similar to: write a function inside the summation in a more condensed form

I am relatively new to R, so this may be a much simpler question than it seems to me. I am trying to create a function that includes two summations, and can't figure out how. I am attaching the equation as a pdf file. This function will then be optimized over a chosen range of values, but right now I just need help with the function. Thank you. Zack Darnell Duke University -- Zack

Hi I'm having different outputs from GLM when using a "condensed" table V1 V2 V3 Present Absent 0 0 0 3 12 0 0 1 0 0 0 1 0 0 0 0 1 1 1 0 1 0 0 7 20 1 0 1 0 0 1 1 0 3 0 1 1 1 6 0 resp=cbind(Present, Absent) glm(resp~V1+V2+V3+I(V1*V2*V3),family=binomial) >Deviance Residuals: [1] 0 0 0 0 0 0 0 0 etc and also coefficients... And when using the same but

Dear R users... I made the R-code for this triple summation computation http://www.nabble.com/file/p20517134/a.jpg ------------------------------------------------- Here is my code.. x=seq(.1,1,.1); l=10 y=seq(1,10); m=10 z=seq(.1,1,.1); n=10 sum(sapply(1:l, function(i) {sum(sapply(1:m, function(j) {sum(sapply(1:n, function(k){exp(x[i]*y[j]*z[k] )/gamma(y[j]+1)}))^(1.5) }))}))

Dear R users... I made the R-code for this double summation computation http://www.nabble.com/file/p19213599/doublesum.jpg ------------------------------------------------- Here is my code.. sum(sapply(1:m, function(k){sum(sapply(1:m, function(j){x[k]*x[j]*dnorm((mu[j]+mu[k])/sqrt(sig[k]+sig[j]))/sqrt(sig[k]+sig[j])}))})) ------------------------------------------------- In fact, this is

Dear R experts I need to write a function that incorporates double summation, the problem being that the upper limit of the second summation is the index of the first summation, i.e: sum_{j=0}^{x} sum_{i=0}^{j} choose(i+j, i) where x variable or constant, doesn't matter. The following code obviously doesn't work: f=function(x) {j=0:x; i=0:j; sum( choose(i+j,i) ) } Can you help? Thanks

Dear All, I am studying some process measurement time series in R and trying to identify time delays using cross-correlation function ccf. The results have however been bit confusing. I found a couple of years old message about this issue but unfortunately wasn't able to find it again for a reference. For example, an obvious time shift is observed between the measurements y1 and y2 when the

Dear R users, I try to compute this summation, http://www.nabble.com/file/p25054272/dd.jpg where f(y|x) = Negative Binomial(y, mu=exp(x' beta), size=1/alp) http://www.nabble.com/file/p25054272/aa.jpg http://www.nabble.com/file/p25054272/cc.jpg In fact, I tried to use "do.call" function to compute each u(y,x) before the summation, but I got an error, "Error in X[i, ]

Hi all, I have a very quick question on how to use the summation sign in R for the function. Here?s a basic example: the function is sum(i=1 to 5)log(1-xi^2) Id be grateful if someone knows how to do this without writing it out 5 times - I am looking sth along the lines of the following: computeR <- function(x) { return (-sum(log(1-x^2)) }^ thank you vm in advance! -- View this

Hi all, I'm trying to model some data where the y is defined by y = summation[1 to 50] B1 * x + B2 * x^2 + B3 * x^3 Hopefully that reads clearly for email. Anyway, if it wasn't for the summation, I know I would do it like this lm(y ~ x + x2 + x3) Where x2 and x3 are x^2 and x^3. However, since each value of x is related to the previous values of x, I don't know how to do this.

