Function to Calculate Mode in R

Sample Data Set (Vector)

vec <- c(1, 2, 3, 4, 5, 6, 7, 8, 9, 3)

print(vec)

##  [1] 1 2 3 4 5 6 7 8 9 3

Method 1 (Using library modeest)

library(modeest)

## 
## This is package 'modeest' written by P. PONCET.
## For a complete list of functions, use 'library(help = "modeest")' or 'help.start()'.

mlv(vec, method = "mfv")

## Mode (most likely value): 3 
## Bickel's modal skewness: 0.4 
## Call: mlv.default(x = vec, method = "mfv")

Method 2 (Function to find mode)

# Function to find mode
Find_Mode <- function(x) {
  unique_val <- unique(x) # Find unique values in the vector
  
  # Check to determine whether mode exist or not
  if (length(x)==length(unique_val)) {
    mode_x <- 'Mode does not exist'
    return(mode_x)
  } 
  
  # Create freq vector to keep track of number of occurences of a value
  freq <- rep(0, length(unique_val))
  
  # For loop to update the number of occurences
  for (i in 1:length(unique_val)) {
    for (j in 1:length(x)) {
      if (unique_val[i]==x[j]) {
        freq[i] = freq[i] + 1;
      }
    }
  }
  
  # Check to determine whether mode exist or not
  if (mean(freq)==max(freq)) {
    mode_x <- 'Mode does not exist'
    return(mode_x)
  }
  
  # Find and return the mode
  idx <- which.max(freq)
  mode_x <- unique_val[idx]
  return(mode_x)
}

# Find mode of vec
Find_Mode(vec)

## [1] 3

Method 3 (Alternative Function to find mode)

Find_Mode2 <- function(x) {
  ux <- unique(x)
  # Check to determine whether mode exist or not
  if (length(x)==length(ux)) {
    mode_x <- 'Mode does not exist'
    return(mode_x)
  }
  
  # Finding the number of occurences
  tab <- tabulate(match(x, ux))
  
  # Check to determine whether mode exist or not
  if (mean(tab)==max(tab)) {
    mode_x <- 'Mode does not exist'
    return(mode_x)
  }
  
  # Find and return the mode
  idx <- which.max(tab)
  mode_x <- ux[idx]
  return(mode_x)
}

Find_Mode2(vec)

## [1] 3