# R: [R] slope estimations of teeth like data

Petr Pikal petr.pikal at precheza.cz
Tue Jun 15 15:21:46 CEST 2004

```On 15 Jun 2004 at 13:52, Vito Muggeo wrote:

> Dear Petr,
> Probably I don't understand exactly what you are looking for.
>
> However your "plot(x,c(y,z))" suggests a broken-line model for the
> response "c(y,x)" versus the variables x. Therefore you could estimate
> a segmented model to obtain (different) slope (and breakpoint)
> estimates. See the package segmented.

Thank you Vito, but it is not what I want. plot(x,c(y,z)) shows only one "spike"
and I have many such spikes in actual data.

My actual data look like those

set.seed(1)
y <- 0.03*x[1:100]+rnorm(100, mean=.001, sd=.03)
z <- 3-rep(seq(1,100,10),each=10)*.03+rnorm(100,mean=.001, sd=.03)
yy <- NULL
for( i in 1:10) yy <- c(yy,c(y,z)[1:floor(runif(1)*200)])
y.l <- length(yy)
plot(1:y.l, yy)

x axis is actually a time and y is a weight of gradually filled conteiner, which is
irregularly emptied. I want to do an hourly and/or daily averages of increases in
weight (it can by done by aggregate)

myfac <- gl(y.l/12,12,length=1271) #hopefully length is ok

y.agg <- aggregate(diff(yy), list(myfac), mean)
## there will be list(hod=cut(time.axis,"hour")) construction actually

0.03 can be expected average result and some aggregated values ar OK but some
are wrong as they include values from emptying time.

*** This*** is probably what I need, I need to set some logical vector which will
be TRUE when there was a filling time and FALSE during other times. And I
need to specify it according a data I have available.

Best what I was able to do was to consider filling time as a time when let say

diff(yy) >= 0

was between prespecified limits, but you know how it is with real life and
prespecified limits.

Or I can plot my data against time, manually find out regions which are correct
and make a aggregation only with correct data. But there are 24*60*3 values
each day so I prefer not to do it manually.

Or finally I can throw away any hourly average which is not in set limits, but I
prefer to throw away as little data as possible.

I hope I was able to clarify the issue a bit.

Thank you
Best regards
Petr

>
> best,
> vito
>
>
>
> ----- Original Message -----
> From: Petr Pikal <petr.pikal at precheza.cz>
> To: <r-help at stat.math.ethz.ch>
> Sent: Tuesday, June 15, 2004 1:11 PM
> Subject: [R] slope estimations of teeth like data
>
>
> > Dear all
> >
> > Suppose I have teeth like data similar like
> >
> > x <- 1:200
> > y <- 0.03*x[1:100]+rnorm(100, mean=.001, sd=.03)
> > z <- 3-rep(seq(1,100,10),each=10)*.03+rnorm(100,mean=.001, sd=.03)
> > plot(x,c(y,z))
> >
> > and I want to have a gradient estimations for some values from
> > increasing
> part of
> > data
> >
> > like
> >
> > y.agg <- aggregate(diff(c(y,z)),
> > list(rep(seq(1,200,10),each=10)[1:199]),
> mean)
> >
> > y.agg[1:10,]  ##is OK, I want that
> > y.agg[11:20,] ##is not OK, I do not want that
> >
> > actual data are similar but more irregular and have subsequent
> > gradual
> increases
> > and decreases, more like
> >
> > set.seed(1)
> > yy<-NULL
> > for( i in 1:10) yy <- c(yy,c(y,z)[1:floor(runif(1)*200)])
> > length(yy)
> > [1] 1098
> >
> > plot(1:1098,yy)
> >
> > Is there anybody who has some experience with such data, mainly how
> > to
> extract
> > only increasing portions or to filter values of "yy" such as only
> aggregated slopes
> > from increasing parts are computed and other parts are set to NA.
> Sometimes
> > actual data have so long parts of steady or even slightly increasing
> values at
> > decreasing part that aggregated values are slightly positive
> > although they
> are
> > actually from decreasing portion of data.
> >
> > Thank you
> > Petr Pikal
> > petr.pikal at precheza.cz
> >
> > ______________________________________________
> > R-help at stat.math.ethz.ch mailing list
> > https://www.stat.math.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide!
> http://www.R-project.org/posting-guide.html

Petr Pikal
petr.pikal at precheza.cz

```

More information about the R-help mailing list