Create an Expression in R Programming - expression() Function

Compute Derivative of an Expression in R Programming – deriv() and D() Function

Last Updated : 30 Jun, 2020

In R programming, derivative of a function can be computed using deriv() and D() function. It is used to compute derivatives of simple expressions.

Syntax:
deriv(expr, name)
D(expr, name)

Parameters:
expr: represents an expression or a formula with no LHS
name: represents character vector to which derivatives will be computed

Example 1:

# Expression or formula 
f = expression(x^2 + 5*x + 1) 
  
# Derivative 
cat("Using deriv() function:\n") 
print(deriv(f, "x")) 
  
cat("\nUsing D() function:\n") 
print(D(f, 'x')) 

Output:

Using deriv() function:
expression({
    .value <- x^2 + 5 * x + 1
    .grad <- array(0, c(length(.value), 1L), list(NULL, c("x")))
    .grad[, "x"] <- 2 * x + 5
    attr(.value, "gradient") <- .grad
    .value
})

Using D() function:
2 * x + 5

Example 2:

# Little harder derivative 
  
# Using deriv() Function 
cat("Using deriv() function:\n") 
print(deriv(quote(sinpi(x^2)), "x")) 
  
# Using D() Function 
cat("\nUsing D() function:\n") 
print(D(quote(sinpi(x^2)), "x")) 

Output:

Using deriv() function:
expression({
    .expr1 <- x^2
    .value <- sinpi(.expr1)
    .grad <- array(0, c(length(.value), 1L), list(NULL, c("x")))
    .grad[, "x"] <- cospi(.expr1) * (pi * (2 * x))
    attr(.value, "gradient") <- .grad
    .value
})

Using D() function:
cospi(x^2) * (pi * (2 * x))

Create an Expression in R Programming - expression() Function

utkarsh_kumar

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