Model 具有p值和标准差的vecm模型的编码

我运行了VECM模型，只得到了系数值。如何获得相同结果中的p值和标准误差据我所知，答案是：

以下为未调整的自由度：

coeftest(cajorls(ca.jo(finland, ecdet="none", type="eigen", K=2),r=1)$rlm) 
coef(summary(cajorls(ca.jo(finland, ecdet="none", type="eigen", K=2), r=1)$rlm))

V1.eigen <- ca.jo(finland, ecdet="none", type="eigen", K=2) # rank=1
vecm <- cajorls(V1.eigen, r=1)
beta <- V1.eigen@V[,1] 
alfa <- V1.eigen@W[,1] 
residuals <- resid(vecm$rlm)
N <- nrow(residuals)
sigma <- crossprod(residuals)/N     
beta.se <- sqrt(diag(kronecker(solve(crossprod(V1.eigen@RK[,-1])), solve(t(alfa)%*%solve(sigma) %*% alfa))))
beta.t <- c(NA, beta[-1]/beta.se) # deg.of freedom adjusted
names(beta.t) <- rownames(cajorls(ca.jo(finland, ecdet="none", type="eigen", K=2), r=1)$beta) 
beta.t
beta.pval <- dt(beta.t, df=vecm$rlm$df.residual)
beta.pval

以下是调整的自由度：

V1.eigen <- ca.jo(finland, ecdet="none", type="eigen", K=2) # rank=1
vecm <- cajorls(V1.eigen, r=1)
beta <- V1.eigen@V[,1] 
alfa <- V1.eigen@W[,1] 
residuals <- resid(vecm$rlm)
N <- nrow(residuals)
sigma <- crossprod(residuals)/N     
beta.se <- sqrt(diag(kronecker(solve(crossprod(V1.eigen@RK[,-1])), solve(t(alfa)%*%solve(sigma) %*% alfa))))
beta.t <- c(NA, beta[-1]/beta.se) # deg.of freedom adjusted
names(beta.t) <- rownames(cajorls(ca.jo(finland, ecdet="none", type="eigen", K=2), r=1)$beta) 
beta.t
beta.pval <- dt(beta.t, df=vecm$rlm$df.residual)
beta.pval

据我所知，答案是：

以下为未调整的自由度：

coeftest(cajorls(ca.jo(finland, ecdet="none", type="eigen", K=2),r=1)$rlm) 
coef(summary(cajorls(ca.jo(finland, ecdet="none", type="eigen", K=2), r=1)$rlm))

V1.eigen <- ca.jo(finland, ecdet="none", type="eigen", K=2) # rank=1
vecm <- cajorls(V1.eigen, r=1)
beta <- V1.eigen@V[,1] 
alfa <- V1.eigen@W[,1] 
residuals <- resid(vecm$rlm)
N <- nrow(residuals)
sigma <- crossprod(residuals)/N     
beta.se <- sqrt(diag(kronecker(solve(crossprod(V1.eigen@RK[,-1])), solve(t(alfa)%*%solve(sigma) %*% alfa))))
beta.t <- c(NA, beta[-1]/beta.se) # deg.of freedom adjusted
names(beta.t) <- rownames(cajorls(ca.jo(finland, ecdet="none", type="eigen", K=2), r=1)$beta) 
beta.t
beta.pval <- dt(beta.t, df=vecm$rlm$df.residual)
beta.pval

以下是调整的自由度：

V1.eigen <- ca.jo(finland, ecdet="none", type="eigen", K=2) # rank=1
vecm <- cajorls(V1.eigen, r=1)
beta <- V1.eigen@V[,1] 
alfa <- V1.eigen@W[,1] 
residuals <- resid(vecm$rlm)
N <- nrow(residuals)
sigma <- crossprod(residuals)/N     
beta.se <- sqrt(diag(kronecker(solve(crossprod(V1.eigen@RK[,-1])), solve(t(alfa)%*%solve(sigma) %*% alfa))))
beta.t <- c(NA, beta[-1]/beta.se) # deg.of freedom adjusted
names(beta.t) <- rownames(cajorls(ca.jo(finland, ecdet="none", type="eigen", K=2), r=1)$beta) 
beta.t
beta.pval <- dt(beta.t, df=vecm$rlm$df.residual)
beta.pval

V1.eigen