I'm just guessing (since as David pointed out, no reproducible example
were given), but this perhaps could be the problem:
R> x <- 1:10
R> y <- rnorm(x)
R> fm <- loess(y ~ x)
R> predict(fm, data.frame(x=5:15))
[1] 0.1830450 0.2145826 -0.2158466 -0.3051978 -0.2635318 -0.1013985
[7] NA
On May 17, 2010, at 4:47 AM, Chintanu wrote:
Hi,
I wonder why my attempt to extend an existing loess fit to a new
data set is
producing error. I was trying the following:
dat = read.csv(choose.files())
x = dat[,2]; y = dat[,1]
x.sort = sort(x)
That is not needed, furthermore, you don't e
Hi,
I wonder why my attempt to extend an existing loess fit to a new data set is
producing error. I was trying the following:
dat = read.csv(choose.files())
x = dat[,2]; y = dat[,1]
x.sort = sort(x)
y.loess = loess(y~x, span=0.75)
# For testing the above fit with a new dataset:
test = read.csv(
> > project.org] On Behalf Of Karl Ove Hufthammer
> > Sent: Tuesday, November 24, 2009 1:11 AM
> > To: r-h...@stat.math.ethz.ch
> > Subject: Re: [R] Loess Fit
> >
> > On Mon, 23 Nov 2009 14:03:11 -0700 Greg Snow
> > wrote:
> > > If you need a fu
> -Original Message-
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-
> project.org] On Behalf Of Karl Ove Hufthammer
> Sent: Tuesday, November 24, 2009 1:11 AM
> To: r-h...@stat.math.ethz.ch
> Subject: Re: [R] Loess Fit
>
> On Mon, 23 Nov 2009
On Mon, 23 Nov 2009 14:03:11 -0700 Greg Snow
wrote:
> If you need a function to reproducibly generate predictions, then
> use loess to generate a set of predictions for a reasonably dense set
> of x-values, then use approxfun or splinefun to create a function to
> interpolate for you. Then th
enter
Intermountain Healthcare
greg.s...@imail.org
801.408.8111
From: Christian Miner [mailto:christian.mi...@gmail.com]
Sent: Monday, November 23, 2009 2:13 PM
To: Greg Snow
Cc: Thomas S. Dye; r-help@r-project.org
Subject: Re: [R] Loess Fit
What if you wanted to do this with multiple x's, mu
@imail.org
>
> 801.408.8111
>
>
>
> *From:* Christian Miner [mailto:christian.mi...@gmail.com]
> *Sent:* Monday, November 23, 2009 2:05 PM
> *To:* Greg Snow
> *Cc:* Thomas S. Dye; r-help@r-project.org
>
> *Subject:* Re: [R] Loess Fit
>
>
>
> Thanks, I&#
. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.s...@imail.org
801.408.8111
From: Christian Miner [mailto:christian.mi...@gmail.com]
Sent: Monday, November 23, 2009 2:05 PM
To: Greg Snow
Cc: Thomas S. Dye; r-help@r-project.org
Subject: Re: [R] Loess Fit
Thanks, I'll try
ntain Healthcare
> greg.s...@imail.org
> 801.408.8111
>
>
> > -Original Message-
> > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-
> > project.org] On Behalf Of Thomas S. Dye
> > Sent: Monday, November 23, 2009 1:39 PM
> > To: Christian
Behalf Of Thomas S. Dye
> Sent: Monday, November 23, 2009 1:39 PM
> To: Christian Miner
> Cc: r-help@r-project.org
> Subject: Re: [R] Loess Fit
>
> Thanks Christian. The client is always right ...
>
> Tom
>
> On Nov 23, 2009, at 10:32 AM, Christian Miner wrote:
>
Thanks Christian. The client is always right ...
Tom
On Nov 23, 2009, at 10:32 AM, Christian Miner wrote:
> sorry, I don't. I have data that I can estimate, but my client wants
> to "What if..." 20 separate scenarios, and that requires a function.
>
> On Mon, Nov 23, 2009 at 12:22 PM, Thomas
Message-
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-
> project.org] On Behalf Of Christian Miner
> Sent: Monday, November 23, 2009 12:04 PM
> To: r-help@r-project.org
> Subject: [R] Loess Fit
>
> I'm working on Loess fit models using R, once I have the
Hi Christian,
Do you have a reference to a publication where this has been done?
All the best,
Tom
On Nov 23, 2009, at 10:15 AM, Christian Miner wrote:
> it's a tricky maneuver. When I finish the fit, the predict function
> will give me the values, and I can smooth this out so it looks like
On Nov 23, 2009, at 2:03 PM, Christian Miner wrote:
I'm working on Loess fit models using R, once I have the fit
accomplished,
I'm looking to back-out the equation of the fitted non-linear curve,
wondering if there is a way to determine this equation in R? I've been
looking but can't find any
I'm working on Loess fit models using R, once I have the fit accomplished,
I'm looking to back-out the equation of the fitted non-linear curve,
wondering if there is a way to determine this equation in R? I've been
looking but can't find any literature. For me, the graph of the function is
great, b
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