# 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)`

```
# NOT RUN {
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)
# }
```

*Documentation reproduced from package stats, version 3.5.0, License: Part of R 3.5.0*

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