jacobian( f, var, params = list(), coordinates ="cartesian", accuracy =4, stepsize =NULL)f %jacobian% var
Arguments
f: array of characters or a function returning a numeric array.
var: vector giving the variable names with respect to which the derivatives are to be computed and/or the point where the derivatives are to be evaluated. See derivative.
params: list of additional parameters passed to f.
coordinates: coordinate system to use. One of: cartesian, polar, spherical, cylindrical, parabolic, parabolic-cylindrical or a vector of scale factors for each varibale.
accuracy: degree of accuracy for numerical derivatives.
stepsize: finite differences stepsize for numerical derivatives. It is based on the precision of the machine by default.
Returns
array.
Details
The function is basically a wrapper for gradient with drop=FALSE.
Functions
f %jacobian% var: binary operator with default parameters.
Examples
### symbolic Jacobian jacobian("x*y*z", var = c("x","y","z"))### numerical Jacobian in (x=1, y=2, z=3)f <-function(x, y, z) x*y*z
jacobian(f = f, var = c(x=1, y=2, z=3))### vectorized interfacef <-function(x) x[1]*x[2]*x[3]jacobian(f = f, var = c(1,2,3))### symbolic vector-valued functionsf <- c("y*sin(x)","x*cos(y)")jacobian(f = f, var = c("x","y"))### numerical vector-valued functionsf <-function(x) c(sum(x), prod(x))jacobian(f = f, var = c(0,0,0))### binary operator"x*y^2"%jacobian% c(x=1, y=3)
References
Guidotti E (2022). "calculus: High-Dimensional Numerical and Symbolic Calculus in R." Journal of Statistical Software, 104(5), 1-37. tools:::Rd_expr_doi("10.18637/jss.v104.i05")
See Also
Other differential operators: curl(), derivative(), divergence(), gradient(), hessian(), laplacian()