similar to: How to improve the robustness of "loess"? - example included.

I am using package ks() to build 3D representations of bird territories and calculate territory volume from spatial data (simply x, y, and z coordinates). What I want to do is determine at what sample size (# locations collected) does the territory volume stop increasing. This should give me an idea of the number of points needed for future seasons. So I have a couple of birds each with 200

Dear R list, Can anyone help with a plotting question? I'm trying to display some data on a plot and I've almost got the format I need (see code below), but 2 things I can't get: 1. How to get "Jan","Feb","Mar" on the x=axis instead of 1:3? 2. How to get "T"s on the end of my error bars like you have in standard scientific plots? Any comments

Dear R users I'm having problems in putting special characters (like 佱, 併, 佺 ) in my plots, as much in titles, as in axis names, as in legend...when I save them as a pdf document. They don't appear... I don't know if it is because I'm using a linux platform... The script is the following: library(grDevices) jpeg(file="Fronteira/FronteiraNova.jpeg",

> On Dec 8, 2017, at 6:16 PM, David Winsemius <dwinsemius at comcast.net> wrote: > > >> On Dec 8, 2017, at 4:48 PM, Ashta <sewashm at gmail.com> wrote: >> >> Hi David, Ista and all, >> >> I have one related question Within one group I want to keep records >> conditionally. >> example within >> group A I want keep rows that

You could make numeric vectors, named by the group identifier, of the contraints and subscript it by group name: > DM <- read.table( text='GR x y + A 25 125 + A 23 135 + A 14 145 + A 35 230 + B 45 321 + B 47 512 + B 53 123 + B 55 451 + C 61 521 + C 68 235 + C 85 258 + C 80 654',header = TRUE, stringsAsFactors = FALSE) > > GRmin <- c(A=15, B=40, C=60) > GRmax <-

Hi I am trying to get the tricube weights from the loess outputs as I need to calculate an error function which requires the weight. So I have used the following example from the R: cars.lo <- loess(dist ~ speed, cars, span=0.5, degree=1, family="symmetric") Then i try to get the weights: cars.lo$weights [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

Hi, I'm trying to normalize data by fitting a line through the highest density of points (in a 2D plot). In other words, if you visualize the data as a density plot, the fit I'm trying to achieve is the line that goes through the "crest" of the mountain. This is similar yet different to what LOESS does. I've been using loess before, but it does not exactly that as it takes

hi, new to R and using the car package to do some scatterplots with ellipses hoping to add the area and center points of each ellipse to the legend? looking for some direction / ideas.... here is the script, the data is where golf shots end up by club. x (dispersion), y (distance), group (Club) thanks, sam ## usage: Rscript shotScatter.R infile outfile level1 level2 minX maxX minY maxY

Dear all, I am facing a strange problem with text files formats. I am currently using a C++ code named voro++ (http://math.lbl.gov/voro++/). This code accepts text files with four columns: <id> <x> <y> <z> where id is an identification number and x,y,z are the coordinates of a point in a 3D space. The input file, name it myfile_cpp.txt, is generated by another C++ code

Hello, This sounds like a problem to which many solutions should exist, but I did not manage to find one. Basically, given a list of datapoints, I'd like to keep those within the X% percentile highest density. That would be equivalent to retain only points within a given line of a contour plot. Thanks to anybody who could let me know which function I could use! Best, Emmanuel

Functionally identical but much simpler. Should also better integrate with future layer/viewport changes/fixes. Cc: 10.1 <mesa-stable at lists.freedesktop.org> Signed-off-by: Ilia Mirkin <imirkin at alum.mit.edu> --- Not *strictly* necessary in stable, but it will make backporting later fixes easier. No regressions in piglit. src/gallium/drivers/nouveau/nv50/nv50_program.c | 5

hi! i want to change the "robustness weights" used by loess. these are described on page 316 of chambers and hastie's "statistical models in S" book as r_i = B(e_i,6m) where B is tukey's biweight function, e_i are the residulas, and m is the median average distance from 0 of the residuals. i want to change 6m to, say, 3m. is there a way to do this? i cant

Hi all, I 've got a question about the usage of loess in the modreg package. The documentation (loess.html) states that the smoothing window is either set by span or enp.target. If span is used, the details section of the docs state... <SNIP> DETAILS Fitting is done locally. That is, for the fit at point x, the fit is made using points in a neighbourhood of x, weighted by their

Hi all, I 've got a question about the usage of loess in the modreg package. The documentation (loess.html) states that the smoothing window is either set by span or enp.target. If span is used, the details section of the docs state... <SNIP> DETAILS Fitting is done locally. That is, for the fit at point x, the fit is made using points in a neighbourhood of x, weighted by their

Hello, I need help with the details of loess prediction algorithm. I would like to get it implemented as a part of a measurement system programmed in LabView. My job is provide a detailed description of the algorithm. This is a simple one-dimensional problem - smoothing an (x, y) data set. I found quite a detailed description of the fitting procedure in the "white book". It is also

The following gives two functions for producing distribution graphs: distribution-graph produces a single graph, and multiple.distribution.graph produces a number of graphs side by side. Regards, Tore Wentzel-Larsen statistician Centre for Clinical research Armauer Hansen house Haukeland University Hospital N-5021 Bergen tlf +47 55 97 55 39 (a) faks +47 55 97 60 88 (a) email

Hello, I'm hoping for some help implementing a general optimization problem in R. I'd like to write a program that for a vector of non-negative input values, x, returns a non-negative "normalized" vector y such that sum(y)==1, and y <= maxx (vector of maximum values), and for which sum((x-y)^2) is minimized. Additionally, I'd like to remove (0,minx) from the domain of each

Dear all, I generated a Correlograms and used the panel.ellipse (confidence ellipse and smoothed line) option. Is there a way to get instead of the smoothed line the linear regression? Thanks, As hz -- View this message in context: http://r.789695.n4.nabble.com/Correlograms-and-linear-regression-tp2331071p2331071.html Sent from the R help mailing list archive at Nabble.com.

I'm updating the loess routines to allow for, among other things, arbitrary local polynomial degree and number of predictors. For now, I've given the updated package its own namespace. The trouble is, panel.loess still calls the original code in package:stats instead of the new loess package, regardless of whether package:loess or package:lattice comes first in the search list. If I

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 >