| e04vj {NAGFWrappers} | R Documentation |
e04vj may be used before e04vh to determine the sparsity pattern for the Jacobian.
e04vj(nf, usrfun, lena, leng, x, xlow, xupp,
n = nrow(x))
nf |
integer nf, the number of problem functions in F(x), including the objective function (if any) and the linear and nonlinear constraints. Simple upper and lower bounds on x can be defined using the arguments xlow and xupp and should not be included in F. |
usrfun |
function usrfun must define the problem functions F(x). This function is passed to e04vj as the external argument usrfun.
|
lena |
integer Lena should be an overestimate of the number of elements in the linear part of the Jacobian. |
leng |
integer Leng should be an overestimate of the number of elements in the nonlinear part of the Jacobian. |
x |
double array An initial estimate of the variables x. The contents of x will be used by e04vj in the call of usrfun, and so each element of x should be within the bounds given by xlow xupp. |
xlow |
double array |
xupp |
double array Contain the lower and upper bounds l_x and u_x on the variables x. |
n |
integer: default = nrow(x) n, the number of variables. |
R interface to the NAG Fortran routine E04VJF.
IAFUN |
integer array |
JAVAR |
integer array |
NEA |
integer Is the number of nonzero entries in A such that F(x) = f(x) + Ax. |
A |
double array Define the coordinates (ij) and values A_ij of the nonzero elements of the linear part A of the function F(x) = f(x) + Ax. |
IGFUN |
integer array |
JGVAR |
integer array Define the coordinates (ij) of the nonzero elements of G, the nonlinear part of the derivatives J(x) = G(x) + A of the function F(x) = f(x) + Ax. |
NEG |
integer The number of nonzero entries in G. |
IFAIL |
integer ifail =0unless the function detects an error or a warning has been flagged (see the Errors section in Fortran library documentation). |
NAG
http://www.nag.co.uk/numeric/FL/nagdoc_fl23/pdf/E04/e04vjf.pdf
optlist <- list()
ifail <- 0
usrfun = function(status, n, x, needf, nf, f, needg,
leng, g) {
f[1] <- 1000 %*% sin(-x[1] - 0.25) + 1000 %*% sin(-x[2] -
0.25) - x[3]
f[2] <- 1000 %*% sin(x[1] - 0.25) + 1000 %*% sin(x[1] - x[2] -
0.25) - x[4]
f[3] <- 1000 %*% sin(x[2] - x[1] - 0.25) + 1000 %*% sin(x[2] -
0.25)
f[4] <- -x[1] + x[2]
f[5] <- x[1] - x[2]
f[6] <- 1e-06 %*% x[3]^3 + 2e-06 %*% x[4]^3/3 + 3 %*% x[3] +
2 %*% x[4]
list(STATUS = as.integer(status), F = as.matrix(f), G = as.matrix(g))
}
nf <- 6
lena <- 300
leng <- 300
x <- matrix(c(0, 0, 0, 0), nrow = 4, ncol = 1, byrow = TRUE)
xlow <- matrix(c(-0.55, -0.55, 0, 0), nrow = 4, ncol = 1,
byrow = TRUE)
xupp <- matrix(c(0.55, 0.55, 1200, 1200), nrow = 4,
ncol = 1, byrow = TRUE)
e04vj(nf, usrfun, lena, leng, x, xlow, xupp)