search for: innefici

Greetings, Can anyone suggest me if we can vectorize the following problem effectively? I have two datasets, one dataset is portfolio of stocks returns on a historical basis and another dataset consist of a bunch of factors (again on a historical basis). I intend to compute a rolling n-day sensitivitiesfor each stock for each factor, so the output will be a data frame with

...os x with RoR. It normally works great, however, when I use it for one project, kill the process, then switch to another project and start up using ./script/server, all I get is a blank page. No errors or html. The only solution I have found so far is to restart my machine, but that seems terribly inneficient. How does everybody else handle this, or do you guys not have this problem? Thanks! -- Randy Schmidt x@altorg.com 267.334.6833

...gument mismatch. Two vectors needed as input.")} } # The loop-based solution I have is: if (is(x, "Matrix") ) { cos = array(NA, c(ncol(x), ncol(x))) for (i in 2:ncol(x)) { for (j in 1:(i - 1)) { cos[i, j] = cosine(x[, i], x[, j]) } } } This solution seems inneficient. Is there an easy way of achieving this with a clever do.call + apply combination? Also, I have noticed that getting a row from a Matrix object produces a normal array (i.e., it does not inherit Matrix class). However, selecting >1 rows, does produce a same-class matrix. If I convert with as...

...gument mismatch. Two vectors needed as input.")} } # The loop-based solution I have is: if (is(x, "Matrix") ) { cos = array(NA, c(ncol(x), ncol(x))) for (i in 2:ncol(x)) { for (j in 1:(i - 1)) { cos[i, j] = cosine(x[, i], x[, j]) } } } This solution seems inneficient. Is there an easy way of achieving this with a clever do.call + apply combination? Also, I have noticed that getting a row from a Matrix object produces a normal array (i.e., it does not inherit Matrix class). However, selecting >1 rows, does produce a same-class matrix. If I convert with as...

...ombine the whole 5 variables changing at once. I understand there are many possible combinations (factorial of 5000!, 422 with some 500 digits) but I surmise there must be a better way to do it. So far, I have been changing them manually, but this task make the whole thing terribly slow and inneficient. Any ideas are appreciated. Thanks. Cuanto mas grande son, mas daño hacen. Postulado de Perkin. ------------------------------ Jesús Guillermo Andrade (Abg.) Gerente de Litigios y Corporativo. EDM. AC. API. Andrade & Moreno S.C. (http://amlegal.wordpress.com/) [[alternative HTML version...

...s. I solved this problem by creating a second logical matrix which contains all possible combinations of rows: tt <- matrix(as.logical(c(1,0,0,0,1,0,0,0,1,1,1,0,1,0,1,0,1,1,1,1,1)), nrow=3) and then subset the first matrix and check if all columns are covered. This solution, though, is highly inneficient and I am certain that a combination of apply or something will do. ########################### possibles <- NULL length.possibles <- NULL ## I guess the minimum solution is has half the number of rows guesstimate <- floor(nrow(tt)/2) + nrow(tt) %% 2 checked <- logical(nrow(tt)) re...

...vectors needed as input.")} } # The loop-based solution I have is: if (is(x, "Matrix") ) { cos = array(NA, c(ncol(x), ncol(x))) # preallocate memory for (i in 2:ncol(x)) { for (j in 1:(i - 1)) { cos[i, j] = cosine(x[, i], x[, j]) } } } This solution seems inneficient. Is there an easy way of achieving this with a clever do.call + apply combination? -- Thanks in advance, -Jose -- Jose Quesada, PhD Research fellow, Psychology Dept. Sussex University, Brighton, UK http://www.andrew.cmu.edu/~jquesada

Dear all, I am doing 200 times simulation. For each time, I generate a matrix and define some function on this matrix to get a 6 dimension vector as my results. As the loop should be slow, I generate 200 matrice first, and save them into a list named ma, then I define zz<-sapply(ma, myfunction) To my surprise, It almost costs me the same time to get my results if I directly use a loop

Dear all, I am doing 200 times simulation. For each time, I generate a matrix and define some function on this matrix to get a 6 dimension vector as my results. As the loop should be slow, I generate 200 matrice first, and save them into a list named ma, then I define zz<-sapply(ma, myfunction) To my surprise, It almost costs me the same time to get my results if I directly use a loop

Hi, I have a website where customers enter their phone numbers to be called. I'd like them to have to put in information and 'schedule' a call. 1) Call Immediately 2) Call in the next _ minutes 3) Call me tomorrow, same time. So, Asterisk will pull two variables from this php websites, $phonenumber and $timetocall. $timetocall will need to be calculated as