Z.pred <- matrix(predict(fit, newdata = xy), Y.pred <- seq(min(y), max(y), length.out = grid.lines) X.pred <- seq(min(x), max(x), length.out = grid.lines) # Compute the linear regression (z = ax + by + d) Use the argument surf in scatter3D() function to add a regression surface.Use the function lm() to compute a linear regression model: ax + by + cz + d = 0.The mtcars data will be used: data(mtcars) This is described at the end of the present article. The package plot3Drgl allows to plot easily the graph generated with plot3D in openGL, as made available by package rgl. This “4D” plot (x, y, z, color) with a color legend is not (easily) possible using the packages mentioned above (scatterplot3d, scatter3d, rgl). In addition to the x, y (and z) values, an additional data dimension can be represented by a color variable (argument colvar). Plot3D, from Karline Soetaert, is an R package containing many functions for 2D and 3D plotting: scatter3D, points3D, lines3D, text3D, ribbon3d, hist3D, etc. To close the discussion about 3D, in this tutorial I’ll describe the impressive plot3D package and its extension plot3Drgl package. In my previous articles, I already described how to make 3D graphs in R using the package below: 3D fancy Scatter plot with small dots on basal plane.Add points and text to an existing plot.Change the type of the box around the plot.Functions for scatter plots and texts in 2D and 3D.
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