AMModels (version 0.1.4)

grepAMModelLib: Search For A Model In A Model List Using grep

Description

Returns an abbreviated amModelLib object that contains models and data that meet search terms.

Usage

grepAMModelLib(pattern, amml, search = c("all", "model", "data"), ...)

Arguments

pattern

Search string or value, typically a model or data name

amml

An amModelLib object

search

Length 1 character vector indicating whether to search and return models or data that meet the search criteria.

…

Additional arguments to grep.

Value

An object of class amModelLib.

Details

grep is used to search both names, values (models/data), and metadata. An attempt is made to keep data with models if searching for models, or to keep models with data if searching for data, or to keep prior/posterior models together. The relational link between models their data relies on a case-agnostic 'data' element in the model metadata that names the linked data, and the same is true for models that use 'prior' to link to other models.

See Also

Other amModelLib: AMModels, amData, amModelLib, amModel, getters, insertAMModelLib, lsModels, rmModel

Examples

# NOT RUN {
# create dataset 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


# create two amModel objects with metadata and a soft link to the data
full.model <- amModel(
    lm.D9, 
    comment = 'full model', 
    source = 'lm helpfile (R).', 
    taxa = 'plants', 
    data = 'plant.data'
)

no.int.model <- amModel(
    lm.D90, 
    comment = 'model without intercept', 
    source = 'lm helpfile (R).', 
    taxa = 'plants', 
    data = 'plant.data'
)


# create an amData object that includes metadata
plant.data <- data.frame(group = group, weight = weight)
plant.data <- amData(
    plant.data, 
    comment = 'Dataset from lm helpfile.'
)

log.plant.data <- data.frame(group, log.weight=log(weight))
log.plant.data <- amData(
    log.plant.data, 
    comment = 'data to fit log model', 
    source = 'lm helpfile (R).'
)

# create an amModelLib that contains the two amModel objects and two amData objects
# the models and data must be supplied as named lists
mymodels <- amModelLib(
    models = list(
        full.model = full.model, 
        no.int.model = no.int.model
    ), 
    data=list(
        plant.data = plant.data, 
        log.plant.data = log.plant.data
    )
)


# search the entire amModelLib for the word 'intercept'
# the dataset associated with the model will be returned
grepAMModelLib("intercept", amml = mymodels) 

# the class of returned search is an amModelLib object
class(grepAMModelLib("intercept", amml = mymodels))  
 
# search for data containing the word 'log'
grepAMModelLib("log", amml = mymodels, search = "data") 

# search for models containing the word 'full'
# Because 'full.model' is soft-linked to a dataset, 
# the dataset information will be returned.
grepAMModelLib("full", amml = mymodels, search = "model") 

  
# }