG" > names(RG) [1] "R" "G" "Rb"

Hi all, I am trying to merge 2 big data.frame. The problem is merge is memory intensive so R is going out of memory error: cannot allocate vector of size 360.1 Mb. To overcome this, I am exploring option of using data.table package. But its not helping in term of memory as merge in data.table is fast but not memory efficient. Similar error is coming. My inputs are inp1 V1 V2 1 a i1 2 a i2 3 a

hello everyone. Look at the following R idiom: a <- array(1:30,c(3,5,2)) M <- (matrix(1:15,c(3,5)) %% 4) < 2 a[M,] <- 0 Now, I think that "a[M,]" has an unambiguous meaning (to a human). However, the last line doesn't work as desired, but I expected it to...and it recently took me an indecent amount of time to debug an analogous case. Just to be explicit, I would

Hi all, Can anyone suggest me how to insert rows in between data frames and also keep the ordering of row numbers correct? Estimate Std. Error t value Pr(>|t|) recmeanC2 9.275880e-17 6.322780e-17 1.467057e+00 0.14349903 recmeanC3 1.283534e-17 2.080644e-17 6.168929e-01 0.53781390

It seems that that it's hard to vectorize int64 in LLVM. For example, LLVM 3.4 generates very complicated code for the following IR. I am running on a Haswell processor. Is it because there is no alternative AVX/2 instructions for int64? The same thing also happens to zext <2 x i32> -> <2 x i64> and trunc <2 x i64> -> <2 x i32>. Any ideas to optimize these

How to NATURAL sort a vector or data frame* by row* , in ascending order ? V1 V2 V3 V4 i1 5.000000e-01 1.036197e-17 4.825338e+16 0.00000000 i10 4.001692e-18 1.365740e-17 2.930053e-01 0.76973827 i12 -1.052843e-17 1.324484e-17 -7.949081e-01 0.42735000 i13 2.571236e-17 1.357336e-17 1.894325e+00 0.05922715 i2

Dear R-helpers ? I have 7 data points that I want to fit a continuous curve to, that should look similar to a sine wave My data points would mark the local minima and maxima respectively. This is what I?ve got so far. And I would keep doing so, but sadly nls() then says that it has reached the maximum number of Iterations? ?

Background: OS: Linux Mandrake 10.1 release: R 2.0.0 editor: GNU Emacs 21.3.2 front-end: ESS 5.2.3 --------------------------------- Colleagues I am having some trouble extracting results from the function by, used to average variables in a data.frame first by one factor (depth) and then by a second factor (station). The real data.frame is quite large > dim(data.2001) [1] 32049 11 Here is a

I am having problems with comparing individual means in a within-subjects ANOVA. From my understanding, TukeyHSD is not appropriate in this context. So I am trying to compute contrasts, as follows: seven subjects participated in each of 6 conditions (intervals). > subject = factor(rep(c(1:7), each = 6)) > interval = factor(rep(c(1:6), 7)) and here is the dependent variable: > dv

Can any one help it will be very kind, loop statements I have this table and some more records, I want to reshape it V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 TP53 Dis1 Dis2 Dis3 Dis4 Dis5 Dis6 DCI New1 New2 New3 New4 FDI Hi2 H3 H4 GHD I1 I3 I4 I5 I6 I7 I8 I want my new table or matrix to be some thing like this V1 V2 V3 Tp53 Dis1 Dis2 Tp53 Dis1 Dis3 Tp53 Dis1 Dis4 Tp53 Dis1 Dis5 Tp53 Dis1 Dis6 Tp53 Dis2

> On 24.07.2015, at 08:06, zhi chen <zchenhn at gmail.com> wrote: > > It seems that that it's hard to vectorize int64 in LLVM. For example, LLVM 3.4 generates very complicated code for the following IR. I am running on a Haswell processor. Is it because there is no alternative AVX/2 instructions for int64? The same thing also happens to zext <2 x i32> -> <2 x

I'm looking for guidance on how to implement forward stepwise regression using lmStepAIC in Caret. The stepwise "direction" appears to default to "backward". When I try to use "scope" to provide a lower and upper model, Caret still seems to default to "backward". Any thoughts on how I can make this work? Here is what I tried: itemonly <-

Hello: When I use SPSS I execute the AGGREGATE DATA comand for the next data: 2112141123212213212213334 3143244113442312121213344 2114141123112214212113344 2112211122212413421213221 3114444123442414343413344 2312231223212222323223322 2143241123212313131213234 2113241113212313222213333 2113141123112214212113344 2114141123412111114413344 2113211122342314222313234 2114141123112414212113344

Hello, I've been working with "nnet" and now I'd like to use the weigths, from the fitted model, to iterpret some of variables impornatce. I used the following command: mts <- nnet(y=Y,x=X,size =4, rang = 0.1, decay = 5e-4, maxit = 5000,linout=TRUE) X is (m x n) Y is (m x 1) And then I get the coeficients by: Wts<-coef(mts) b->h1 i1->h1

Here is a drop-in replacement for the R incomplete beta function. src/math/pbeta.c It is a slightly modified version of the cephes library one from Netlib. In the few cases I tried it seems to give at least 14 digit agreement with the one in S-PLUS (its hard to get more). I'm not sure what performance is like. I'd like to know if it helps with some of the problems which have been

Hi All, ? I am trying to use the lordif package in R and can't figure out the reason for the above error when I try to run the calctheta() function. ################## # read data using foreign package - must be Stata 11 or earlier racedata<- read.dta("race.dta")??? # item responses resp.data<-racedata[,-c(1:2)] # grouping variable is in the second column

Hello, I wanted to ask one general question ( for now it is hard to check it manually, maybe there is a fast answer): can I construct an operation, say, addition, from operand_0 - 5 bits size and operand_1 - 3 bit size -> receive result as 6 bit size . I am basically reducing these sizes in the whole IR, so I want that all operands can have arbitrary sizes ( llvm pass is not really good because