search for: delta_i

Hello, Could someone give me a hint about what might be the difference between running urppTest with Z-alpha and Z-tau in type=c("Z-alpha", "Z-tau")? Is this the underlying equation: delta_y(t) = mu + tau*timetrend+(1-rho)*y(t-1) + alpha_1*delta_y(t-1) + ... + alpha_k*delta_y(t-k) + error term ? I looked at Banerjee et al. mentioned in the fSeries documentation, but that

I am trying to fit a linear mixed model of the form y_ij = X_ij \beta + delta_i + e_ij where e_ij ~N(0,s^2_ij) with s_ij known and delta_i~N(0,tau^2) I looked at the ecme routine in package:pan, but this routine does not allow for different Vi (variance covariance matrix of the e_i vector) matrices for each cluster. Is there an easy way to fit this model in R or should I b...

...;-matrix(nrow=54, ncol=30) mat_Yr_m<-matrix(nrow=54, ncol=30) D<-matrix(nrow=30, ncol=54) DELTA<-(matrix(nrow=30,ncol=54))*50 for (i in 1:length(vec_IS)){ for (j in 1:length(vec_IT)){ Yr_m<-rnorm(54,m=0,sd=1) mat_Yr_m[,j]<-Yr_m delta_i<-lower_m%*%mat_Yr_m[,j] mat_delta[,j]<-as.vector(delta_i) } DELTA_1<-mat_delta[,1] DELTA_2<-mat_delta[,2]-a_1*mat_delta[,1] for (t in 3:length(vec_IT)){ mat_DELTA[,t]<-mat_delta[,t] - a_1*mat_delta[,t-1]...

Hello all, I would like to carry out a single-equation approach of the Error Correction Model such as Delta_y(t) = a + b*y(t-1) + c*x1(t-1) + d*x2(t-1) + e*delta_x1(t) + f*delta_x2(t) + epsilon(t) Where, a, b, c, d, e, f are coefficients to be estimated, y is the dependent variable, and x1, x2 are independent variables. For the single equation approach of ECM, there is a requirement of the

Assume that we collect below data : - subjects = 20 males + 20 females, every single individual is independence, and difference events = 1, 2, 3... n covariates = 4 blood types A, B, AB, O http://r.789695.n4.nabble.com/file/n4245397/CodeCogsEqn.jpeg ?m = hazards rates for male ?n = hazards rates for female Wm = Wn x ?, frailty for males, where ? is the edge ratio of male compare to female Wn =