Displaying 20 results from an estimated 5000 matches similar to: "LOESS confidence interval"
2010 Oct 26
2
anomalies with the loess() function
Hello Masters,
I run the loess() function to obtain local weighted regressions, given
lowess() can't handle NAs, but I don't
improve significantly my situation......, actually loess() performance leave
me much puzzled....
I attach my easy experiment below
#------SCRIPT----------------------------------------------
#I explore the functionalities of lowess() & loess()
#because I have
2008 Feb 03
3
Drawing a loess line
Dear all,
To draw a lowess line on a plot was a piece of cake; to draw a loess
line, however, seems not that easy. Is the loess plotting implemented
at all in relation to the loess function, or do I have to look in
add-on packages?
Thanks,
Marcin
2010 May 31
3
What does LOESS stand for?
Dear R-community,
maybe someone can help me with this:
I've been using the loess() smoother for quite a while now, and for
the matter of documentation I'd like to resolve the acronym LOESS.
Unfortunately there's no explanation in the help file, and I didn't
get anything convincing from google either.
I know that the predecessor LOWESS stands for "Locally Weighted
2006 Feb 07
2
Prediction method for lowess,loess,lokerns,lpepa,ksmooth
Hi Every Body,
I don't know why some regression functions have no related prediction function. For example lowess, loess, lokerns, lpridge, lpepa, and ksmooth.
What could help? Is there any global or wrapper function so that can help?
Regards,
Amir Safari
---------------------------------
[[alternative HTML version deleted]]
2023 Mar 23
2
loess plotting problem
For some reason the following code is not plotting as I want it to. I want
to plot a "loess" line plotted over a scatter plot. I get a jumble, with
lines connecting all the points. I had a similar problem with "lowess". I
solved that by dropping "NA" rows from the data columns. Please help.
library(stats)
attach(gini_pci_wdi_narm)
plot(ny_gnp_pcap_pp_kd, si_pov_gini)
2010 Nov 22
1
how to sample lowess/loess into matrix ?
code:
x <- rnorm(32)
y <- rnorm(32)
plot(x,y)
lines(lowess(x,y),col='red')
Now I need to sample the lowess function into matrix where one series will
be X and other will be values of lowess at particular X.
--
View this message in context: http://r.789695.n4.nabble.com/how-to-sample-lowess-loess-into-matrix-tp3053458p3053458.html
Sent from the R help mailing list archive at
2012 Aug 08
1
Confidence bands around LOESS
Hi Folks,
I'm looking to do Confidence bands around LOESS smoothing curve.
If found the older post about using the Standard error to approximate it
https://stat.ethz.ch/pipermail/r-help/2008-August/170011.html
Also found this one
http://www.r-bloggers.com/sab-r-metrics-basics-of-loess-regression/
But they both seem to be approximations of confidence intervals and I was
wonder if there was
2023 Mar 23
1
loess plotting problem
Dear Anupam Tyagi,
You didn't include your data, so it's not possible to see exactly what
happened, but I think that you misunderstand the object that loess()
returns. It returns a "loess" object with several components, including
the original data in x and y. So if pass the object to lines(), you'll
simply connect the points, and if x isn't sorted, the points
2023 Mar 23
1
loess plotting problem
Thanks, John.
However, loess.smooth() is producing a very different curve compared to the
one that results from applying predict() on a loess(). I am guessing they
are using different defaults. Correct?
On Thu, 23 Mar 2023 at 20:20, John Fox <jfox at mcmaster.ca> wrote:
> Dear Anupam Tyagi,
>
> You didn't include your data, so it's not possible to see exactly what
>
2001 Aug 14
1
loess() v.s. lowess()
Hi there,
Just out of curious, is there any difference between loess() and
lowess() in R (and Splus in fact).
Which one is more often used?
Thanks,
Ko-Kang Wang
------------------------------------------------------------------------------
Ko-Kang Kevin Wang
Statistical Analysis Division Leader
Software Developers' Klub (SDK)
University of Auckland
New Zealand
2012 Apr 24
1
Scatter plot / LOESS, or LOWESS for more than one parameter
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]]
2011 Mar 18
1
Difficulty with 'loess' function
Hi,
I am trying to create a loess smooth from hydrologic data. My goal is to
create a smooth line that describes discharge at a certain point in time. I
have done this using the 'lowess' function and had no problem, but I'm
having some difficulty with loess. I am inputting the date ('date') and
discharge ('q') values using the 'scan' function, then inputting
2005 Apr 05
2
future update to loess
Background: I'm a student of Prof. Cleveland at Purdue University.
Eventually, we'd like to release a new version of the loess routine in R.
For starters, this implementation would have support for local polynomial
degree 3, better control over the number of cells in the KD tree, and
perhaps a better solution in higher predictor dimension.
I see that Prof. Ripley was responsible for
2008 Aug 05
2
95% CI bands on a Lowess smoother
Hi there,
I'm plotting some glass RI values just by plotting
plot(x)
then I put on my lowess smoother
lines(lowess(x))
now I want to put on some 95% Confidence Interval bands of the lowess
smoother, but don't know how??
Thanks
--
Gareth Campbell
PhD Candidate
The University of Auckland
P +649 815 3670
M +6421 256 3511
E gareth.campbell@esr.cri.nz
gcam032@gmail.com
[[alternative
2012 Mar 08
2
Moving average with loess
Hello All,
I just have a very simple question. I recently switching from Matlab to R, so cannot figure out some of the easy tasks in the new environment.
Is there any weighted local regression smoothing in R? Basically, I want to have weighted moving average. All the functions that I know of need two variables for fitting.
Best,
Robert
2008 May 30
3
loess plot
I was trying to plot some data in R. I used the following code to draw a loess fit and got the output as
>?lines(lowess(log(abs(t(res))), log(abs(t(synthesised)))), col="red")
Error in lowess(log(abs(t(res))), log(abs(t(synthesised)))) :?? NA/NaN/Inf in foreign function call (arg 1)
Then I thought to use your Limma package for background correction. Do you think it's a right
2009 Sep 06
1
[LLVMdev] identifying live in and live out variables in a basic block pass
Hello,
I need to identify the live in (but mostly the live out) variables in a
basic block (pass)
I went over the documentation but couldn't find a way to do it.
can anyone help and if possible point me to some code snippets ...
thanks
- fadi.
-------------- next part --------------
An HTML attachment was scrubbed...
URL:
2012 Apr 30
1
Help with loess "Standard Error of the Residuals"
Dear All
I'm having trouble working out what exactly loess means by its "Standard Error of the Residuals" denoted s
and in particular when the weights argument is invoked.
For example, if the weights are weights are all =1, then s^2 is nearly sum sq res/ (n -1 - 'equiv num paras')
If the weights are all k then s is proportional to k
If the weights are unequal, I
2005 Dec 06
3
strange behavior of loess() & predict()
Dear altogether,
I tried local regression with the following data. These data are a part
of a bigger dataset for which loess is no problem.
However, the plot shows extreme values and by looking into the fits, it
reveals very extreme values (up to 20000 !) although the original data are
> summary(cbind(x,y))
x y
Min. :1.800 Min. :2.000
1st Qu.:2.550
2011 Aug 08
2
confidence interval as shaded band (lme)
Hi all,
I?m trying to plot confidence intervals for the fitted values I get with my
lme model in R.
Is there any way I can plot this in the form of a shaded band, like the
output of geom_smooth() in ggplot2 package. ggplot2 seems to use only lm,
glm, gam, loess and rlm as smoothing methods.
Any advice on the functions I should use to accomplish this will be very
helpful.
Thank you very much.