methods-amModelLib: Methods For Displaying, Summarizing, And Manipulating...

In AMModels: Adaptive Management Model Manager

Description

Getters and setters for AMModelLib objects.

Usage

## S4 method for signature 'amModelLib'
summary(object, name, ...)

## S4 method for signature 'amModelLib'
show(object)

## S4 method for signature 'amModelLib'
c(x, ..., recursive = FALSE)

## S4 method for signature 'amModelLib,ANY,ANY,ANY'
x[i, j, ..., drop = TRUE]

## S4 method for signature 'amModelLib,ANY,ANY'
x[[i]]

## S4 method for signature 'amModelLib'
x$name

## S4 replacement method for signature 'amModelLib,ANY,ANY'
x[[i, j, ...]] <- value

Arguments

object	An amModelLib object.
name	For $ A literal character string or a name (possibly backtick quoted); for summary an amModel or amData name as character string.
...	Additional arguments passed to other functions or methods.
x	An amModelLib object.
recursive	Iterate recursively through lists (ignored).
i, j	indices specifying elements to extract or replace. Indices are numeric or character vectors or empty (missing) or NULL.
drop	Not used.
value	Replacement value.

Details

Summary adds the metadata to the default show method. If name is supplied the call is passed on to the amModel or amData object with the specified name.

Value

summary returns a list with the same elements displayed during the call. Others return an amModelLib object.

Examples

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

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

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

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



# 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
    )
)

summary(mymodels)
mymodels <- c(mymodels, mymodels)
mymodels[c(2,1)]
mymodels[[1]]
mymodels[['full.model']]
mymodels$full.model

AMModels documentation built on May 1, 2019, 10:25 p.m.