similar to: need smooth cdf lines

Hi r-users, I would like to overlap 2 ecdf plots.  I tried this below and it gives me two plots of ecdf but just both just in black. par(mar=c(4,4,2,1.2),oma=c(0,0,0,0),xaxs="i", yaxs="i") plot(ecdf(datobs)) lines(ecdf(gam_sum_gen)) Then I try to add colors etc and also the legend but fail. par(mar=c(4,4,2,1.2),oma=c(0,0,0,0),xaxs="i", yaxs="i")

Hi r-users,   I would like to overlap a smooth line on the histogram.  I tried using spline but it does not work. sq     <- seq(0,900,by=50) sq.50  <- as.character(sq) datobs <- sum_pos ## first, plot histogram histo <- hist(datobs,breaks=sq,freq=F) ## extract counts from histogram and calculate the probability in ## each specified interval. Also check the length of the interval is

Hi r-users, I would like my axes to intersect at (0,0).  I tried  xaxs="i",yaxs="i" but it does not change anything.  I hope anybody can help me with this problem.  Here is my code. hist(datobs, prob=TRUE, main ="PDF of the sum of two stations",col="yellowgreen", cex.axis=1.2, xlab="Rainfall (mm)", ylab="Relative frequency", ylim=

Hi r-users, I would like to add a plot of vertical line segment with arrow from (77,.6) to (77,0) and also a horizontal  line segment with arrow from (0,0.6) to (77,.6) .  So far this is what I have: plot(sq, cdf, type="l", lwd=4,col="blue",xaxs="i",yaxs="i", xlab= "Rainfall (mm)", ylab= "Random no.", main="Random number  and

Hi, Does anybody encounter the same problem when we overlap histogram and density     that the density line seem to shift to the right a little bit?           If you do have the same problem, what should we do to correct that?           Thank you.           par(mar=c(4,4,2,1.2),oma=c(0,0,0,0))     hist(datobs,prob=TRUE, main ="Volume of a catchment from four    

Hi,   I would like to distinguish my plots using colors but I got error message.  How do I correct that?     plot(ecdf(z), main ="CDF for observed and simulated weighted sum",type="l",lwd=2,col="blue", xlab="Weighted sum (mm)", ylab="Cumulative Percent", xlim=c(0,15), xaxs ='i', yaxs ='i',ylim=c(0,1)) par(new=TRUE)

This question might seem silly, because I felt that it MUST be in the mailing list archives or help files somewhere, but I simply couldn't find it. I want to make some simple CDF (cumulative distribution function) plots to check whether distributions are Gaussian / normal. But in order to check how "normal" the distribution is, I really need the y-axis to be Gaussian as well

Hi R-users,   I would like to search for the values of seq that match my rand values.  In excel I will use =VLOOKUP(G2,$E$2:$F$32,2).  For example, for rand=.262 it will give me approximately seq=120 and rand=0.964293344, seq=460 and etc.   E           F     G cdf         seq   rand 0.00E+00    0     0.262123478 1.56E-03    20    0.964293344 1.55E-02    40    0.494827113 5.30E-02    60   

Hi r-users,   I have this data below and would like to plot a barplot overlap with a line. This is my data: > hist_50     pdf_obs pdf_gen.50 1  0.000000   0.000000 2  0.083156   0.125366 3  0.132196   0.158230 4  0.126866   0.149432 5  0.120469   0.127897 6  0.121535   0.104096 7  0.103412   0.082171 8  0.082090   0.063539 9  0.065032   0.048408 10 0.050107   0.036470 11 0.036247   0.027236 12

Dear all, I have define a discrete distribution P(y_i=x_i)=p_i, which I want to plot a CDF plot. However, I can not find a function in R to draw it for me after searching R and R-archive. I only find the one for the sample CDF instead my theoretical one. I find stepfun can do it for me, however, I want to plot some different CDF with same support x in one plot. I can not manage how to do it with

Good Afternoon, I'm trying to create a cdf plot, with the following code. It works well, but I have little doubt, if you can help solve. When I create the plot, like the graph line would still not appear with point #cdf x<-table(Dataset$Apcode) View(s) hist(s) *plot(ecdf(x))* x<-1 37607 2 26625 3 5856 4 25992 5 30585 6 16064 7 9850 .. ... .. 186 52 -- View this message in

My machine has 8GB memory. I had quit all other programs that might take a lot of memory when I try the script (before I post the first message in this thread). The cdf file is of only 741 MB. It is strange to me to see the error. On Mon, Dec 28, 2009 at 2:38 AM, Wolfgang Huber <whuber at embl.de> wrote: > Dear Peng Yu > > how big is the RAM of your computer? You could try with

Hi r users,   I would like sort of   cdf         seq   rand 0.00E+00    0     0.262123478 1.56E-03    20    0.964293344 1.55E-02    40    0.494827113 5.30E-02    60    0.733726005 1.16E-01    80    0.800408948 1.97E-01    100   0.925748466 2.88E-01    120   0.047578356 3.80E-01    140   0.266060366 4.68E-01    160   0.125522629 5.48E-01    180   0.701193274 6.18E-01    200   0.915799432

Hello all, I would like to plot the emperical CDF, normal CDF and pareto CDF in the same graph and I amusing the following codes. "z" is a vector and I just need the part when z between 1.6 and 3. plot(ecdf(z), do.points=FALSE, verticals=TRUE, xlim=c(1.6,3),ylim=c(1-sum(z>1.6)/length(z), 1)) x <- seq(1.6, 3, 0.1) lines(x,pgpd(x, 1.544,0.4373,-0.2398), col="red") y

All, Thanks for all of your help & advice! I created a plot starting with qqnorm, if I remember right, but I had to add a LOT of extras. I was surprised that it doesn't include the probability (e.g. 50% at mean) and instead provides the standard deviations (e.g., 0 at mean) on the axis. Plus, there is no line through Q1 & Q3 to help give a sense of the normality of the graph.

Hello, I wanted to know if there is a simple way of getting the inverse cdf for a KDE estimate of a density (using the ks or KernSmooth packages) in R ? The method I'm using now is to perform a numerical integration of the pdf to get the cdf and then doing a search for the desired probablity value, which is highly inefficient and very slow. Thanks, -fj [[alternative HTML version deleted]]

Hi, I have a data set which is assumed to follow weibull distr'. How can I find of cdf for this data. For example, for normal data I used (package - lmomco) >cdfnor(15,parnor(lmom.ub(c(df$V1)))) Also, lmomco package does not have functions for finding cdf for some of the distributions like lognormal. Is there any other package, which can handle these distributions?

Hi all, Just a random shot in the dark. Does anyone have/know of a function for the CDF of a generalized error dist? -- Elliot Williams (ewilliams at ucsd.edu) Economics Department, UC San Diego -------------- next part -------------- An embedded message was scrubbed... From: Elliot Williams <ewilliams at ucsd.edu> Subject: [R] Generalized Error Distribution (Exponential Power) CDF?

Hi R-users,   I have this code below and I understand the error message but do not know how to correct it.  My question is how do I get rid of “with absolute error < 7.5e-06” attach to value of cdf so that I can carry out the calculation.   integrand <- function(z) { alp  <- 2.0165   rho  <- 0.868   # simplified expressions   a      <- alp-0.5   c1     <-

Hi all, is there any package in R capable of smooth approximation of CDF basing on given sample? (Thus, I am not speaking about ecdf) In particular, I expect very much that the approximation should subject to the property: f(x0)<=f(x1) for x0<x1, where x0 and x1 belong to range of the sample given. Polynomial approximation could be OK for me as well. P.S.