[Gretl-users] Functionality of functions meanc() - meanr()

Gretl 2020d, Windows 64-bit. I give the command matrix meancolumnsB  = meanc(B) The matrix "meancolumnsB " is generated as a single-row matrix as expected, but with "nan" in all its cells. I can see the matrix B  ok, it is a 10000 X 9 matrix, I can copy-paste it, export it in spreadsheet etc. What I observe is that there are 6  rows in the "B" matrix with "nan" values. So it appears that the meanc() function , in contrast to the mean() function, cannot skip missing values? If this is the case can we do something about it? The matrix B collects results from MLE simulations, and there are various instances where we are bound to get a "nan" value (the MLE did not converge, or the B may collect the elements of the Hessian but the Hessian is not computable and the algorithm drops back to OPG, etc) Note: I also run matrix meanrowsB  = meanr(B) Here, the result came out ok, with a "nan" result for the 6 rows of "B" that were filled with "nan" originally. But what would happen if in some row I would have some numbers and some "nan"? Will the meanr() return then a "nan" result? -- Alecos Papadopoulos PhD Athens University of Economics and Business web: alecospapadopoulos.wordpress.com/ skype:alecos.papadopoulos