quadDeriv {logcondens} | R Documentation |
Computes gradient and diagonal of the Hesse matrix w.r.t. to eta of a quadratic approximation to the reparametrized original log-likelihood function
L(varphi) = sum_{i=1}^m w_i varphi(x_i) - int_{-infty}^{infty} exp(varphi(t)) dt.
where L is parametrized via
{eta}({varphi}) = Bigl(varphi_1, Bigl(eta_1+ sum_{j=2}^i (x_i-x_{i-1})eta_iBigr)_{i=2}^mBigr).
{varphi}: vector (varphi(x_i))_{i=1}^m representing concave, piecewise linear function varphi,
{eta}: vector representing successive slopes of varphi.
quadDeriv(dx, w, eta)
dx |
Vector (0, x_i-x_{i-1})_{i=2}^m. |
w |
Vector of weights as in activeSetLogCon . |
eta |
Vector {eta}. |
m times 2 matrix. First column contains gradient and second column diagonal of Hesse matrix.
Kaspar Rufibach, kaspar.rufibach@gmail.com
Lutz Duembgen, duembgen@stat.unibe.ch,
http://www.staff.unibe.ch/duembgen
quadDeriv
is used by the function icmaLogCon
.