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F-test with HAC estimate
Can regression and IDW spatial interpolation be done in one model in R?Coefficient estimates for model with more than one categorical explanatory variableAccounting for temporal correlation in GLMMHow can I perform a linear regression on my group variances in R?Newey West and paired t test to correct for autocorrelationPerforming Anova on Bootstrapped Estimates from Quantile RegressionR: wald test on multivariate regression modelR: Coeftest causes errorHow to get confidence interval for hypothesis test of non-linear multiple parametersPartial residual plot with confidence intervals in R for multivariate generalized linear regression
.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty margin-bottom:0;
I am calculating a multi-variate OLS regression in R, and I know the residual are autocorrelated. I know I can use Newey-West correction when performing the t-test to check whether one of the coefficient is zero. I can do that using:
require(sandwich)
model <- lm(y ~ x1 + x2)
coeftest(model, vcov=NeweyWest(model))
where y was the variable to regress and x1 and x2 the predictor. This seems a good approach since my sample size is large.
But what if I want to run an F-test to test whether the coefficient of x1 is 1 and the coefficient of x2 is zero simultaneously? I cannot find a way to do that in R, if I want to account for the autocorrelation of the residuals. For instance, if I use the function linearHypothesis in R, it seems that Newey-West cannot be used as an argument of vcov. Any suggestion? An alternative would be to do bootstrapping to estimate a confidence ellipse for my point (1,0), but I was hoping to use an F-test if possible. Thank you!
r statistics autocorrelation
asked Mar 26 at 1:18
HakuhoSanHakuhoSan
61 bronze badge
add a comment |
I am calculating a multi-variate OLS regression in R, and I know the residual are autocorrelated. I know I can use Newey-West correction when performing the t-test to check whether one of the coefficient is zero. I can do that using:
require(sandwich)
model <- lm(y ~ x1 + x2)
coeftest(model, vcov=NeweyWest(model))
where y was the variable to regress and x1 and x2 the predictor. This seems a good approach since my sample size is large.
But what if I want to run an F-test to test whether the coefficient of x1 is 1 and the coefficient of x2 is zero simultaneously? I cannot find a way to do that in R, if I want to account for the autocorrelation of the residuals. For instance, if I use the function linearHypothesis in R, it seems that Newey-West cannot be used as an argument of vcov. Any suggestion? An alternative would be to do bootstrapping to estimate a confidence ellipse for my point (1,0), but I was hoping to use an F-test if possible. Thank you!
r statistics autocorrelation
asked Mar 26 at 1:18
HakuhoSanHakuhoSan
61 bronze badge
1
No data. Code is not reproducible.
– 42-
Mar 26 at 2:33
add a comment |
I am calculating a multi-variate OLS regression in R, and I know the residual are autocorrelated. I know I can use Newey-West correction when performing the t-test to check whether one of the coefficient is zero. I can do that using:
require(sandwich)
model <- lm(y ~ x1 + x2)
coeftest(model, vcov=NeweyWest(model))
where y was the variable to regress and x1 and x2 the predictor. This seems a good approach since my sample size is large.
But what if I want to run an F-test to test whether the coefficient of x1 is 1 and the coefficient of x2 is zero simultaneously? I cannot find a way to do that in R, if I want to account for the autocorrelation of the residuals. For instance, if I use the function linearHypothesis in R, it seems that Newey-West cannot be used as an argument of vcov. Any suggestion? An alternative would be to do bootstrapping to estimate a confidence ellipse for my point (1,0), but I was hoping to use an F-test if possible. Thank you!
r statistics autocorrelation
asked Mar 26 at 1:18
HakuhoSanHakuhoSan
61 bronze badge
I am calculating a multi-variate OLS regression in R, and I know the residual are autocorrelated. I know I can use Newey-West correction when performing the t-test to check whether one of the coefficient is zero. I can do that using:
require(sandwich)
model <- lm(y ~ x1 + x2)
coeftest(model, vcov=NeweyWest(model))
where y was the variable to regress and x1 and x2 the predictor. This seems a good approach since my sample size is large.
But what if I want to run an F-test to test whether the coefficient of x1 is 1 and the coefficient of x2 is zero simultaneously? I cannot find a way to do that in R, if I want to account for the autocorrelation of the residuals. For instance, if I use the function linearHypothesis in R, it seems that Newey-West cannot be used as an argument of vcov. Any suggestion? An alternative would be to do bootstrapping to estimate a confidence ellipse for my point (1,0), but I was hoping to use an F-test if possible. Thank you!
r statistics autocorrelation
r statistics autocorrelation
asked Mar 26 at 1:18
HakuhoSanHakuhoSan
61 bronze badge
asked Mar 26 at 1:18
HakuhoSanHakuhoSan
61 bronze badge
asked Mar 26 at 1:18
HakuhoSanHakuhoSan
61 bronze badge
asked Mar 26 at 1:18
HakuhoSanHakuhoSan
61 bronze badge
asked Mar 26 at 1:18
HakuhoSanHakuhoSan
61 bronze badge
61 bronze badge
1
No data. Code is not reproducible.
– 42-
Mar 26 at 2:33
add a comment |
1
No data. Code is not reproducible.
– 42-
Mar 26 at 2:33
1
1
No data. Code is not reproducible.
– 42-
Mar 26 at 2:33
No data. Code is not reproducible.
– 42-
Mar 26 at 2:33
add a comment |
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No data. Code is not reproducible.
– 42-
Mar 26 at 2:33