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Adding Noise to a Numeric Vector in R Programming – jitter() Function

  • Last Updated : 19 Jun, 2020

In R programming, jittering means adding small amount of random noise to a numeric vector object. In this article, we’ll learn to use jitter() function and create a plot to visualize them.

Syntax: jitter(x, factor)

Parameters:
x: represents numeric vector
factor: represents numeric value for factor specification

Example 1:




# Define numeric vectors
x <- round(runif(1000, 1, 10))
y <- x + rnorm(1000, mean = 0, sd = 5)
  
# output to be present as PNG file 
png(file="withoutJitter.png")
  
# Plotting without jitter function
plot(x, y, xlim = c(0, 11),
     main = "Without Jitter Function")
  
# saving the file 
dev.off()
  
x_j <- jitter(x)
  
# output to be present as PNG file 
png(file="withJitter.png")
  
# Plotting with jitter function
plot(x_j, y, xlim = c(0, 11),
     main = "With Jitter Function")
  
# saving the file 
dev.off()

Output:
withoutJitter



withJitter

Example 2: With large factor value




# Define numeric vectors
x <- round(runif(1000, 1, 10))
y <- x + rnorm(1000, mean = 0, sd = 5)
  
# output to be present as PNG file 
png(file="withoutJitterFactor.png")
  
# Plotting without jitter function
plot(x, y, xlim = c(0, 11),
     main = "Without Jitter Function")
  
# saving the file 
dev.off()
  
x_j <- jitter(x, factor = 2)
  
# output to be present as PNG file 
png(file="withJitterFactor.png")
  
# Plotting with jitter function
plot(x_j, y, xlim = c(0, 11),
     main = "With Jitter Function and Large Factor")
  
# saving the file 
dev.off()

Output:
withoutJitterFactor

withJitterFactor




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