::Free Statistics and Forecasting Software::

All rights reserved. The non-commercial (academic) use of this software is free of charge. The only thing that is asked in return is to cite this software when results are used in publications.

This free online software (calculator) computes the following charts for a trivariate dataset: 3-dimensional scatterplots, all combinations of 2-by-2 scatterplots, histograms, bivariate density plots with the corresponding contour plots and regression line.

This software enables the user to visually explore the relationship between 3 variables. In addition it illustrates how 3-dimensional scatterplots are related to 2-dimensional scatterplot matrices and density plots.

To make this more useful, the last plot uses Variables X and Y as coordinates and displays the interpolated Z values as a contour plot.

Enter (or paste) your data delimited by hard returns.

---

Source code of R module

x <- array(x,dim=c(length(x),1)) colnames(x) <- par5 y <- array(y,dim=c(length(y),1)) colnames(y) <- par6 z <- array(z,dim=c(length(z),1)) colnames(z) <- par7 d <- data.frame(cbind(z,y,x)) colnames(d) <- list(par7,par6,par5) par1 <- as.numeric(par1) par2 <- as.numeric(par2) if (par1>500) par1 <- 500 if (par2>500) par2 <- 500 if (par1<10) par1 <- 10 if (par2<10) par2 <- 10 library(GenKern) library(lattice) panel.hist <- function(x, ...) { usr <- par("usr"); on.exit(par(usr)) par(usr = c(usr[1:2], 0, 1.5) ) h <- hist(x, plot = FALSE) breaks <- h$breaks; nB <- length(breaks) y <- h$counts; y <- y/max(y) rect(breaks[-nB], 0, breaks[-1], y, col="black", ...) } bitmap(file="cloud1.png") cloud(z~x*y, screen = list(x=-45, y=45, z=35),xlab=par5,ylab=par6,zlab=par7) dev.off() bitmap(file="cloud2.png") cloud(z~x*y, screen = list(x=35, y=45, z=25),xlab=par5,ylab=par6,zlab=par7) dev.off() bitmap(file="cloud3.png") cloud(z~x*y, screen = list(x=35, y=-25, z=90),xlab=par5,ylab=par6,zlab=par7) dev.off() bitmap(file="pairs.png") pairs(d,diag.panel=panel.hist) dev.off() x <- as.vector(x) y <- as.vector(y) z <- as.vector(z) bitmap(file="bidensity1.png") op <- KernSur(x,y, xgridsize=par1, ygridsize=par2, correlation=cor(x,y), xbandwidth=dpik(x), ybandwidth=dpik(y)) image(op$xords, op$yords, op$zden, col=terrain.colors(100), axes=TRUE,main="Bivariate Kernel Density Plot (x,y)",xlab=par5,ylab=par6) if (par3=="Y") contour(op$xords, op$yords, op$zden, add=TRUE) if (par4=="Y") points(x,y) (r<-lm(y ~ x)) abline(r) box() dev.off() bitmap(file="bidensity2.png") op <- KernSur(y,z, xgridsize=par1, ygridsize=par2, correlation=cor(y,z), xbandwidth=dpik(y), ybandwidth=dpik(z)) print(op) image(op$xords, op$yords, op$zden, col=terrain.colors(100), axes=TRUE,main="Bivariate Kernel Density Plot (y,z)",xlab=par6,ylab=par7) if (par3=="Y") contour(op$xords, op$yords, op$zden, add=TRUE) if (par4=="Y") points(y,z) (r<-lm(z ~ y)) abline(r) box() dev.off() bitmap(file="bidensity3.png") op <- KernSur(x,z, xgridsize=par1, ygridsize=par2, correlation=cor(x,z), xbandwidth=dpik(x), ybandwidth=dpik(z)) print(op) image(op$xords, op$yords, op$zden, col=terrain.colors(100), axes=TRUE,main="Bivariate Kernel Density Plot (x,z)",xlab=par5,ylab=par7) if (par3=="Y") contour(op$xords, op$yords, op$zden, add=TRUE) if (par4=="Y") points(x,z) (r<-lm(z ~ x)) abline(r) box() dev.off() data.loess <- loess(z ~ x * y) data.loess xgrid <- seq(min(x), max(x), (max(x) - min(x)) / par1) ygrid <- seq(min(y), max(y), (max(y) - min(y)) / par2) data.fit <- expand.grid(x = xgrid, y = ygrid) (mtrxz <- predict(data.loess, newdata = data.fit)) bitmap(file="interpol1.png") image(xgrid, ygrid, mtrxz, col=terrain.colors(100), axes=T, main="Interpolation of Variable Z", xlab="Variable X", ylab="Variable Y") contour(xgrid, ygrid, mtrxz, add=T) dev.off()

Cite this software as:

Wessa P., (2020), 3-Dimensional Scatterplots (v1.0.8) in Free Statistics Software (v1.2.1), Office for Research Development and Education, URL https://www.wessa.net/rwasp_cloud.wasp/

The R code is based on :

Deepayan Sarkar (2006)., lattice: Lattice Graphics. R package, version 0.13-8.

David Lucy and Robert Aykroyd (2004)., GenKern: Functions for generating and manipulating kernel density estimates., R package version 1.1-0.

To cite Wessa.net in publications use:
Wessa, P. (2024), Free Statistics Software, Office for Research Development and Education,
version 1.2.1, URL https://www.wessa.net/

© All rights reserved. Academic license for non-commercial use only.
The free use of the scientific content, services, and applications in this website is granted for non commercial use only. In any case, the source (url) should always be clearly displayed. Under no circumstances are you allowed to reproduce, copy or redistribute the design, layout, or any content of this website (for commercial use) including any materials contained herein without the express written permission.

Information provided on this web site is provided "AS IS" without warranty of any kind, either express or implied, including, without limitation, warranties of merchantability, fitness for a particular purpose, and noninfringement. We use reasonable efforts to include accurate and timely information and periodically update the information, and software without notice. We make no warranties or representations as to the accuracy or completeness of such information (or software), and it assumes no liability or responsibility for errors or omissions in the content of this web site, or any software bugs in online applications. Your use of this web site is AT YOUR OWN RISK. Under no circumstances and under no legal theory shall we be liable to you or any other person for any direct, indirect, special, incidental, exemplary, or consequential damages arising from your access to, or use of, this web site.

Software Version : 1.2.1
Algorithms & Software : Patrick Wessa, PhD
Server : www.wessa.net

About | Comments, Feedback & Errors | Privacy Policy | Statistics Resources | Wessa.net Home