An objective function combines the sum of squared error of basis expansion estimates and the penalty controls how those estimates fail to satisfies the ODE model
innerobj_multi(basis_coef, ode.par, input, derive.model,NLS)Basis coefficients for interpolating observations given a basis object.
Structural parameters of the ODE model.
Contains dependencies for the optimization, including observations, penalty parameter lambda, and etc..
The function defines the ODE model and is the same as the ode.model in pcode.
Default is TRUE so the function returns vector of residuals, and otherwise returns sum of squared errors.
Vector of residuals and evaluation of penalty function on quadrature points for approximating the integral.