r - Dependency matrix -

i need build dependency matrix 91 variables of data-set.

i tried use codes, didn't succeed.

here part of important codes:

p<- length(dati) chisquare <- matrix(dati, nrow=(p-1), ncol=p) 

it should create squared-matrix variables

system.time({for(i in 1:p){     for(j in 1:p){         <- dati[, rn[i+1]]         b <- dati[, cn[j]]         chisquare[i, (1:(p-1))] <- chisq.test(dati[,i], dati[, i+1])$statistic         chisquare[i, p] <- chisq.test(dati[,i], dati, i+1])$p.value     }} }) 

it should relate "p" variables analyze whether dependent each other

error in `[.data.frame`(dati, , rn[i + 1]) :    not defined columns selected  moreover: there 50 , more alerts (use warnings() read first 50)  timing stopped at: 32.23 0.11 32.69   warnings() #let's check >: in chisq.test(dati[, i], dati[, + 1]) :   chi-squared approximation may incorrect 

chisquare #all cells (unless in last column seems have p-values) have same values row

i tried way, provided me knows how manage r better me:

#strange values have in columns sum(dati == 'x')  #replacing "x" x x <- dati[dati=='x']  #distribution of answers each question answers <- t(sapply(1:ncol(dati), function(i) table(factor(dati[, i], levels = -2:9), usena = 'always')))  rownames(answers) <- colnames(dati) answers #correlation pairs  i<- diag(ncol(dati))  #empty diagonal matrix  colnames(i) <- rownames(i) <- colnames(dati) rn <- rownames(i) cn <- colnames(i)  #loop system.time({     for(i in 1:ncol(dati)){         for(j in 1:ncol(spain)){             <- dati[, rn[i]]             b <- dati[, cn[j]]             r <- chisq.test(a,b)$statistic             r <- chisq.test(a,b)$p.value             i[i, j] <- r         }      } })   user  system elapsed    29.61    0.09   30.70   there 50 , more alerts (use warnings() read first 50)  warnings() #let's check -> : in chisq.test(a, b) : chi-squared approximation may incorrect  diag(i)<- 1  #result head(i) 

the columns stop @ 5th variable, whereas i need check dependency between variables. each one.

i don't understand i'm wrong, hope i'm not far...

i hope receive help, please.

you apparently trying compute p-value of chi-squared test, pairs of variables in dataset. can done follows.

# sample data n <- 1000 k <- 10 d <- matrix(sample(letters[1:5], n*k, replace=true), nc=k) d <- as.data.frame(d) names(d) <- letters[1:k]  # compute p-values k <- ncol(d) result <- matrix(1, nr=k, nc=k) rownames(result) <- colnames(result) <- names(d) for(i in 1:k) {   for(j in 1:k) {       result[i,j] <- chisq.test( d[,i], d[,j] )$p.value   } } 

in addition, there may wrong data, leading warnings get, not know it.

your code has many problems me try enumerate them (you start try create square matrix different number of rows , columns, , lost).