What is the basic difference between rep() and replicate in R?

  • Thread starter Thread starter user366312
  • Start date Start date
  • Tags Tags
    Difference
Click For Summary
SUMMARY

The primary difference between the R functions rep() and replicate() lies in their evaluation of expressions. The rep() function replicates a single value produced by the random() function multiple times, while replicate() evaluates the random() function multiple times to generate a vector of random values. This distinction is crucial for users looking to understand how to effectively utilize these functions in R programming. For detailed information, refer to the R manual available at this link.

PREREQUISITES
  • Basic understanding of R programming
  • Familiarity with functions and their arguments in R
  • Knowledge of random number generation in R
  • Access to R documentation for reference
NEXT STEPS
  • Explore the sample() function in R for random number generation
  • Learn about the differences between apply() and replicate() in R
  • Investigate the use of rep() with different data types
  • Read the R manual section on function evaluation for deeper insights
USEFUL FOR

This discussion is beneficial for R programmers, data analysts, and statisticians who are looking to enhance their understanding of function behavior in R, particularly in relation to random number generation and data replication techniques.

user366312
Gold Member
Messages
88
Reaction score
3
TL;DR
What is the basic difference between `rep()` and `replicate()` in R?
[CODE title="R code"] random <- function()
{
sample(1:10, size=1)
}

> rep(random(), 4)
[1] 8 8 8 8

> rep(random(), 4)
[1] 2 2 2 2

> replicate(4, random())
[1] 3 6 10 3[/CODE]

Why is this difference?
 
Technology news on Phys.org
First, a word of caution: I have never coded in R. That said:

See https://www.quora.com/Why-and-when-do-we-use-a-replicate-function-in-R

In your first case, "random()" is evaluated to produce a random number that is replicated 4 times. The result from random() is passed to "rep" as a single value.
In the second case, "random()" is evaluated 4 times to produce 4 random numbers. The expression "random()" is passed to replicate so that it can be used as many times as needed.

"replicate" takes an "expression" as an argument - so that it can evaluate it multiple times.
"rep" takes a vector.

Each of these functions has its own variations.
They are detailed in the full manual: https://cran.r-project.org/doc/manuals/r-release/fullrefman.pdf
 
Last edited:
We have many threads on AI, which are mostly AI/LLM, e.g,. ChatGPT, Claude, etc. It is important to draw a distinction between AI/LLM and AI/ML/DL, where ML - Machine Learning and DL = Deep Learning. AI is a broad technology; the AI/ML/DL is being developed to handle large data sets, and even seemingly disparate datasets to rapidly evaluated the data and determine the quantitative relationships in order to understand what those relationships (about the variaboles) mean. At the Harvard &...

Similar threads

  • · Replies 1 ·
Replies
1
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 3 ·
Replies
3
Views
1K
Replies
1
Views
1K
  • · Replies 17 ·
Replies
17
Views
2K
Replies
3
Views
2K
Replies
3
Views
2K
Replies
6
Views
2K
  • · Replies 9 ·
Replies
9
Views
2K
  • · Replies 27 ·
Replies
27
Views
4K