[R] sciplot question

[Jarle Bjørgeengen]

On May 26, 2009, at 3:02 , Frank E Harrell Jr wrote:

> Jarle Bjørgeengen wrote:
>> On May 26, 2009, at 4:37 , Frank E Harrell Jr wrote:
>>> Manuel Morales wrote:
>>>> On Mon, 2009-05-25 at 06:22 -0500, Frank E Harrell Jr wrote:
>>>>> Jarle Bjørgeengen wrote:
>>>>>> On May 24, 2009, at 4:42 , Frank E Harrell Jr wrote:
>>>>>>
>>>>>>> Jarle Bjørgeengen wrote:
>>>>>>>> On May 24, 2009, at 3:34 , Frank E Harrell Jr wrote:
>>>>>>>>> Jarle Bjørgeengen wrote:
>>>>>>>>>> Great,
>>>>>>>>>> thanks Manuel.
>>>>>>>>>> Just for curiosity, any particular reason you chose  
>>>>>>>>>> standard error , and not confidence interval as the default  
>>>>>>>>>> (the naming of the plotting functions associates closer to  
>>>>>>>>>> the confidence interval .... ) error indication .
>>>>>>>>>> - Jarle Bjørgeengen
>>>>>>>>>> On May 24, 2009, at 3:02 , Manuel Morales wrote:
>>>>>>>>>>> You define your own function for the confidence intervals.  
>>>>>>>>>>> The function
>>>>>>>>>>> needs to return the two values representing the upper and  
>>>>>>>>>>> lower CI
>>>>>>>>>>> values. So:
>>>>>>>>>>>
>>>>>>>>>>> qt.fun <- function(x) qt(p=.975,df=length(x)-1)*sd(x)/ 
>>>>>>>>>>> sqrt(length(x))
>>>>>>>>>>> my.ci <- function(x) c(mean(x)-qt.fun(x), mean(x)+qt.fun(x))
>>>>>>>>> Minor improvement: mean(x) + qt.fun(x)*c(-1,1) but in  
>>>>>>>>> general confidence limits should be asymmetric (a la  
>>>>>>>>> bootstrap).
>>>>>>>> Thanks,
>>>>>>>> if the date is normally distributed , symmetric confidence  
>>>>>>>> interval should be ok , right ?
>>>>>>> Yes; I do see a normal distribution about once every 10 years.
>>>>>> Is it not true that the students-T (qt(... and so on)  
>>>>>> confidence intervals is quite robust against non-normality too ?
>>>>>>
>>>>>> A teacher told me that, the students-T symmetric confidence  
>>>>>> intervals will give a adequate picture of the variability of  
>>>>>> the data in this particular case.
>>>>> Incorrect.  Try running some simulations on highly skewed data.   
>>>>> You will find situations where the confidence coverage is not  
>>>>> very close of the stated level (e.g., 0.95) and more situations  
>>>>> where the overall coverage is 0.95 because one tail area is near  
>>>>> 0 and the other is near 0.05.
>>>>>
>>>>> The larger the sample size, the more skewness has to be present  
>>>>> to cause this problem.
>>>> OK - I'm convinced. It turns out that the first change I made to  
>>>> sciplot
>>>> was to allow for asymmetric error bars. Is there an easy way (i.e.,
>>>> existing package) to bootstrap confidence intervals in R. If so,  
>>>> I'll
>>>> try to incorporate this as an option in sciplot.
>>>
>>> library(Hmisc)
>>> ?smean.cl.boot
>> H(arrel)misc :-)
>> Thanks for valuable input Frank.
>> This seems to work fine. (slightly more time consuming , but what  
>> do we have CPU power for )
>> library(Hmisc)
>> library(sciplot)
>> my.ci <- function(x) c(smean.cl.boot(x)[2],smean.cl.boot(x)[3])
>
> Don't double the executing time by running it twice!  And this way  
> you might possibly get an upper confidence interval that is lower  
> than the lower one.  Do function(x) smean.cl.boot(x)[-1]
>

D'oh

>> lineplot 
>> .CI 
>> (V1 
>> ,V2 
>> ,data 
>> = 
>> d 
>> ,col 
>> = 
>> c 
>> (4 
>> ),err 
>> .col 
>> = 
>> c 
>> (1 
>> ),err 
>> .width 
>> = 
>> 0.02 
>> ,legend 
>> =FALSE,xlab="Timeofday",ylab="IOPS",ci.fun=my.ci,cex=0.5,lwd=0.7)  
>> Have I understood you correct in that this is a more accurate way  
>> of visualizing variability in any dataset , than the students T  
>> confidence intervals, because it does not assume normality  ?
>
> Yes but instead of saying variability (which quantiles are good at)  
> we are talking about the precision of the mean.
>

Right.

>> Can you explain the meaning of B, and how to find a sensible value  
>> (if not the default is sufficient) ?
>
> For most purposes the default is sufficient.  There are great books  
> and papers on the bootstrap for more info, including improved  
> variations on the simple bootstrap percentile confidence interval  
> used here.
>
> Frank

Once again, thanks.

Best regards
- Jarle Bjørgeengen