bigglm: Bounded memory linear regression

In biglm: Bounded Memory Linear and Generalized Linear Models

Bounded memory linear regression

Description

bigglm creates a generalized linear model object that uses only p^2 memory for p variables.

Usage

bigglm(formula, data, family=gaussian(),...)
## S3 method for class 'data.frame'
bigglm(formula, data,...,chunksize=5000)
## S3 method for class 'function'
bigglm(formula, data, family=gaussian(),
     weights=NULL, sandwich=FALSE, maxit=8, tolerance=1e-7,
     start=NULL,quiet=FALSE,...)
## S3 method for class 'RODBC'
bigglm(formula, data, family=gaussian(),
      tablename, ..., chunksize=5000)
## S4 method for signature 'ANY,DBIConnection'
bigglm(formula, data, family=gaussian(),
tablename, ..., chunksize=5000)
## S3 method for class 'bigglm'
vcov(object,dispersion=NULL, ...)
## S3 method for class 'bigglm'
deviance(object,...)
## S3 method for class 'bigglm'
family(object,...)
## S3 method for class 'bigglm'
AIC(object,...,k=2)

Arguments

formula	A model formula
data	See Details below. Method dispatch is on this argument
family	A glm family object
chunksize	Size of chunks for processng the data frame
weights	A one-sided, single term formula specifying weights
sandwich	TRUE to compute the Huber/White sandwich covariance matrix (uses p^4 memory rather than p^2)
maxit	Maximum number of Fisher scoring iterations
tolerance	Tolerance for change in coefficient (as multiple of standard error)
start	Optional starting values for coefficients. If NULL, maxit should be at least 2 as some quantities will not be computed on the first iteration
object	A bigglm object
dispersion	Dispersion parameter, or NULL to estimate
tablename	For the SQLiteConnection method, the name of a SQL table, or a string specifying a join or nested select
k	penalty per parameter for AIC
quiet	When FALSE, warn if the fit did not converge
...	Additional arguments

Details

The data argument may be a function, a data frame, or a SQLiteConnection or RODBC connection object.

When it is a function the function must take a single argument reset. When this argument is FALSE it returns a data frame with the next chunk of data or NULL if no more data are available. Whenreset=TRUE it indicates that the data should be reread from the beginning by subsequent calls. The chunks need not be the same size or in the same order when the data are reread, but the same data must be provided in total. The bigglm.data.frame method gives an example of how such a function might be written, another is in the Examples below.

The model formula must not contain any data-dependent terms, as these will not be consistent when updated. Factors are permitted, but the levels of the factor must be the same across all data chunks (empty factor levels are ok). Offsets are allowed (since version 0.8).

The SQLiteConnection and RODBC methods loads only the variables needed for the model, not the whole table. The code in the SQLiteConnection method should work for other DBI connections, but I do not have any of these to check it with.

Value

An object of class bigglm

References

Algorithm AS274 Applied Statistics (1992) Vol.41, No. 2

See Also

biglm, glm

Examples

data(trees)
ff<-log(Volume)~log(Girth)+log(Height)
a <- bigglm(ff,data=trees, chunksize=10, sandwich=TRUE)
summary(a)

gg<-log(Volume)~log(Girth)+log(Height)+offset(2*log(Girth)+log(Height))
b <- bigglm(gg,data=trees, chunksize=10, sandwich=TRUE)
summary(b)

## Not run: 
## requires internet access
make.data<-function(urlname, chunksize,...){
      conn<-NULL
     function(reset=FALSE){
     if(reset){
       if(!is.null(conn)) close(conn)
       conn<<-url(urlname,open="r")
     } else{
       rval<-read.table(conn, nrows=chunksize,...)
       if (nrow(rval)==0) {
            close(conn)
            conn<<-NULL
            rval<-NULL
       }
       return(rval)
     }
  }
}

airpoll<-make.data("http://faculty.washington.edu/tlumley/NO2.dat",
        chunksize=150,
        col.names=c("logno2","logcars","temp","windsp",
                    "tempgrad","winddir","hour","day"))

b<-bigglm(exp(logno2)~logcars+temp+windsp,
         data=airpoll, family=Gamma(log),
         start=c(2,0,0,0),maxit=10)
summary(b)         

## End(Not run)

biglm documentation built on June 22, 2024, 9:43 a.m.