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How to Visualize Regression Plane in R?
Description

To visualize the regression plane using R programming.

Process

   R Function :lm()

   To compute a linear regression model:ax + by + cz + d = 0

   Argument surf To add a regression surface.

  Surfis a list specifying a (fitted)surface to be added on the scatter plot.

   The list should include at least x,y, z, defining the surface.

Sapmle Code

#Regression Plane

 

#Input

#x, y, z variables

x<-mtcars$wt

y<-mtcars$disp

z<-mtcars$mpg

 

# Compute the linear regression (z = ax + by + d)

fit<-lm(z ~ x + y)

 

#Predict values on regular xy grid

grid.lines<-25

x.pred<-seq(min(x), max(x), length.out = grid.lines)

y.pred<-seq(min(y), max(y), length.out = grid.lines)

xy<-expand.grid( x = x.pred, y = y.pred)

z.pred<-matrix(predict(fit, newdata = xy), nrow = grid.lines, ncol = grid.lines)

 

#Fitted points for droplines to surface

fitpoints<-predict(fit)

 

#Scatter plot with regression plane

scatter3D(x, y, z, pch = 18, cex = 2,

theta = 20, phi = 20, ticktype = “detailed”,

xlab = “wt”, ylab = “disp”, zlab = “mpg”,

surf = list(x = x.pred, y = y.pred, z = z.pred,

facets=NA,fit = fitpoints), main = “mtcars”)

Screenshots