bradleyd wrote
> Thanks Pete. The TRIM argument in the MEAN function tells me how to trim
> off decimal points, but I am lost as to how to append the mean values of
> TEMP and IBI between the 10% and 90% quantiles of DAY in each YEAR.
>
> DAY is the julian date that an event occurred in certain y
bradleyd wrote
> That does it, thanks. Do you think you help me a little bit further?
>
> I actually have 4 columns, YEAR, DAY, TEMP , and IBI. They are all
> numeric. I need to calculate the average TEMP and IBI values between the
> 10% and 90% quantiles for each YEAR.
>
> The code
*
> by(data
bradleyd wrote
> Thanks for your help Pete. I can almost get it to work with;
>
>> by(day,year,quantile)
>
> but this only gives me 0% 25% 50% 75% 100%, not the ones I'm looking
> for, 10% and 90%.
>
> I have tried;
>
>> by(day,year,quantile(c(0.1, 0.9))) but this is rejected by
> Error in
bradleyd wrote
> Excuse the request from an R novice! I have a data frame (DATA) that has
> two numeric columns (YEAR and DAY) and 4000 rows. For each YEAR I need to
> determine the 10% and 90% quantiles of DAY. I'm sure this is easy enough,
> but I am a new to this.
>
>> quantile(DATA$DAY,c(0.1,
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