search for: durbinwatsontest

...first without weights, then with weights: regtest1<-lm(Y~., data=mysample[-13])) regtest2<-lm(Y~., data=mysample[-13]),weights=mysample$weight) summary(regtest1) summary(regtest2) Then I calculate Durbin-Watson for both regressions using 2 different packages: library(car) library(lmtest) durbinWatsonTest(regtest1)[2] dwtest(regtest1)$stat durbinWatsonTest(regtest2)[2] dwtest(regtest2)$stat When there are no weights, the Durbin-Watson statistic is the same. But when there are weights, 2 packages give Durbin-Watson different statistics. Anyone knows why? Also, it's interesting that both of them...

Using ordered probit model, I get errors from dwt and bptest. dwt: Error in durbinWatsonTest.default(...) : requires vector of residuals bptest: Error in storage.mode(y) <- "double" : invalid to change the storage mode of a factor I imagine I have to restate as an individual probit model for each category, but is there an easier way? thanks, bp [[alternative HTML versio...

Hi, How could I use R to check Durbin Watson Test Bound? Best, Rebecca

Hello, I am attending a course in Computational Statistics at ETH and in one of the assignments I am asked to prove that a time series is not autocorrelated using the R function "acf". I tried out the acf function with the given data, according to what I found here: http://landshape.org/enm/options-for-acf-in-r/ this test data does not look IID but rather shows some trends so how can I