similar to: updated package "lmtest" 0.9-2

Hi, I am trying to learn time series, and I am attending a colleague's course on Econometrics. However, he uses e-views, and I use R. I am trying to reproduce his examples in R, but I am having problems specifying a AR(1) model. Would anyone help me with my code? Thanks in advance! Reproducible code follows: download.file("https://sites.google.com/a/proxima.adm.br/main/ex_32.csv

> Dear R Helpers! > > bgtest{lmtest} performs the Breusch-Godfrey test for higher > order serial > correlation. > > Is the Higher Order Correlation function already programmed in > R I couldn't find it? > > Sergei Petrov > ?acf ?pacf HTH, Bernhard ---------------------------------------------------------------------- If you have received this e-mail

I have been reading about autocorrelation in linear models over the last couple of days, and I have to say the more I read, the more confused I get. Beyond confusion lies enlightenment, so I'm tempted to ask R-Help for guidance. Most authors are mainly worried about autocorrelation in the residuals, but some authors are also worried about autocorrelation within Y and within X vectors

Hi, I'm dealing with time series. I usually use stl() to estimate trend, stagionality and residuals. I test for normality of residuals using shapiro.test(), but I can't test for autocorrelation and heteroskedasticity. Is there a way to perform Durbin-Watson test and Breusch-Pagan test (or other simalar tests) for time series? I find dwtest() and bptest() in the package lmtest, but it

Hello! I have a data frame mysample (sorry for a long way of creating it below - but I need it in this form, and it works). I regress Y onto X1 through X11 - 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

Hi all, Within a foreach loop with doSNOW, we cant call functions which come from the non-default package. We need to load(require/library) the package once more within the foreach loop. Anyone knows why would happen like this? Is it caused by the snow package and something happened when "snow" parallelize the job? Other than load the package once more with in the foreach loop, is

Dear R-users, I've been using R for a while and I am very satisfied! Unfortunately, I still have not figured out an efficient and general way to construct and use lags of time series, especially when I need to work with different packages. Let me give an example. I have two time series x and y and I want to estimate a variaty of distributed lags models and run different tests

Hi, P-values in Durbin-Watson test obtained through the use of functions available in packages "lmtest" and "car" are different. The difference is quite significant. function "dwtest" in "lmtest" is much faster than "burbinwatson" in "car". Actually, you can take a nap while the latter trying to calculated Durbin-Watson test. My question

Should "dwtest" and "durbin.watson" be giving me the same DW statistic and p-value for these two fits? library(lmtest) library(car) X <- c(4.8509E-1,8.2667E-2,6.4010E-2,5.1188E-2,3.4492E-2,2.1660E-2, 3.2242E-3,1.8285E-3) Y <- c(2720,1150,1010,790,482,358,78,35) W <- 1/Y^2 fit <- lm(Y ~ X - 1) dwtest(fit,alternative="two.sided")

Dear editor: I'm writing this letter to enquire where can I download the package of "lmtest". Can you send me this package? THanks a lot. Best regards, Shu-Fei Wu

Hi, R core team I am using the function {aidsEst} in package [micEcon] to do an AIDS model now. So far, everything is good. But I want to test the auto correlation and heteroskedasticity of the individual equation from AIDS demand system. How can I return the individual equation? PS: serial correlation test is {bgtest} in package [lmtest] and heteroskedasticity is {bptest} in package

Hello all- I have two time series, Index1stdiff and Comps1stdiff. I regressed the first on the second and R returned the summary stats I expected. Then I looked at and plotted the residuals. I then wanted to assess autocorrelation characteristics and tried to run a Durbin-Watson using: library(lmtest) dwtest(formula=Index1stdiff~Comps1stdiff,alternative=c("greater")) I am

Hi r-programmers, I performe Breusch-Pagan tests (bptest in package lmtest) to check the homoscedasticity of the residuals from a linear model and I carry out carry out White's test via bptest (formula, ~ x * z + I(x^2) + I(z^2)) include all regressors and the squares/cross-products in the auxiliary regression. But what can I do if I want find coefficient and p-values of variables x, z, x*z,

Dear all, Trying to test for heteroskedasticity I tried several test from the car package respectively lmtest. Now that they produce rather different results i am somewhat clueless how to deal with it. Here is what I did: 1. I plotted fitted.values vs residuals and somewhat intuitively believe, it isn't really increasing... 2. further I ran the following tests bptest (studentized

Dear useRs, a new version of the lmtest package is available from CRAN. Thanks to Giovanni Millo who provided the initial versions of several new functions (and many helpful discussions), there is new functionality for the comparison of nested and non-nested linear models. For non-nested model comparisons, the Cox test, encompassing test and J test are now available. For nested model

Dear useRs, a new version of the lmtest package is available from CRAN. Thanks to Giovanni Millo who provided the initial versions of several new functions (and many helpful discussions), there is new functionality for the comparison of nested and non-nested linear models. For non-nested model comparisons, the Cox test, encompassing test and J test are now available. For nested model

Hi, I want to test for independence in my GLS model fitp2, but when I try to use the dwtest function in the lmtest library, I get the error message "Error in terms.default(formula) : no terms component". The model and data set are below. Any suggestions would be really helpful! Thanks a lot in advance, M. Grace fitp2:

Hello Uwe First, I want to thank you for spending your time replying to my mail. I'm very impressed with the speed that my question was answered. I'm new at R (about two weeks) and reading your mail made me realize that it was indeed a question of vectors of different lengths. I thinked that I could create a function ("carfun") without creating a "x" vector, since

On Mon, 4 Apr 2016, varin sacha via R-help wrote: > Hi Deepak, > > In econometrics there is another test very often used : the white test. > The white test is based on the comparison of the estimated variances of > residuals when the model is estimated by OLS under the assumption of > homoscedasticity and when the model is estimated by OLS under the > assumption of

Hi everyone, I've downloaded the lmtest package, but I'm having trouble building it. Here's the output: copland:/home/wilson/tmp# R CMD INSTALL -l /usr/lib/R/library lmtest_0.9-0.tar.gz * Installing *source* package 'lmtest' ... ** libs g77 -fPIC -g -O2 -c pan.f -o pan.o gcc -shared -o lmtest.so pan.o -L/usr/lib/gcc-lib/i386-linux/2.95.4 -lreadline -ldl -lncurses