R: Evaluate Derivatives Numerically

numericDeriv {stats} | R Documentation

## Evaluate Derivatives Numerically

### Description

`numericDeriv` numerically evaluates the gradient of an expression.

### Usage

    numericDeriv(expr, theta, rho = parent.frame(), dir = 1.0)

### Arguments

`expr` | The expression to be differentiated. The value of this expression should be a numeric vector.
`theta` | A character vector of names of numeric variables used in `expr`.
`rho` | An environment containing all the variables needed to evaluate `expr`.
`dir` | A numeric vector of directions to use for the finite differences.

### Details

This is a front end to the C function `numeric_deriv`, which is described in Writing R Extensions.

The numeric variables must be of type `real` and not `integer`.

### Value

The value of `eval(expr, envir = rho)` plus a matrix attribute called `gradient`. The columns of this matrix are the derivatives of the value with respect to the variables listed in `theta`.

### Author(s)

Saikat DebRoy saikat@stat.wisc.edu

### Examples

    myenv <- new.env()
    assign("mean", 0., envir = myenv)
    assign("sd", 1., envir = myenv)
    assign("x", seq(-3., 3., len = 31), envir = myenv)
    numericDeriv(quote(pnorm(x, mean, sd)), c("mean", "sd"), myenv)

[Package stats version 3.1.2 Index]