On 11/07/2012 12:31 AM, kun...@gfz-potsdam.de wrote:
Hi,
I have a question about the computation of confidence intervals in the zyp
package, in particular using the functions zyp.sen and confint.zyp, or
zyp.yuepilon.
(1) I'm a bit confused about the confidence intervals given by zyp.sen and
confint.zyp. When I request a certain confidence interval in the function, the
R output seems to deliver another confidence interval, e.g. when I set
level=0.95 in the function, then the output is for 0.025 and 0.975 (instead of
the expected 0.05 and 0.95). See example below. Which confint statement is the
right one?
(2) I checked the documentation but did not find a specification about which
confidence interval is used in the zyp.yuepilon function. It seems to be the
same as level=0.95 in confint.zyp (I'm not sure if this is 0.95 or 0.975 - see
above).
Maybe, I'm just not seeing the obvious explanation... Could anybody advise me?
Thanks in advance,
Katy
---
My example:
x<- c(0, 1, 2, 3, 4, 5)
y<- c(6, 4, 1, 8, 7, 8)
# zyp.sen and confint.zyp function
slope<- zyp.sen(y~x)
slope$coef
Intercept x
4.5000000 0.6666667
ci_99<- confint.zyp(slope, level=0.99)
ci_99
0.005 0.995
Intercept -2.071288 10.07129
x -3.000000 3.00000
ci_95<- confint.zyp(slope, level=0.95)
ci_95
0.025 0.975
Intercept -0.6196794 8.619679
x -2.5000000 2.333333
ci_90<- confint.zyp(slope, level=0.90)
ci_90
0.05 0.95
Intercept 0.1230428 7.876957
x -2.0000000 2.000000
# zyp.yuepilon
# confidence interval corresponds to nominal 0.95 interval in confint.zyp
(output 0.025 0.975)
xy_senslope<- zyp.yuepilon (y, conf.intervals=TRUE)
xy_senslope
lbound trend trendp ubound tau sig
nruns autocor valid_frac
-2.50000000 0.66666667 4.00000000 2.33333333 0.80000001 0.08641075
1.00000000 -0.22400000 1.00000000
linear intercept
0.74285714 3.83333333
Hi Katy,
I didn't see an answer to this, so I'll attempt one. A 95% confidence
interval is defined as an interval within which 95% of replicated values
will fall. In most cases, the preferred confidence interval among the
many which could be calculated is symmetric about the observed value in
the sense that half of the replicated values are expected to fall above
the observed value and half below. This means that 2.5% of replications
would be expected to produce values below the lower confidence limit and
2.5% above the upper one. If these proportions were 5% below and 5%
above, you would get a 90% confidence interval.
Jim
______________________________________________
R-help@r-project.org mailing list
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.
