[R] how to compute Bonferroni, Tukey's, Sheffe 95%-condence intervals for coefficients B1, B2, B3 in linear regression?

[super]

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" <dwinsemius at comcast.net> wrote:
>
>> On May 4, 2016, at 7:45 AM, super <desolator88 at 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
>