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======================================================================================================================== Hi, I cannot participate in todays meeting. With reference to Kelds mail below: As I have understood it RDS is a system where you can identify and reference an unique physical object (from 3 topological aspects) within, for example, a power plant. This means that you can build a representation of the plant as a hierarchy of objects (and the relations between objects?). I can see a need to be able to categorize what objects a topic is related to/describes. This is needed for filtering or retrieval purposes. The new subject scheme feature in DITA 1.2 could be used to address this issue (as you see I'm a big fan of this feature). Each unique object in the RDS is "registered" as a subject in the scheme map. Then the RDS for a specific plant could be seen as a taxonomy. Further more a classification map could be used to relate DITA topics the a subject with in the scheme. One problem with the subject scheme feature of DITA 1.2, as I see it, is the fact that you can classify a DITA topic using the topicmeta part and then do the same thing using a subject scheme, where there are no coordination. In fact you can state one thing in the topicmeta, but state contradictory data in your classification map. We surely need to look into this from our work group. The subject scheme feature is primarely intended to define ENUMs to not hardcode them in a DTD, but the sheme can also be used to represent the subjects a topic is describing, for example parts or objects/products in a machine or plant. I'm planning to give some more input which is also related to the ditatoctemp proposal and the filtering proposal. Br, Jonatan ________________________________________ From: Keld Jellesen [ keld ... @advice2u.dk ] Sent: Wednesday, June 02, 2010 1:47 PM To: chri ... @seicodyne.ch ; dita ... @lists.oasis-open.org Subject: RE: [dita-machine- industry ] Groups - DITA Machine Industry SC Meeting modified I thing we need to address a RDS system with DITA-Machinery SC. RDS is Reference Designation System and is used in various places for example the energy sector. The overall foundation for this is the ISO-81346, which is quite abstract. However VGB have developed a solution called RDS-PP (Power Plant) which is a concrete suggestion to build a RDS system for the wind energy sector. It is in close family with KKS which I can imagine will be included in the RDS-PP for the future. Best Regards Keld -----Original Message----- From: chri ... @seicodyne.ch [mailto: chri ... @seicodyne.ch ] Sent: 25. maj 2010 16:08 To: dita ... @lists.oasis-open.org Subject: [dita-machine- industry ] Groups - DITA Machine Industry SC Meeting modified Unfortunatley the conference call has not been activated for us. If it is not getting activated till quarter past, we will switch to the alternative calling number: +1 218 486 8700 Passcode: 185771 Best regards Chris --------------------------------------------------------------------- To unsubscribe from this mail list, you must leave the OASIS TC that generates this mail. Follow this link to all your TCs in OASIS at: https://www.oasis-open.org/apps/org/workgroup/portal/my_workgroups.php --------------------------------------------------------------------- To unsubscribe from this mail list, you must leave the OASIS TC that generates this mail. Follow this link to all your TCs in OASIS at: https://www.oasis-open.org/apps/org/workgroup/portal/my_workgroups.php Dear Jarrod, You asked about ASReml's na.include=Y option. No, this does not do any fancy imputation or augmentation like MCMCglmm does either. As you can read on p113 of the user guide (p139 of the pdf) http://www.vsni.co.uk/downloads/asreml/release3/UserGuide.pdf !mvinclude just imputes zeros. This obviously assumes centred covariates. For factors, another factor level is created. Damian Damian Collins, Biometrician, I&I NSW dami ... @industry.nsw.gov.au Dear Doug, Perhaps I misunderstand Rubin's missing data theory, and/or perhaps its not relevant to Thierry's problem. I was under the impression that if the probability of missingness depends on the value observed for some other data (MAR), then by including this data and structuring the likelihood correctly then correct inferences (i.e. in the absence of missingness) could be made. Given that the default na.action of lmer seems to deletes other data (complete case analysis), it is hard to see how the other data can be used to 'correct' for missingness. MCMCglmm uses augmentation for missing data. Internally, this is often used just to simplify/speed up the matrix operations using dummy data. However, I had presumed that if users really did have MAR data then the augmentation would take care of this. I know ASReml has an na.includeY argument so presumably there is something to be gained by not reducing the problem to a complete-case analysis, but perhaps this function is there just to allow users to make predictions for missing data points. I know the asreml team read this list, so perhaps they could comment? Cheers, Jarrod, This message is intended for the addressee named and may contain confidential information. If you are not the intended recipient, please delete it and notify the sender. Views expressed in this message are those of the individual sender, and are not necessarily the views of their organisation. _______________________________________________ R-si ... @r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models