General Location Model as e.g. found in "Statistical Analysis with Missing Data". This version can be fit to a data.frame or numdfr without missing data, and supports prediction of new data and 'completion prediction' of data with missing values. It also supports conditional completion (as needed in EMLasso).
|Date of publication||2013-04-17 15:43:49|
|Maintainer||Nick Sabbe <email@example.com>|
|License||GPL (>= 2)|
combineGLoMos: Combine a set of similar GLoMo objects into 1
getGuidData: Unique identifiers for all rows of dfr and their matches in a...
GLoMo: Fit naive General Location Model
GLoMo-package: Naive General Location Model
predict.conditional: Predict from GLoMo model with conditional rejection
predict.GLoMo: Predict (sample) data from GLoMo model
randomFillAndRepeatDataRow: Fill unmatched datarow in GLoMo
rCatsAndCntInDfr: (Multiply) complete dataset based on marginal properties of...
reusableDataForGLoMoSampling: Calculate GLoMo data that is usable for repeated 'completing'...
updateGuidData: Update 'GuidData' object from one GLoMo to the next