I would like to code the following in R: a1(b1+b2+b3) + a2(b1+b3+b4) + a3(b1+b2+b4) + a4(b1+b2+b3) or in summation notation: sum_{i=1, j\neq i}^{4} a_i * b_i I realise this is the same as: sum_{i=1, j=1}^{4} a_i * b_i - sum_{i=j} a_i * b_i would appreciate some help. Thank you. -- View this message in context: http://r.789695.n4.nabble.com/summation-coding-tp4646678.html Sent from the R

Full_Name: Nick Efthymiou Version: R1.5.0 and above OS: Red Hat Linux Submission from: (NULL) (162.93.14.73) With the introduction of the functions rowSums(), colSums(), rowMeans() and colMeans() in R1.5.0, function "SEXP do_colsum(SEXP call, SEXP op, SEXP args, SEXP rho)" was added to perform the fast summations. We have an excellent opportunity to improve the accuracy by

Hello, I have to compute a multiple summation (not an integration because the independent variables a are discrete) for all the values of a function of several variables f (x_1,...,x_n), that is sum ... sum f(x_1,...,x_n) x_1 x_n have you some suggestion? Is it possible? I know that for multiple integration there is the function adapt, but it has at most n=20. In my case n depends on the

Probability <- function(N, f, m, b, x, t) { #N is the number of lymph nodes #f is the fraction of Dendritic cells (in the correct node) that have the antigen #m is the number of time steps #b is the starting position (somewhere in the node or somewhere in the gap between nodes. It is a number between 1 and (x+t)) #x is the number of time steps it takes to traverse the gap #t is the number

Dear helpers in this forum, This is a clarified version of my previous questions in this forum. I really need your generous help on this issue. > Suppose I have the following data set: > > id x y > 023 1 2 > 023 2 5 > 023 4 6 > 023 5 7 > 412 2 5 > 412 3 4 > 412 4 6 > 412 7 9 > 220 5 7 > 220 4 8 > 220 9 8 > ...... > Now I want to compute the

Hello! Maybe this is a trivial question as I'm still a new baby in R but I wish that u will help me. I want to calculate the following U= sum (t_j*v_j) where t_j is a vector and v_j is the matrix Thanks Dina

Hello: I'm dealing with an issue currently that I'm not sure the best way to approach. I've got a very large (10G+) dataset that I'm trying to create a histogram for. I don't seem to be able to use hist directly as I can not create an R vector of size greater than 2.2G. I considered condensing the data previous to loading it into R and just plotting the frequencies as a

> > Hi all, > I have a vector xm say: xm = c(1,2,3,4,5,5,5,6,6) > > I want to return a vector with the corresponding probabilities based on the > amount of times the numbers occurred. For example, I should get the > following vector for xm: > prob.xm = c(1/9, 1/9, 1/9, 1/9, 3/9, 3/9, 3/9, 2/9, 2/9) > Using prop.table gives: Usage (with table) > prob.xm <-

I have used R for years but run into a seemingly simple problem involving 'ifelse'. condensed code like this a=c(2,NA,NA,NA,2,2,NA,2,NA,2) b=c(NA,1,1,NA,2,2,2,2,2,2) #I want to combined a and b into c so that c would be a valid number either a or b is not missing c=ifelse(a==1|b==1,1,ifelse(a==2|b==2,2,NA)) cbind(a,b,c) a b c [1,] 2 NA NA [2,] NA 1 1 [3,] NA 1 1

Hello all, I'm currently using R to do PCA Analysis, and was wondering if anyone knew the specific R Code that could limit the output of the PCA Analysis so that you only get the Principal Component features as your output and none of the extraneous words or numbers that you don't want. If that was unclear, let me use linear regression as an example: "lm(y~x)" is the normal

Hi, I would like to plot a linear relationship between variable x and y. Can anyone help me with scaled plotting and axes so that all data points can be visualized somehow evenly? Plaint plot(x,y) will generate condensed points near (0,0) due to several large data points. Thank you. Eric > x [1] 0.3497630 3.3948900 1.5224900 0.2690660 0.1078720 0.0451689 0.5902680 0.2757550