similar to: package "arules" - 'transpose' of the transactions

Someone can help me? I tried several things and always don't converge # Model library(sem) dados40.cov <- cov(dados40,method="spearman") model.dados40 <- specify.model() F1 -> Item11, lam11, NA F1 -> Item31, lam31, NA F1 -> Item36, lam36, NA F1 -> Item54, lam54, NA F1 -> Item63, lam63, NA F1 -> Item65, lam55, NA F1 -> Item67, lam67, NA F1 ->

I am currently trying to transpose some large panel data set ie transposing multiple rows in into a single column. instead the transpose functionality transposes all rows into columns. my sample data set looks like below: ACCT_NUM ACCOUNT_NAME TRAN_AMT DATE EMPLOYER 101913 GK 7489 30-Apr-10 PENSION 101913 GK 7489 30-May-10 PENSION 101913

Hello, I have a multi-year dataset (see below) with date, a data value and a flag for the data value. I want to find the monthly median for each month in this dataset and then plot it. If anyone has suggestions they would be greatly apperciated. It should be noted that there are some dates with no values and they should be removed. Thanks Emily > print ( str(data$flow$daily) )

I'd greatly appreciate your help in making a bar graph with multiple variables plotted on it. All the help sites I've seen so far only plot 1 variable on the y-axis Data set: I have 6 sites, each measured 5 times over the past year. During each sampling time, I counted the occurrences of different benthic components (coral, dead coral, sand, etc.) over 5 transects in each site site

Hi All, I am currently conducting a mixed model. I have 7 repeated measures on a simulated clinical trial. If I understand the model correctly, the outcome is the measure (as a factor) the predictors are clinical group and trial (1-7). The fixed factors are the measure and group. The random factors are the intercept and id and group. I tried using 2 functions to calculate mixed effects.

Dear all, I am trying to look for a built in function that performs the cochran Q test. that is, cochranq.test(X) where X is a contingency table (maybe a matrix or data.frame). The output will naturally be the test statisitcs, p-value, etc. A quick search on Google gives me the cochran.test in the 'outlier' package, but I had a look at the description of the test and it doesn't look

Hi All, Apologies if this has been answered somewhere else, but I have been searching for an answer all day and not been able to find one. I am trying to plot a path diagram for a CFA I have run, I have installed Rgraphviz and run the following: pathDiagram(cfa, min.rank='item1, item2, item3, item4, item5, item6, item7, item8, item9, item10, item11, item12', max.rank='SMP,

I would like to have tags mandatory in my app. The following keeps giving me error that params is nill. def validate() if (@params[:tags]) errors.add(@params[:tags], ":tags must be entered ") end end Why cannot I access params in my model class? The field for tags is called "tags" How else can I add an error using errors.add? I

Hello all, I have problem with setting up random effects. I have a model: y=x1+x2+x1*x2+z1+z1*x2 where x1, x2, x1*x2 are fixed effects and z1, z1*x2 are random effects (crossed effects) I use library(nlme) 'lme' function. My question is: how I should set up random effects? I did lme(y~x1+x2+x1:x2, data=DATA, random=~z1+z1:x2, na.action='na.omit') but it did not work.

I have a new problem: Register RBP is used in a function foo. (I am not allocating RBP to any virtual register, the instances of RBP in function foo are in the machine code when my register allocator starts.) Function foo calls function bar. Register RBP is not saved across the call, though it is live after the call. Function bar includes a virtual register. The code that I'm using to

Dear all, When I coerce a vector into a multi dimensional array, I would like R to start filling the array along the last dimension, then the 2nd last etc. Let's jump straight into an example. x <- 1 : 24 y <- array(dim=c(2,2,6)) I would like to have: y[1,1,1] = 1 y[1,1,2] = 2 ... y[1,1,6] = 6 y[1,2,1] = 7 y[1,2,2] = 8 ... y[2,1,1] = 13 ... y[2,2,1] = 19 if I do y<- array(x,

Hi, I am writing a function which requires user to enter a single character. Something like: hello<-function(){ input<-scan(n=1,what="a") if(input=="h")cat("Hello") # What goes after the 'if' is completely arbitrary, for simplicity sake I simply put a cat command here. } I want R to automatically finish scanning after the user has entered the 1st

Hi, layout(1:2) # split the screen into 2 regions plot(1:2) # plot in region 1 plot(1:2) # plot in region 2 par(mfg=c(1,1)) # Then I want to update the plot in region 1 plot(1.5,1.5) But the this last plot overlays with my 1st plot. Q: How do I replace my first plot with my last? #### NOTE ###### I know I can do this with split.screen and screen(n,TRUE) But then it actually clears the

On 11/30/2012 6:36 PM, Lang Hames wrote: > > > RBP is used as the frame pointer on x86 (hence its automatic > appearance in your code), and shouldn't be allocated to any vreg in > function bar. Loading/saving RBP should be managed by the stack frame > setup/teardown code. > If it doesn't already, your allocator should filter out reserved > registers (See

On Tue, 9 Oct 2018 11:09:53 +0300 Reio Remma <reio at mrstuudio.ee> wrote: > Do you see anything in Dovecot logs? It should definitely log if there > were permission issues. With 'mail_debug=yes' I see nothing relevant. Just something like this when I want to expunge deleted mails: Oct 09 10:40:01 imap(tselmeci)<15816><ZwHSosd3NL/AqAFm>: Debug: Mailbox INBOX:

Hello All: This series is an update version of multiqueue virtio-net driver based on Krishna Kumar's work to let virtio-net use multiple rx/tx queues to do the packets reception and transmission. Please review and comments. Test Environment: - Intel(R) Xeon(R) CPU E5620 @ 2.40GHz, 8 cores 2 numa nodes - Two directed connected 82599 Test Summary: - Highlights: huge improvements on TCP_RR

Hello All: This series is an update version of multiqueue virtio-net driver based on Krishna Kumar's work to let virtio-net use multiple rx/tx queues to do the packets reception and transmission. Please review and comments. Test Environment: - Intel(R) Xeon(R) CPU E5620 @ 2.40GHz, 8 cores 2 numa nodes - Two directed connected 82599 Test Summary: - Highlights: huge improvements on TCP_RR

Hi, Using the package lpSolve API, I need to build a 2000*100000 constraint matrix. I wonder which method is faster: (a) model = make.lp(0,0) add.constraint(model, ...) or (b) model = make.lp(2000,100000) set.constraint(model,...) Thanks ------------ KC