similar to: summated scale

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

Dear R-help community, If I have a data.frame df as follows: > df x1 x2 x3 x4 x5 x6 1 5 5 1 1 2 1 2 5 5 5 5 1 5 3 1 5 5 5 5 5 4 5 5 1 4 5 5 5 5 1 5 2 4 1 6 5 1 5 4 5 1 7 5 1 5 4 4 5 8 5 1 1 1 1 5 9 1 5 1 1 2 5 10 5 1 5 4 5 5 11 1 5 5 2 1 1 12 5 5 5 4 4 1 13 1 5 1 4 4 1 14 1 1 5 4 5 5 15 1 5 5 4

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.

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) }))}))

Hi everyone, Let me have a dataframe named ?mydata? and created as below, *> n=c(5,5,5,5) #number of trils > x1=c(2,3,1,3) ) #number of successes > x2=c(5,5,5,5) #number of successes > x3=c(0,0,0,0) #number of successes > x4=c(5,0,5,0) #number of successes > mydata=data.frame(n,x1,x2,x3,x4) > mydata* n x1 x2 x3 x4 1 5 2 5 0 5 2 5 3 5 0 0 3 5 1 5 0 5 4 5 3 5 0

Hello all I have a feeling this is very simple......but I am not sure how to do it My boss has two variables, one is an average of 4 numbers, the other is an average of 3 of those numbers i.e var1 = (X1 + X2 + X3 + X4)/4 var2 = (X1 + X2 + X3)/3 all of the X variables are supposed to be measuring similar constructs not surprisingly, these are highly correlated (r = .98), the question is how

For the query below I have also included the follwing information. Thanks for your replies > str(FeaturePresenceMatrix) chr [1:65530, 1:40] "0" "0" "0" "0" "1" "0" "0" "0" "0" ... - attr(*, "dimnames")=List of 2 ..$ : chr [1:65530] "4" "5" "6" "7" ...

Dear list, Below I've written a clunky for loop that counts NA's in a row, replacing all with NA if there are more than 3 missing values, or keeping the values if 4 or more are present. This is sample code from a very large dataframe I'm trying to clean up. I know there are many simpler more elegant solutions to this little problem. Would someone be willing to show me how to

Hello, I would appreciate if someone could help me resolve the following: 1. df1[!is.na( X1 | X2 | X3 | X4 | X5),][,1:5] # This does not work 2. Is these message harmful? The following object(s) are masked from 'df1 (position 3)': X1, X2, X3, X4, X5 Thanks, Pradip Muhuri #Reproducible Example set.seed(5) df1<-data.frame(matrix(sample(c(1:10,NA),100,replace=TRUE),ncol=5))

Hi, I am looking for some generalization of colSums and rowSums for general vector valued functions, and for arrays of more than 2 dimensions. So as a concrete example, suppose I have a 3 dimensional array, given by x = array(1:100,c(3,4,5)). and I want to sum the 3rd index of x to obain a 3 by 4 matrix. Using rowSums would return a vector of length 3 because it treats the last two indices as

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

Dear Rusers, I have met a difficult problem on explaining the differences of principal component analysis(PCA) between R,S-PLUS and SAS/STATA/SPSS, which wasn't met before. Althought they have got the same eigenvalues, their coeffiecients were different. First, I list my results from R,S-PLUS and SAS/STATA/SPSS, and then show the original dataset, hoping sb. to try and explain it.

Dear All, I have a data frame with n columns: X1, X2, ., Xn. Now I want to create a new column: if X1 = X2 = . = Xn, the value is 1; Otherwise, the value is 0. How to do that in a quick way instead of doing (n choose 2) comparisons? Thank you, Frank [[alternative HTML version deleted]]

Hi, I would like to operate on certain columns in a dataframe, but not others. My data looks like this: x1 x2 x3 1 2 3 4 5 6 7 8 9 I want to create a new column named x4 that is the sum of x1 and x2, but NOT x3. I looked at colSums and apply, but those functions seem to use all the columns in a dataframe. How do I only use select columns? If it helps, in Stata this would be gen x4

Hello, I have a particular situation where a single "wrong" observation is impacting the results of a traditional regression to the point that betas become unreliable. I need a way to calculate the most likely betas. Here's an example: set.seed(1) unknownbeta <- matrix(seq(100,500,100),25,5,byrow=TRUE) x <-matrix(runif(25*5),25) y <- rowSums(unknownbeta*x)

Estimados Hoy instale RStudio, y por sorpresa o desconocimiento de mi parte, veo que hay la posibilidad de importar datos excel, spss, sas, stata, texto, recuerdo consultas en la lista al respecto, posiblemente mucho se soluciones con las herramientas propuestas por RStudio. Javier Rubén Marcuzzi [[alternative HTML version deleted]]

Dear List, I want to ask a AIC question based on package library(MuMIn) The relative importance of 16 explanatory variables are assessed using delta AIC in a generalized linear model. Please kindly advise if it is possible to show models with any two only certain variables. Thank you. Elaine I asked a similar question and got a great help for models with only one variable as below.

Dear friends, I'm doing a simulation on logistic regression model, but the programs can't work well,please help me to correct it and give some suggestions. My programs: data<-matrix(rnorm(400),ncol=8) #sample size is 50 data<-data.frame(data) names(data)<-c(paste("x",1:8,sep="")) #8 independent variables,x1-x8; #logistic regression model is

Hi I have a two-column integer matrix like this: R> jj [,1] [,2] [1,] -1 1 [2,] -2 2 [3,] -7 6 [4,] -8 7 [5,] -6 5 [6,] -9 8 [7,] -5 4 [8,] 3 -3 [9,] -10 9 [10,] -4 3 I want a diagnostic that detects whether a row is a multiple of the first row or not. In this case, this would be rows 1,2, and 8. How to do this