spacom (version 1.0-5)

SpawAggregateOutput-class: Class "SpawAggregateOutput"

Description

Output object of the function SpawAggregate.

Objects from the Class

Objects can be created by calls of the form new("SpawAggregateOutput", ...).

Slots

seed:

Object of class "ANY" ~~

contains the random seed which was used in SpawAggregate. Use this seed if you want to reproduce the same resamples.

aggregated.samples:

Object of class "list" ~~

A list of matrices of dimension $n by m$ where $n$ is the number of contextual units and $m$ is the number of resamples containing the aggregated context data for each resample.

frames:

Object of class "list" ~~

A list of data.frames. One data.frame per contextual name, each containing the mean estimate, standard deviation, median and confidence intervals of the corresponding contextual variable by contextual unit.

Methods

merge

signature(x = "SpawAggregateOutput", y = "SpawAggregateOutput"): Merges SpawAggregateOutput objects. This is useful if contextual data is being aggregated from different individual level data bases.

[

signature(x = "SpawAggregateOutput", i = "ANY", j = "ANY", drop = "ANY"): Allows to extract the dataframe corresponding to a bootstrap sample.

getSample

signature(object = "SpawAggregateOutput"): Also allows to extract the dataframe corresponding to a bootstrap sample.

length

signature(x = "SpawAggregateOutput"): Returns the number of bootstrap samples contained in the object.

names

signature(x = "SpawAggregateOutput"): Returns the names of aggregated variables in the object

names<-

signature(x = "SpawAggregateOutput"): Allows to assign names to the aggregates in the object

names<-

signature(x = "SpawAggregateOutput", NA = "ANY"): Allows to change names to the aggregated variables in the object.

show

signature(object = "SpawAggregateOutput"): Prints a meaningful short description of the object.

See Also

is generated by SpawAggregate

Examples

## load distance matrix
data(d_geo)
## create a weight matrix
geow.50 <- WeightMatrix(d_geo, bandwidth=50)
## load contextual data
data(traces_event)

## aggregate data

wv.int <- SpawAggregate(contextual.data=traces_event,
                        context.id="area.name",
                        contextual.names=c("w_all", "w_all"),
                        contextual.weight.matrices=list(NULL, geow.50),
                        aggregation.functions="weighted.mean",
                        design.weight.names="weight",
                        nb.resamples=4)
## check the number of samples
length(wv.int)

## check the second sample
head(wv.int[2])

## change the names of the weighted indicators to more significant ones
names(wv.int) <- c("w_all.0", "w_all.50")

showClass("SpawAggregateOutput")