[R] Scatter plot / LOESS, or LOWESS for more than one parameter

[Greg Snow]

Assuming that you want event as the x-axis (horizontal) you can do
something like (untested without reproducible data):

par(mfrow=c(2,1))
scatter.smooth( event, pH1 )
scatter.smooth( event, pH2 )

or

plot( event, pH1, ylim=range(pH1,pH2) , col='blue')
points( event, pH2, col='green' )
lines( loess.smooth(event,pH1), col='blue')
lines( loess.smooth(event,pH2), col='green')

Only do the second one if pH1 and pH2 are measured on the same scale
in a way that the comparison and any crossings are meaningful or if
there is enough separation (but not too much) that there is no
overlap, but still enough detail.



On Mon, Apr 23, 2012 at 10:40 PM, R. Michael Weylandt
<michael.weylandt at gmail.com> wrote:
> The scatter plot is easy:
>
> plot(pH1 ~ pH2, data = OBJ)
>
> When you say a loess for each -- how do you break them up? Are there
> repeat values for pH1? If so, this might be hard to do in base
> graphics, but ggplot2 would make it easy:
>
> library(ggplot2)
> ggplot(OBJ, aes(x = pH1, y = pH2)) + geom_point() + stat_smooth() +
> facet_wrap(~factor(pH1))
>
> or something similar.
>
> Michael
>
> On Mon, Apr 23, 2012 at 11:26 PM, David Doyle <kydaviddoyle at gmail.com> wrote:
>> Hi folks.
>>
>> If I have the following in my "data"
>>
>> event    pH1    pH2
>> 1            4.0     6.0
>> 2            4.3     5.9
>> 3            4.1     6.1
>> 4            4.0     5.9
>> and on and on..... for about 400 events
>>
>> Is there a way I can get R to plot event vs. pH1  and event vs. pH2 and
>> then do a loess or lowess line for each??
>>
>> Thanks in advance
>> David
>>
>>        [[alternative HTML version deleted]]
>>
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>> and provide commented, minimal, self-contained, reproducible code.
>
> ______________________________________________
> R-help at 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.



-- 
Gregory (Greg) L. Snow Ph.D.
538280 at gmail.com