***** To join INSNA, visit http://www.insna.org ***** Emiel, As far as I know, you cannot put NAs in the attribute files for MPNet (Peng or someone else from MelNet can correct me if I am wrong here). So to use your data in MPNet you might have to do some sort of imputation for missing data. Unfortunately, there is no ALAAM estimation software in R (that I know of) - specifically statnet does not have this functionality. However I have very recently written a Python implementation of ALAAM estimation (and simulation and goodness-of-fit), available from: https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_stivalaa_ALAAMEE&d=DwIFaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=XrwS5980_B0ppSPHcalrMQTUjBlb-DfyDd4-4FUg0v4&s=OHoz87LUU60YIHwGwy_yKnRVg7uQGQskSB983K1DsVY&e= This implementation allows NA values in the attribute files. Although it was mainly written to experiment with the equilibrium expectation (EE) algorithm (Byshkin et al. 2018) for ALAAM estimation, I also implemented the Robbins-Monro stochastic approximation algorithm (exactly as used in MPNet and the older IPNet program) for comparison. As the EE algorithm implementation for ALAAM is definitely to be considered experimental at this stage, you should probably use the stochastic approximation algorithm for now. Unlike MPNet, it only handles one-mode undirected networks for now, but part of my motivation for this implementation in Python was to make it readable as a demonstration or reference implementation, and easy to add new change statistics etc. This should be fine for small amounts of missing data. However, if there is a large amount of missing data, and specifically if the data is missing because it is a network sample rather than simply some data missing at random, it may be more appropriate to consider it as a network sampling problem for ALAAM (see Stivala et al. 2020) Regards, Alex. Institute of Computational Science, Università della Svizzera italiana. Byshkin, M., Stivala, A., Mira, A., Robins, G., & Lomi, A. (2018). Fast maximum likelihood estimation via equilibrium expectation for large network data. Scientific Reports, 8(1), 1-11. Stivala, A. D., Gallagher, H. C., Rolls, D. A., Wang, P., & Robins, G. L. (2020). Using Sampled Network Data With The Autologistic Actor Attribute Model. arXiv preprint arXiv:2002.00849. On Mon, Jun 15, 2020 at 11:22 PM Emiel de Lange <[log in to unmask]> wrote: > ***** To join INSNA, visit https://urldefense.proofpoint.com/v2/url?u=http-3A__www.insna.org&d=DwIFaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=XrwS5980_B0ppSPHcalrMQTUjBlb-DfyDd4-4FUg0v4&s=aECgtg9vg5mlBHIzktXoIJ8f5AL6fUAFrTop990yHc4&e= ***** > > Hi, > > I am trying to use MPNet to estimate ALAAMs. However, I receive an error > message saying the input string is incorrect. > > I wonder if this might be because I have NAs in my attribute files. Can > ALAAMs in MPNet handle missing attribute data? > > Is it possible to estimate ALAAMs in R? > > Many thanks, > > Emiel > > The University of Edinburgh is a charitable body, registered in Scotland, > with registration number SC005336. > > _____________________________________________________________________ > SOCNET is a service of INSNA, the professional association for social > network researchers (https://urldefense.proofpoint.com/v2/url?u=http-3A__www.insna.org&d=DwIFaQ&c=sJ6xIWYx-zLMB3EPkvcnVg&r=yQQsvTNAnbvDXGM4nDrXAje4pr0qHX2qIOcCQtJ5k3w&m=XrwS5980_B0ppSPHcalrMQTUjBlb-DfyDd4-4FUg0v4&s=aECgtg9vg5mlBHIzktXoIJ8f5AL6fUAFrTop990yHc4&e= ). To unsubscribe, send > an email message to [log in to unmask] containing the line > UNSUBSCRIBE SOCNET in the body of the message. > _____________________________________________________________________ SOCNET is a service of INSNA, the professional association for social network researchers (http://www.insna.org). To unsubscribe, send an email message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET in the body of the message.