search for: sij

...(c(rep(-N:N, each = reps), rep(-N:N, times = reps)), > nrow = 2, byrow = TRUE) > } > rj<-positions(N)*spacing # all positions in the 2N x 2N array > rj<-rj[1:2,-((dim(rj)[2]-1)/2+1)] # remove rj=(0,0) > > mod<-function(x){sqrt(x[1]^2+x[2]^2)} # modulus > > sij <-function(rj){ > rij=mod(rj-ri) > cos_ij=rj[1]/rij > sin_ij=rj[2]/rij > > A<-(1-1i*k*rij)*(3*cos_ij^2-1)*exp(1i*k*rij)/(rij^3) > B<-k^2*sin_ij^2*exp(1i*k*rij)/rij > > sij<-A+B > } > > s_ij<-apply(rj,2,sij) > S<-sum(s_ij) > alpha_s/(1-alpha_s...

...would, of course, then like R to spit out the massive table with 1000 columns of randomly generated temperature values for each index i to n. Finally I would like to compute the slope estimator associated with the Theil statistic. All I need to do is compute the n(n-1)/n individual slope values; Sij = (Yj -Yi)/(Xj-Xi) where the Ys are the Scores for samples i to n and the Xs are the set of randomly generated temperature values, as before, 1 less than or equal to i less than j less than or equal to n. The median is then the estimator of Beta (the slope). I would like to compute the slopes for...

...t (w.l.o.g.) X1 denote the first r of them, and X2 the last (k-r). Likewise, let mu1 and mu2 denote their respective expectations. Then, of course, the expectation of X2 given X1=x1 is mu2 + S21*inv(S22)*(x1 - mu1) and the covariance matrix of X2 given X1=x2 is S22 - S21*inv(X11)*S12 where Sij is the matrix derived from S by taking the rows corresponding to the indices of Xi and the columns corresponding to the indices of Xj, and these define the MVN conditional distribution of X2 given X1=x1. While these are not difficult to write one's own functions for in R, I feel almost sure th...

Ben trovati. Ho questa _form : <%= error_messages_for ''requirement'' %> <!--[form:requirement]--> <p><label for="requirement[structure_id]">Struttura</label><br/> <%= @structures = Structure.find(:all, :order => "nome").map {|f| [f.nome,f.id] } select(:structure, :id, @structures) %> <p><label