similar to: Fitting a trend-line

Dear R-users, I am using R(a package igraph) to calculate certain topological features of networks. When I try to draw a plot between these features I get an error. Following is the code I am using : *> plot(met_eco_deg,met_eco_bet) > lmout<-lm(met_eco_bet ~ met_eco_deg) > abline(lmout) Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...) : plot.new

Hi all , I am facing some problems with 'ls' command. Whenever I use it I get the following error : ls("KEGG.db") Error in as.environment(pos) : no item called "KEGG.db" on the search list ls("pkgname") Error in as.environment(pos) : no item called "KEGG.db" on the search list and this is true for any package. Can anything be done

hej! can anyone help me with a hint how to find a function to fit a linear trend line into a scatter plot. as well as testing it for significance. thanx/thisse

Hi all, I am trying to construct a frequency distribution graph i.e. suppose there is a variable *"k"* and it takes a range of values. What I want to do is to plot *"P(k)" *(probability/frequency of finding a specific value of *"k"*) vs *"k"*.I would like to get a smooth curve between "P(k) vs k". I have already tried

Dear all, I have this directory structure : Dir1 Dir2 Dir3 Dir4 ......................... A.xml D.xml G.xml B.xml E.xml H.xml C.xml F.xml I.xml Within each of these directories (Dir1, Dir2 etc) there are a num of xml files (A.xml, B.xml etc). What I want to do is to enter into the first directory read all the xml files do certain operations

Hi all, Presently I have R-2.6 version installed on my system. Because of this I am unable to install certain packages.Will an "updatepackages()" command help or would I have to uninstall the older version of R and then install the newer versions ? Can anyone help me out ? Thanks in advance. Anupam Sinha [[alternative HTML version deleted]]

Dear list users How is it possible to visualise both a linear trend line and a quadratic trend line on a plot of two variables? Here my almost working exsample. data(Duncan) attach(Duncan) plot(prestige ~ income) abline(lm(prestige ~ income), col=2, lwd=2) Now I would like to add yet another trend line, but this time a quadratic one. So I have two trend lines. One linear trend line

Although this should be trivial, I'm having a spot of trouble. I want to make a lattice plot of the format y1+y2 ~ x | grp but then fit a lm to each y variable and add an abline of those models in different colors. If the xyplot followed y~x|grp I would write a panel function as below, but I'm unsure of how to do that with y1 and y2 without reshaping the data before hand. Thoughts

I have a 3d scatter plot and I need to add a trend line. I can add a regression plane, but I need a line, not a plane. Thanks. -- View this message in context: http://n4.nabble.com/3d-trend-line-tp1053686p1053686.html Sent from the R help mailing list archive at Nabble.com.

Dear all , I am trying to install a package by name 'netmodels' keep on getting the following error : > install.packages("netmodels") Warning in install.packages("netmodels") : argument 'lib' is missing: using '/usr/lib64/R/library' also installing the dependency ‘VGAM’ trying URL

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 >

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

How can I had a trend line to my plot? My data looks like this: Date=seq(as.Date("1910/1/1"), as.Date("1920/1/1"), "day") Values=runif(length(Date), min=-5, max=5) dataset=data.frame(Values,as.Date(Date)) I just want to add a linear trend line to this plot(dataset,col=rgb(1,0,0,1/8),cex=0.5,pch=19) -- View this message in context:

Dear all, I have recently installed R on a Red Hat Enterprise Linux (RHEL5) system. But I am unable to load R and it is giving the following error : */usr/local/lib/R/bin/exec/R: error while loading shared libraries: libreadline.so.5: cannot open shared object file: No such file or directory* I have checked for the presence of the above mention library and found that the library

>>>>> Anupam Tyagi >>>>> on Tue, 9 Jul 2024 16:16:43 +0530 writes: > How can I do automatic knot selection while fitting piecewise linear > splines to two variables x and y? Which package to use to do it simply? I > also want to visualize the splines (and the scatter plot) with a graph. > Anupam NB: linear splines, i.e. piecewise

Hi, I am trying to fit a logarithmic trendline to a scatterplot of a species accumulation curve. I've tried abline, lines, curve and scatter.smooth but none of these work. Can anyone help please, Kyran

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)

How can I do automatic knot selection while fitting piecewise linear splines to two variables x and y? Which package to use to do it simply? I also want to visualize the splines (and the scatter plot) with a graph. Anupam [[alternative HTML version deleted]]

Dear R users, I am currently analyzing a dataset using lme(). The model I use has the following structure: model<-lme(response~Covariate+TreatmentA+TreatmentB,random=~1|Block/Plot,method="ML") When I plot the residuals against the fitted values, I see a clear positive trend (meaning that the variance increases with the mean). I tried to solve this issue using weights=varPower(),

I'm using pairs() to generate a scatterplot matrix; pairs(~ Fuzzy.gray.white.ratio+Fuzzy.gw.t.score+AgeWhenTested+signal_mean.noise, data=datam,subset=status=="control",main="Controls", labels=c("G/W","Peak Separation","Age","S/N")) How can I add regression lines to the plots?