[Gretl-users] State space model with missing observations

Hi community! I'm trying to compute a time-varying state space model to calculate stocks' betas. Unfortunately, I have some missing observations and, when this is the case, the model implemented by Gretl suddenly stops and doesn't compute anything (as expected). My question is simple: Is there a way of instructing Gretl to ignore missing values and compute the state spacel model? Here is the example code taken from chapter 35 of Gretl manual. Please note that I added line 6 "INFQ[20] = NA" in order to have a missing data point in the data. <hansl> function void at_each_step(bundle *b) b.obsymat = transp(b.mX[b.t,]) end function open AWM.gdt --quiet smpl 1974:1 1994:1 INFQ[20] = NA # added this line to have a missing value /* parameter initialization */ scalar b0 = mean(INFQ) scalar s_obs = 0.1 scalar s_state = 0.1 /* bundle setup */ bundle B = ksetup(INFQ, 1, 1, 1) matrix B.mX = {URX} matrix B.depvar = {INFQ} B.timevar_call = "at_each_step" B.diffuse = 1 /* ML estimation of intercept and the two variances */ mle LL = err ? NA : B.llt B.obsy = B.depvar - b0 B.obsvar = s_obs^2 B.statevar = s_state^2 err = kfilter(&B) params b0 s_obs s_state end mle /* display the smoothed time-varying slope */ ksmooth(&B) series tvar_b1hat = B.state[,1] series tvar_b1se = sqrt(B.stvar[,1]) gnuplot tvar_b1hat --time-series --with-lines --output=display \ --band=tvar_b1hat,tvar_b1se,1.96 --band-style=fill </hansl> Best, Filipe