similar to: A contingency table of counts by case

I have asked a similar question before but this time the problem is somewhat more involved. I have the following data: case;name;x 1;Joe;1 1;Mike;1 1;Zoe;1 2;Joe;1 2;Mike;0 2;Zoe;1 2;John;1 3;Mike;1 3;Zoe;0 3;Karl;0 I would like to count the number of "case" in which any two "name" a. both have "x=1", b. the first has "x=0" - the second has

Dear all, how can I "reshape"/"cast" the following matrix 00;01;10;11 John.Mike;123;313;12;31 John.Jim;54;57;39;36 John.Steve;135;47;47;74 Mike.Jim;63;37;27;16 Mike.Steve;15;15;5;61 Jim.Steve;6;10;34;35 into a set of stacked 2x2 contingency tables 0;1 John;123;12 Mike;313;31 John;54;39 Jim;57;36 John;135;47 Steve;47;16 ... so that the "fisher.test" and

Hi all, for the data below I would like to 1. generate a dummy variable for each group "gr" of the same composition by people, then save each portion in a separate file, 2. compute the frequency of "1"'s in "x" for each person by group "gr". So, "mike" will have freq=2/3, as he has two "1" and one "0" in 3 groups.

Hello, how can I get rid of all dimnames so that: $amat Var3 Var2 Var1 8 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 7 1 1 1 0 1 0 0 0 1 0 0 0 0 0 0 6 1 1 0 1 0 1 0 0 0 1 0 0 0 0 0 5 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 4 1 0 1 1 0 0 1 0 0 0 0 1 0 0 0 3 1 0 1 0 0 0 0 0 0 0 0 0 1 0 0 2 1 0 0 1 0 0 0 0 0 0 0 0 0 1 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0

Given an x-vector with, say, 3 elements, I would like to compute the following vector of permutated products (1-x1)*(1-x2)*(1-x3) (1-x1)*(1-x2)*x3 (1-x1)*x2*(1-x3) x1*(1-x2)*(1-x3) (1-x1)*x2*x3 x1*(1-x2)*x3 x1*x2*(1-x3) x1*x2*x3 Now, I already have the correctly sorted matrix of permutations! So, the input looks something like: #input x<-c(0.3,0.1,0.2) Nx<-length(x) Ncomb<-2^Nx

Dear All, Suppose I have the following dataframe: country;weight;group bul;10;1 cze;12;1 grc;12;1 hun;12;1 prt;12;1 rom14;1 fra;29;2 ita;29;2 gbr;29;2 aut;10;3 bel;12;3 The "group" variable denotes the id-number of a group of countries. How can I re-label the groups in the descending order of their cumulative "weight", which wound be: country;weight;group fra;29;1 ita;29;1

Hallo, I have two vectors of different lengths which contain the same set of values: X < -c(2,6,1,7,4,3,5) Y <- c(1,1,6,4,6,1,4,1,2,3,6,6,1,2,4,4,5,4,1,7,6,6,4,4,7,1,2) How can I replace the values in Y with the index (!) of the corresponding values in X. So 2 appears in X in the first coordinate, so all 2’s in Y should be replaced by 1, etc. Thank you for your help, Serguei

Hi, I am trying to add duplicates of matrix "mat" by row. Commands subset(mat,duplicated(rownames(mat))) or mat[which(duplicated(rownames(mat))),] return only half of the required indices. How can I find the remaining ones, ie the matches, so that I can add them up? Thanks, Serguei ___________________________________________________________________ Austrian Institute of Economic

Dear All! I want to test a coeffcient restriction beta=1 in a univariate model lm (y~x). Entering lm((y-x)~1) does not help since anova test requires the same dependent variable. What is the right way to proceed? Thank you for your help and marry xmas, Serguei Kaniovski ________________________________________ Austrian Institute of Economic Research (WIFO)

