# numericDeriv

##### Evaluate Derivatives Numerically

`numericDeriv`

numerically evaluates the gradient of an expression.

- Keywords
- models

##### 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`

.

##### Examples

`library(stats)`

```
<testonly>od <- options(digits = 4)</testonly>
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)
<testonly>options(od)</testonly>
```

*Documentation reproduced from package stats, version 3.3, License: Part of R 3.3*

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