Super, Are you just interested in having the final intervals computed for you? Or are you trying to compute them yourself so that you can learn more about what they do? Or something else?
If the first is the case then you can just use the multicomp package as you have mentioned. David was assuming that this was your approach and wanted to know why that was not good enough, what you did with multicomp and why you were not satisfied with the results. If you are happy using multicomp and just are not seeing a piece that you are expecting, then show us what you have tried, what the results are, what you expect the results to be, and how the last 2 differ. Then we can better help you. If your goal is to learn, then re-inventing the wheel can be a good thing, but make it clear that learning is the important part, not just getting an answer. Also show us what you have done so far, what references you are using for the formulas, and where you are stuck. If your goal is something else, then give us more details. On Wed, May 4, 2016 at 10:44 PM, super <desolato...@163.com> wrote: > > > Tks for you attention, i want to know Bonferroni, Tukey's, Sheffe > 95%-condence intervals for coefficients in linear regression, for example, > fit <- lm(y ~ x1 + x2) > confint(fit) would give b0,b1,b2 95%CIs, but i want to get Bonferroni, > Tukey's, Sheffe 95%-condence intervals for these coefficients. Do anyone > happen to know it? > > > > > > > > At 2016-05-05 03:55:45, "David Winsemius" <dwinsem...@comcast.net> wrote: >> >>> On May 4, 2016, at 7:45 AM, super <desolato...@163.com> wrote: >>> >>> >>> Dear experts, >>> I have a problem in compute Bonferroni,Tukey's,Sheffe 95%-condence >>> intervals for coefficients B1,B2,B3 in linear regression using R? how can i >>> do it? I only know how to compute these three cofindence intervals in >>> multicomparsion by using multcomp package, and i am search a lot for how to >>> comupte the three CIs for linear regression coefficients but without any >>> useful information, so, plz help me ~ >> >>Your question does not detail where the 'confint' function in pkg:multcop is >>letting you down. After the first few lines of the first example I type: >> >>confint(wht) >> >>#--------------- >>And get: >> >> Simultaneous Confidence Intervals >> >>Multiple Comparisons of Means: Tukey Contrasts >> >> >>Fit: aov(formula = breaks ~ wool + tension, data = warpbreaks) >> >>Quantile = 2.4155 >>95% family-wise confidence level >> >> >>Linear Hypotheses: >> Estimate lwr upr >>M - L == 0 -10.0000 -19.3536 -0.6464 >>H - L == 0 -14.7222 -24.0758 -5.3687 >>H - M == 0 -4.7222 -14.0758 4.6313 >> >> >>Subsequent examples on that page use linear regression models as there >>starting point. >> >>-- >> >>David Winsemius >>Alameda, CA, USA >> > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. -- Gregory (Greg) L. Snow Ph.D. 538...@gmail.com ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
