# Create An `amModel` Object That Pairs Models With Their Metadata Creates an object of class `amModel`, which is a fitted model object (or similar) with mandatory metadata. An S4 class to store models with descriptive metadata. class ```r amModel(model, ...) ``` ## Arguments - `model`: A model fit object or similar. - ``...``: Named metadata elements, either supplied individually and coerced to list or supplied as a named list. ## Returns An object of class `amModel` suitable for inclusion in an `amModelLib`. ## Slots - **`model`**: A model fit object, e.g. from `lm` or any single object containing the means to predict values from data. - **`metadata`**: A named list of length 1 character vectors that form name:value pairs, e.g. the analyst, the project, the data used, etc. The metadata name `data` can be used to link the model with the name of a data object, and when manipulated in the `amModelLib` an effort will be made to keep the model and data together. When embedded in an `amModelLib`, model metadata may be retrieved or set with `modelMeta`. ## Examples ```r # run models from from lm helpfile ## Annette Dobson (1990) "An Introduction to Generalized Linear Models". ## Page 9: Plant Weight Data. ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14) trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69) group <- gl(2, 10, 20, labels = c("Ctl","Trt")) weight <- c(ctl, trt) lm.D9 <- lm(weight ~ group) lm.D90 <- lm(weight ~ group - 1) # omitting intercept # note the original class of models is 'lm' class(lm.D9) # wrap lm.D9 in an amModel object mod1 <- amModel(model = lm.D9, comment='example from lm') # summarize mod1; summary for the original object class, plus the metadata summary(mod1) # convert lm.D90 to an amModel object mod2 <- amModel(model = lm.D90, comment='second example from lm') # use the function, amModelLib, to create a new amModelLib that includes both models # the models must be supplied as a named list mymodels <- amModelLib( models = list( mod1 = mod1, mod2 = mod2 ), description = "This amModelLib stores linear models from the lm helpfile." ) # list the models of the amModelLib lsModels(mymodels) # the modelMeta function can be used to retrieve model metadata modelMeta(mymodels, 'mod1') # the modelMeta function can also be used to set model metadata modelMeta(mymodels, 'mod1') <- list( url = "https://stat.ethz.ch/R-manual/R-devel/library/stats/html/lm.html" ) modelMeta(amml = mymodels, 'mod1') # use getAMModel to extract the model by name getAMModel(amml = mymodels, 'mod2', as.list = FALSE) # notice the retrieved model is returned in its original class class(getAMModel(amml = mymodels, 'mod2', as.list = FALSE)) # create a new empty amModelLib called mymodels2 mymodels2 <- amModelLib(description = "A second amModelLib called mymodels2.") # use insertAMModelLib to insert amModel objects to an existing amModelLib mymodels2 <- insertAMModelLib(models = list(mod1 = mod1, mod2 = mod2)) # use rmModel to remove an amModel object from an amModelLib rmModel('mod2', amml = mymodels2) ``` ## See Also Other amModelLib: `AMModels`, `amData`, `amModelLib`, `getters`, `grepAMModelLib`, `insertAMModelLib`, `lsModels`, `rmModel`

amModel function