fitvbiglm: Automated Fitting of Biglm Object

In allan: Automated Large Linear Analysis Node

Description

Fits a biglm object on any sized dataset. Automatically chunks up the data and returns a fitted biglm object on the entire dataset.

Usage

fitvbiglm(BaseModel, filename, currentchunksize = -1, silent = TRUE, MemoryAllowed = 0.5, TestedRows = 1000, AdjFactor = 0.095)

Arguments

BaseModel	BaseModel is a biglm object. Must have a formula in the biglm object that specifies the model ie. y~x1 + x2 etc.
filename	Name of the training set file
currentchunksize	Allows user to specify the size of chunking. default is -1 for automatically determining the size by use of getbestchunksize function
silent	specify as TRUE to suppress all nonimportant messages by the function
MemoryAllowed	See function getbestchunksize for argument description.
TestedRows	See function getbestchunksize for argument description.
AdjFactor	See function getbestchunksize for argument description.

Value

Returns a fitted biglm object.

Author(s)

Alan Lee [e-mail]

Examples

#Get external data.  For your own data skip this next line and replace all
#instance of SampleData with "YourFile.csv".
SampleData=system.file("extdata","SampleDataFile.csv", package = "allan")

#get smaller chunk of data to fit initial model
columnnames<-names(read.csv(SampleData, nrows=2,header=TRUE))
datafeed<-readinbigdata(SampleData,chunksize=1000,col.names=columnnames)
datafeed(TRUE)
firstchunk<-datafeed(FALSE)

#create a biglm model from the small chunk with all variables that will be consdered
#for variable selection.
bigmodel <- biglm(PurePremium ~ cont1 + cont2 + cont3 + cont4 + cont5,data=firstchunk,weights=~cont0)

#now fit the model on the humongous dataset
finalbigmodel<-fitvbiglm(bigmodel,SampleData)

allan documentation built on May 1, 2019, 8:43 p.m.