similar to: add a linear regression line to the plot

Dear R users, I see a graph (shown athttps://cid-c486ebef16722625.photos.live.com/self.aspx/%e6%88%91%e5%96%9c%e6%ac%a2%e7%9a%84%e8%8a%b1/untitled.bmp) in a published paper, which is very informative and clear. But I don't know what type the graph is. It looks like a sactter plot but has the points with the same y values are seperate.. I really aprreciate it if someone can tell

Dear R users, I have a question about ploting clock time, the example is as below: y<-seq(from=1, to=30, by=5) x<-c("0:01","1:20", "8:40", "9:25", "15:30", "21:23") x<-as.POSIXct(strptime(paste(x),"%H:%M")) plot(y~x, type="p") I got the plot, but if I want to plot the x range from 1:20 to

Hello, I can`t figure out how can increase the velocity of the fitting data by nls. I have a long data .csv I want to read evry time the first colunm to the other colunm and analisy with thata tools setwd("C:/dati") a<-read.table("Normalizzazione.csv", sep=",", dec=".", header=F) for (i in 1:dim(a[[2]]]) { #preparazione dati da analizzare

Hello guys, I am a total newbie on R, having downloaded it, read the documentation and started playing with it right now. My general question is what 'lr' model can be used for doing a linear regression on points that have a variance associated with them (ie. Monte Carlo simulation results). Actually my Data sets look like: Timestep Energy Variance_of_the_Energy 0.0005 -14.876840

Hi Dears, When I introduce an interaciton in a piecewise model I obtain some quite unusual results. If that would't take u such a problem I'd really appreciate an advise from you. I've reproduced an example below... Many thanks x<-rnorm(1000) y<-exp(-x)+rnorm(1000) plot(x,y) abline(v=-1,col=2,lty=2) mod<-lm(y~x+x*(x>-1)) summary(mod) yy<-predict(mod)

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]]

Hello, I have produced some segmented regressions with the segmented package by Viggo Mutteo. I have some example data and code below. I want to annotate the individual segments with the slope parameter (actually it would be nicer to annotate with 1000*slope and add some small amount of text as well). How can I do it? Reading the docs for segmented I can access all of the slope parameters via a

>>>>> 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

dear all, I apologize for my delay in replying you. Here my contribution, maybe just for completeness: Similar to "earth", "segmented" also fits piecewise linear relationships with the number of breakpoints being selected by the AIC or BIC (recommended). #code (example and code from Martin Maechler previous email) library(segmented) o<-selgmented(y, ~x, Kmax=20,

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

Dear R-list Suppose I have a data set stored in hmet, for which I did get confidence limit on a linear regression as shown below. My question is how I can subset only data points which are within the confidence limit. Thank you. Keun-Hyung --------------------------------------------------------------- Al=rnorm(100, 3) Cd=rnorm(100, 0.2) hmet=data.frame(Al=Al, Cd=Cd) plot(Al,

I am trying to plot a non-linear trend line along with my data. I am sure the solution is simple; any help greatly appreciated. Recent and historic attempts: fit = nls((sd~a+b*exp(-c/time)+d*geology), start=list(a=1, b=1, c=10, d=-1), model=TRUE) plot(time, sd, col=3, main = "Regression", sub=formula(fit)) lines(time, fitted.values(fit), lwd=2) #tt = seq(from=0, to=200, by=10)

Hi - I'd like to construct and plot the percents by year in a small data set (d) that has values between 1988 and 2007. I'd like to have a breakpoint (buy no discontinuity) at 1996. Is there a better way to do this than in the code below? > d year percent se 1 1988 30.6 0.32 2 1989 31.5 0.31 3 1990 30.9 0.30 4 1991 30.6 0.28 5 1992 29.3 0.25 6 1994 30.3

Dear All, I'd like to fit a "kind" of logistic model to small data-set using nonlinear least-squares regression. A transcript of R-script are reproduced below. Estimated B and T (the model's coeff, herein B=-8,50 and T=5,46) seem appropriate (at least visually) but are quite diff from those obtained w/ SPSS (Levenberg-Marquardt): B=-19,56 and T=2,37. Am I doing something wrong in

Hi, I'm trying to verify the calculation of coefficient of determination (r squared) for linear regression. I've done the calculation manually with a simple test case and using the definition of r squared outlined in summary(lm) help. There seems to be a discrepancy between the what R produced and the manual calculation. Does anyone know why this is so? What does the multiple r squared

Dear R users, I am encountering a x axis labeling problem on quite basic plots... I use the following code which displays the labels on the x-axis with a 45 degrees angle: p <- plot(myobject1, type="b", col="red",cex=1, lwd=2, axes=FALSE, ann=FALSE, ylim=c(0,70)) title(main="title", font.main=4) axis(side=1, lab=F) text(axTicks(1), par("usr")[3] - 2,

Hello, A made a xyplot using the lattice library in R (latest version). The publisher of our paper has requested: 1. all tick marks should point inwards instead of outwards. 2. All lines should be thicker (lines, axes, boxes, etc. Everything). Lines is easy...I used: lwd=1.5 but what about the lines of the axes, and the lines that build up the plot itself?....? Any

# I would like to outline the squares in the legend with a black line. Does anyone know how to do this? x.t <- structure(c(5987.387, 4354.516, 3685.789, 6478.592, 5924.315, NA, 8386, 5559.468, NA, 4651.273, 3967.5, NA, 4339.167, 5053.56, NA, 4631.978, 4808.694, NA, 5217.306, 4017.632, NA, 5846.903, 3969.883, NA, 3867.825, 3910.236, NA, 3886.434, 3782.094, NA, 3959.668, 3961.286, NA, 3848.853,

Another solution: library("HelpersMG") plot(0:10,type="n",axes=FALSE,xlab="",ylab="", asp=1) ellipse(center.x = 3, center.y = 5, radius.x = 5, radius.y = 5, lwd=10, col=NA, border=rgb(red = 1, green = 0, blue=0, alpha = 0.5)) ellipse(center.x = 8, center.y = 5, radius.x = 5, radius.y = 5, lwd=10, col=NA, border=rgb(red = 0, green = 1, blue=0, alpha =

Dear All: Thank you very much for all of you. I just have one more thing. Is there a way to fill the borders with small dots, may be different sizes. I tried to do it, but it looks ugly. Here what I tried: library(plotrix) plot(0:10, 0:10, type="n",axes=FALSE,xlab="",ylab="") #### 0:5, draw.circle(4,5,radius=3,border="#ff0000aa", lwd=75)