similar to: Using 'polygon' in a 3d plot

Hi R Users, How to use the function polygon() together with the package scatterplot3d? I am trying to color below of the curves defined for the function density(). I tried to use the site: R GRAPH GALLERY as tutorial. I tried to adapt the example of this page: [figure]: http://addictedtor.free.fr/graphiques/RGraphGallery.php?graph=30 [code]:

Hi everyone, ? I am trying to get a point of intersection between a polyline and a straight line ?.. and get the x and y coordinates of this point. For exemplification consider this: ? ? set.seed(123) ? k1 <-rnorm(100, mean=1.77, sd=3.33) ?k1 <- sort(k1) q1 <- rnorm(100, mean=2.37, sd=0.74) q1 <- sort(q1, decreasing = TRUE) plot(k1, q1, xlim <- c((min(k1)-5),

The control flow was: if (!y) { ppix = ... } if (y) { ... } else if (x) { use ppix for something } else { use ppix for something } Merge the if(!y) block with the two else branches. This avoids a false-positive in the clang static analyzer, it can't know that !y and x are mutually exclusive. The result looks something like this: if (y) { ... } else { ppix = ... if (x) {

Does anyone have any experience plotting complex polygons on a scatterplot3d display? I would like to present some spatially binned data in a 3-d type plot with background polygons (i.e.. a filled coastline map). I can get the coastline onto the plot window as a line type but cannot figure out how to fill the shape. I'm certain it may be possible but might require a bit of digging

Hello all, I am wondering if there is a way to do a spatial error probit/logit model in R? I can't seem to find it in any of the packages. I can do it in MATLAB with Gibbs sampling, but would like to confirm the results. Ideally I would like to use this model to predict probability of parcel conversion in a future time period. This seems especially difficult in a binary outcome model

On 21/10/2020 8:45 a.m., Balint Radics wrote: > Hello, > > Could someone suggest a package/way to make a 3D raster plot of the Earth > (with continent boundaries), and then make a "cut" or "slice" of it such > that one can also visualize some scalar quantity as a function of the > Radius/Depth across that given slice ? > > Formally, I would have a

Hi, My english isn't brilliant and my problem is very difficult to describe but I try ;) My first question is: May I write loop "for" like this or similar - for (i in sth : sth[length(sth)], k in sth_else : length(sth_else) ) - I'd like to have two independent conditions in the same loop "for". My secound question depend on program below. I'd like to write every

Hi all, I have been previously been using scatterplot3d package to create some graphs but unfortunately it does not allow me to rotate the plot on all three axis. The cloud() function in the lattice package does allow me to do so. When I was using scatterplot3d I was using a script (Shown Below) to calculate the mean, quartiles and range limits for all three axis and I was representing that on the

Dear R-helpers, an rgl-ers in particular, what is the easiest way to plot a section of a plane in 3D, that is given by the xyz coordinates of the outline? Suppose I have a polygon - which I know for sure is a set of coordinates on the same plane. One method I found is to use surf.tri from the geometry package, and then plot the triangles with rgl.triangles. This method is not perfect though,

Hi R Users, I have produced a simulated scatter plot of y versus x tightly clustered around the 45 degree line through the origin with the following code: x <- seq(1,100) y <- x+rnorm(100,0,10) plot(x,y,col="blue") abline(0,1) Is there some way to generate a 3-dimensional analogue of this? Can I get a similar simulated scatter plot of points in 3 dimensions where the points

is there no package/function in R to calculate the conditional power or the bayesian predictive power for trials with binary endpoints? Thanks -- View this message in context: http://www.nabble.com/Conditional-power%2C-predictive-power-tf3603396.html#a10066991 Sent from the R help mailing list archive at Nabble.com.

Indeed: Using 'weights' is not meant to indicate that the same observation is repeated 'n' times. As I showed, this gives erroneous results. Hence I suggested that it is discouraged rather than encouraged in the Details section of lm in the Reference manual. Arie ---Original Message----- On Sat, 7 Oct 2017, wolfgang.viechtbauer at maastrichtuniversity.nl wrote: Using

Hello, Could someone suggest a package/way to make a 3D raster plot of the Earth (with continent boundaries), and then make a "cut" or "slice" of it such that one can also visualize some scalar quantity as a function of the Radius/Depth across that given slice ? Formally, I would have a given, fixed longitude, and a list of vectors {latitude, radius, Value} that would show

In the Details section of lm (linear models) in the Reference manual, it is suggested to use the weights= option for summarized data. This must be discouraged rather than encouraged. The motivation for this is as follows. With summarized data the standard errors get smaller with increasing numbers of observations. However, the standard errors in lm do not get smaller when for instance all weights

Han-Lin I don't think I have seen a reply so I will suggest that maybe you could try a different approach than what you are thinking about doing. I believe the current best practice is to use the weights as a covariate in a regression model - and bytheway - the weights are the inverse of the probabilities of selection - not the probabilities. Fundamentally, there is a difficulty in making

Hi all In two days, I am giving a small, informal workshop in our Department about using R. Initially, it was just for statistician, but surprisingly (to me anyhow) many mathematicians are also coming who have a MATLAB background. They are coming at the Workshop from a teaching perspective. They are considering using R to avoid licensing issues with MATLAB. One thing they were hoping me to

Yes. Thank you; I should have quoted it. I suggest to remove this text or to add the word "not" at the beginning. Arie On Sun, Oct 8, 2017 at 4:38 PM, Viechtbauer Wolfgang (SP) <wolfgang.viechtbauer at maastrichtuniversity.nl> wrote: > Ah, I think you are referring to this part from ?lm: > > "(including the case that there are w_i observations equal to y_i and

Seriously, if a method gives a wrong result, it's wrong. line() does NOT implement the algorithm of Tukey, even not after the patch. We're not discussing Excel here, are we? The method of Tukey is rather clear, and it is NOT using the default quantile definition from the quantile function. Actually, it doesn't even use quantiles to define the groups. It just says that the groups

Dear R-List, I've written some code to put measurement values at a position x and y in bins (xb and yb). It works, but I wonder if there isn't a function that would do what I do by hand in "# fill data in bins"? Here is the code: # data x <- c( 1.1, 1.5, 2.3, 2.5, 2.6, 2.9, 3.3, 3.5 ) y <- c( 6.3, 6.2, 5.9, 5.3, 5.4, 4.2, 4.8, 4.6 ) val <- c( 50, 58, 32, 14, 12,

OK. We have now three suggestions to repair the text: - remove the text - add "not" at the beginning of the text - add at the end of the text a warning; something like: "Note that in this case the standard estimates of the parameters are in general not correct, and hence also the t values and the p value. Also the number of degrees of freedom is not correct. (The parameter