SDE example 9 questions

Dear Colleagues, I am having a few problems expanding upon example 9 in Nonmem 7.2. This is the one with the SDE plug-in. I have a model with 3 differential equations and two observation compartments. One of the differential equations is the parameter that I want the process noise on. The SDEs look like this: kmet = exp(A(3)) dAdt(1) = kin - kmet*A(1) dAdt(2) = kmet*A(1) - kel*A(2) dAdt(3) = 0 + SGW3 * dW ; Observations are: F(1) = A(1)/V F(2) = A(2)/V Can someone please provide advice on how to code this model with the SDE plug-in? Here are the points as I understand them: · I have 3 "base ODE equations" which should be DADT(1,2,3). · I have 2 "prediction equations" which should be DADT(4,5). o e.g., DADT(4) = A(1)/V o the actual derivatives (dF_i / dA_j) required by the EKF will be computed from these equations entered in the ODEs, or so promises the commentary in the example · I need to have 9 additional compartments to house the state correlation matrix o Or is it only 6, the upper triangle? o What happens if I have too many? The integrator just runs more slowly? o I don't need to code anything for these, the plug-in will do all the work. · I have 3 "SGW" parameters that get stored in a local array and sent into the filtering code. One for each state. o Can I set the first two to zero, so I only have SGW3 as a THETA parameter? o Shouldn't there be 9 of these? Or does this mechanism only handle a diagonal scale matrix for the independent Wiener processes? · I need to pass the number of ODEs and Observations into SDE_DER o After reviewing the FORTRAN code, it looks like the order of the parameters is reversed from that in the comments. CALL SDE_DER(DADT,A,DA,IR,SGW, NDES, NOBS) § NDES=3, NOBS=2 § DADT, A, and DA are reserved variables (derivatives, state variables, and system jacobian). § What is IR? · I'm unsure how the $ERROR block is working (Y = IPRED+W*EPS(1) + WS*EPS(2)): o Is WS a system variable? If not, how does the SDE_CADD routine update it as promised in the commentary. o How does EPS(2) enter the fray? o Does it matter which EPS is assigned as the process noise term? Must it be the final one, or always the second one? Can there be more than 2 EPS in the model? o Is this a red herring since the R matrix is what really matters for the likelihood computation and that is being constructed by SDE_CADD? Thanks in advance for any assistance you can render. Jason Chittenden Scientist Certara(tm) Implementing Translational Science 5625 Dillard Drive, Suite 205, Cary NC 27518 Certara: The name behind the names you know Tripos - Simcyp - Pharsight http://www.certara.com/