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

Last Updated : 15 Jul, 2025
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: r
# 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: withoutJitterwithJitterExample 2: With large factor value r
# 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: withoutJitterFactorwithJitterFactor
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