Description Usage Arguments Value
Squared error (aka loss function) of x
with respect to data
,
as function of x
. Additional argument jacobian
is the Jacobian matrix of the (vector)
quantity of interest with respect to problem parameters. Such matrices are
computed by, e.g., solvers based on adjoint state method.
1 | squared_error(x, data, jacobian = NULL)
|
x |
numeric or complex vector, computed (simulated) data. |
data |
numeric or complex vector, observed data, must have the same
length as |
jacobian |
numeric or complex matrix, can be |
List with one or two components:
value
numeric scalar;
gradient
numeric vector with length equal to ncol(jacobian)
, missing
if jacobian
is NULL
.
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