similar to: p-value calculation on a joint distribution

Dear R family, I want to calculate the joint probability (distribution) of two random continuous variables X and Y. Could to please tell me how to do it?Thanks in advance.. elisa [[alternative HTML version deleted]]

Dear all, Given rr<-data.frame(r1<-rnorm(1000,10,5),r2<-rnorm(1000,220,5)) How can I add a column (rr$p) for the joint probability of each r1 & r2 pair? I know how to add the column.. I just dont know how to compute the p value for joint probabilities given the two samples. //M

X and Y are independently distributed random variables. I would like to study the contours of the joint density of these two variables. Any function to call? Thank you very much! -- View this message in context: http://www.nabble.com/How-to-plot-contours-for-joint-density-of-2-independently-distributed-r.v.--tp19493126p19493126.html Sent from the R help mailing list archive at Nabble.com.

Hi all, I'm fairly new to R, so I'm still trying to feel out what is available to me. I would like to be able to plot joint density in a two dimensional plot where density is indicated by color or darkness gradients, like a 2d color coded topographic map. Ideally, the output would be something I could then plot other points or lines on. Currently, I'm calculating joint density with

Hello, I want to compute the P-value from the joint cumulative distribution of an n-dimensional order statistic in R, using the formula found on http://cmgm.stanford.edu/%7Ekimlab/multiplespecies/Supplement/methods_network.html My data consists of three different techniques (G2D, POCUS and RANDOM), and each has associated with it a number of rankings (integer between 0 and 1000), like for

Suppose I make two discrete variables -- > D <- data.frame(f1=sample(1:5,100,replace=T), f2=sample(1:5,100,replace=T)) I know I can do: > table(D$f1, D$f2) 0 1 2 3 4 0 5 5 5 5 4 1 4 2 6 7 3 2 5 3 5 3 6 3 3 1 3 1 2 4 6 4 3 3 6 > table(D$f1) 0 1 2 3 4 24 22 22 10 22 > table(D$f2) 0 1 2 3 4 23 15 22 19 21 which is all great. But how do I produce the

Dear all, Please, look at the following code: attach(geyser) f1 <- kde2d(duration, waiting, n = 5) a <- 0 for (i in 1:5){ for (j in 1:5){ a <- a + f1$z[i,j] } } As far as I understood from Help kde2d returns matrix elements of which are values of joint probability mass function Pr(X=x,Y=y) therefore, sum of its elements should sum to 1. Which is not the case from my check. Where is

Hi, I conduct a panel data estimation and obtain estimators for two of the coefficients beta1 and beta2. R tells me the mean and covariance of the distribution of (beta1, beta2). Now I would like to find the distribution of the quotient beta1/beta2, and one way to do it is to simulate via the joint distribution (beta1, beta2), where both beta1 and beta2 follow t distribution. How could we

I am trying to return the p value for a stat from the ECDF. That is the index of the first occurrence, on an ordered vector, of a value either greater than or equal to a given value. Ideally I would not have to order the vector beforehand. Currently I use: PValue<-function(stat, ECDF){ ###Get the length of the ECFD L<-length(ECDF) ###Loop through the ECDF until the p value is

Hi, all ecdf function (Empirical Cumulative Distribution Function) in "stats" package counts from smaller values to larger values. However, I want to draw it by counting from larger value to smaller values and I couldn't find options for this purpose. How can I draw ecdf or ecdf like graph by counting from larger values to smaller values. Thank you in advance. Hyunchul Kim

Hi, i want to plot empirical cumulative density functions for two variables in one plot. For better visualizing the differences in the two cumulative curves I'd like to log-scale the axis. So far I found 3 possible functions to plot ecdf: 1) ecdf() from the package 'stats'. I don't know how to successfully set the log.scales? Combining two plots is not a problem: plot(ecdf(x1))

Dear all, How can I get the duplicated elements from a vector? For example, x <- c("yes", "no", "yes", "yes", "no", "not sure"), how can I filter out all the elements which occured >=2 times? Thanks for any help! Regards, Leon

Hi, from what you're writing: "The logaritmic transformation "shapiro.test(log10(y))" says: W=0.9773, p-value= 2.512e-05." it seems the log-values are not distributed normally and so original data are not distributed like a log-normal: the p-value is extremally small! Other tests for normality are available in package: nortest compare the log-transformation of your ecdf

Hi, I'm bit confused about ecdf (read the help files but still not sure about this). I have an analytical expression for the pdf, but want to get the empirical cdf. How do I use this analytical expression with ecdf? If this helps make it concrete, the pdf is: f(u) = \sum_{t = 1}^T 1/n_t \sum_{i = 1}^{n_t} 1/w K((u - u_{it})/w) where K = kernel density estimator, w = weights, and u_{it} =

Dear list, I have got an array with observational values t and I would like to fit a geometric distribution to it. As I understand the geometric distribution, there is only one parameter, the probability p. I estimated it by 1/mean(t). Now I plotted the estimated density function by plot(ecdf(t),do.points=FALSE,col.h="blue"); and I would like to add the geometric distribution. This

Dear all, I have a data frame with several columns, and I have the specified order of a given column. How can I re-order the rows of my data frame accroding to this specified order? for example, x = data.frame( num = 1:26, alpha = letters[1:26], stringsAsFactors=FALSE) z = sample(x$alpha, replace=FALSE) Can I re-order x accroding to z ? Thanks, Leon [[alternative HTML version

http://r.789695.n4.nabble.com/file/n3567636/ecdfs.jpg ecdfs.jpg http://r.789695.n4.nabble.com/file/n3567636/ecdf_curve.gif ecdf_curve.gif Hello, I have generated a plot of two empirical CDFs (attachment 1). As a result, they are stepwise when plotted. The following code was used: > plot(ecdf(mut), do.points=FALSE, verticals=TRUE, xlim=range(mut, non), > col="red") >

Hi, I've just read this on Vorbis Xtreme site: "11. YOU SAY THAT OGG VORBIS IS PATENT-FREE, BUT I SAW A PATENT NAMED 'JOINT-STEREO' ON FRAUNHOFER'S PATENT LIST? SO OGG VORBIS ACTUALLY ISN'T PATENT-FREE SINCE IT ALSO USES JOINT-STEREO? No. You can't judge on a patent just by looking at its name - what's 'inside' is what matters. So if the name of the

Hi, I am using ecdf-function and want to use the ecdf()-data-points for nls() as data-parameter. nls() expects 'list' or 'environment' as a data-type, knots(ecdf(mydata)) gives me 'numeric'. What should I do now? Thanks in advance - Jochen Here is the code: ################################################# # --- Fit --- # Gumbel-Dist-Function, cumulative,

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