Say I have a FOR-loop for computing powers (just a trivial example) for(i in 1:5) { x<-i^2 y<-i^3 } How can I create a data.frame and a 3D plot of (i,x(i),y(i)), i.e. for each iteration Thanks, Serguei Kaniovski -- ___________________________________________________________________ ??sterreichisches Institut f??r Wirtschaftsforschung (WIFO) Name: Serguei Kaniovski

Hi, In the data below, "case" represents cases, "x" binary states. Each "case" has exactly 9 "x", ie is a binary vector of length 9. There are 2^9=512 possible combinations of binary states in a given "case", ie 512 possible vectors. I generate these in the order of the decimals the vectors represent, as:

Hello, how is, for example, the Schwarz criterion is defined for kmeans? It should be something like: k <- 2 vars <- 4 nobs <- 100 dat <- rbind(matrix(rnorm(nobs, sd = 0.3), ncol = vars), matrix(rnorm(nobs, mean = 1, sd = 0.3), ncol = vars)) colnames(dat) <- paste("var",1:4) (cl <- kmeans(dat, k)) schwarz <- sum(cl$withinss)+ vars*k*log(nobs) Thanks

Dear All! my data is on pairs of countries, i and j, e.g.: y,i,j 1,AUT,BEL 2,AUT,GER 3,BEL,GER I would like to create a dummy (indicator) variable for use in regression (using factor?), such that it takes the value of 1 if the country is in the pair (i.e. EITHER an i-country OR an j-country). Thank you for your help, Serguei ________________________________________ Austrian Institute of

Hi all, I apply "optim" to the function "obj", which minimizes the goodness of fit statistic and obtains Pearson minimum chi-squared estimate for x[1], x[2] and x[3]. The vector "fr" contains the four observed frequencies. Since "fr[i]" appears in the denominator, I would like to substitute "0" in the sum if fr[i]=0. I tried an

I've a vector of pairwise correlations in the order low-index element precedes the high-index element, say: corr(1,2)=0.1, corr(1,3)=0.2, corr(2,3)=0.3, corr(3,4)=0.4 How can I construct the corresponding correlation matrix? I tried using the "combn"-function in "combinat" package: library(combinat) combn(c(0.1,0.2,0.3,0.4),2) , but to no avail... Thank you for your

Dear R-Users I would like to estimate a constrained bivariate normal density, the constraint being that the means are of equal magnitude but of opposite signs. So I need to estimate four parameters: mu (meanvector (mu,-mu)) sigma_1 and sigma_2 (two sd deviations) rho (correlation coefficient) I have looked at several packages, including Gaussian mixture models in Mclust, but I am not sure

Hi all, does anyone know how to automatically update starting values in R? I' m fitting multiple nonlinear models and would like to know how I can update starting values without having to type them in. thank all --- On Fri, 12/26/08, r-help-request@r-project.org <r-help-request@r-project.org> wrote: From: r-help-request@r-project.org <r-help-request@r-project.org> Subject:

Hello All, I have a panel date - here a small-scale example: df <- data.frame(cbind(rep(c("AUT","BEL","DEN","GER"),4),cbind(rep(c(1999,2000,2001,2002),4)),sample(10,16,replace=T))) names(df) <- c("country","year","x") SORT <- c("GER","BEL","DEN","AUT") I need to compute the

Hello, I cannot figure out how to use "tapply" to compute the correlation matrix in the variable "x" between the states? The data is in long format, e.g.: state,year,x Alabama,2001,0.45 Alabama,2002,0.47 Alabama,2003,0.48 Alabama,2004,0.44 Arizona,2001,0.34 Arizona,2002,0.32 Arizona,2003,0.38 Arizona,2004,0.36 Thank you in advance for your help, Serguei Kaniovski

Hello! I have the following combinatorial problem. Consider the cumulative sums of all permutations of a given weight vector 'w'. I need to know how often weight in a certain position brings the cumulative sums equal or above the given threshold 'q'. In other words, how often each weight is decisive in raising the cumulative sum above 'q'? Here is what I do: w <-