# R/lttest.R In urca: Unit Root and Cointegration Tests for Time Series Data

```##
## lttest
##
lttest <- function(z, r){
if(!(class(z)=="ca.jo")){
stop("\nObject 'x' must be of class 'ca.jo'\n")
}
r <- as.integer(r)
if(r >= z@P || r < 1){
stop("\nProvide number of cointegration vectors in valid range.\n")
}
idx <- r + 1
df <- length(idx:z@P)
N <- nrow(z@Z0)
test1 <- ca.jo(z@x, ecdet = "const", K=z@lag, season=z@season, dumvar=z@dumvar)
lambda1 <- test1@lambda
test2 <- ca.jo(z@x, ecdet = "none", K=z@lag, season=z@season, dumvar=z@dumvar)
lambda2 <- test2@lambda
teststat <- -N*sum(log((1-lambda1[idx:z@P])/(1-lambda2[idx:z@P])))
pval <- 1 - pchisq(teststat, df)
lttest <- as.matrix(t(c(teststat, pval)))
colnames(lttest) <- c("test statistic", "p-value")
rownames(lttest) <- "LR test"
cat("LR-test for no linear trend\n")
cat("\n")
cat(paste("H0: H*2(r<=", r, ")\n", sep=""))
cat(paste("H1: H2(r<=", r, ")\n", sep=""))
cat("\n")
cat("Test statistic is distributed as chi-square\n")
cat(paste("with", df, "degress of freedom\n", sep=" "))
print(round(lttest, 2))
}
```

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urca documentation built on May 2, 2019, 2:08 a.m.