# S3 method of class 'data.frame'
speedlm(formula, data, weights = NULL, offset = NULL, sparse = NULL, 
        set.default = list(), method=c('eigen','Cholesky','qr'), 
        model = FALSE, y = FALSE, fitted = FALSE, subset=NULL, ...)

# S3 method of class 'matrix'
speedlm.fit(y, X, intercept = FALSE, offset = NULL, row.chunk = NULL, 
            sparselim = 0.9, camp = 0.01, eigendec = TRUE, 
            tol.solve = .Machine$double.eps, sparse = NULL, tol.values = 1e-07, 
            tol.vectors = 1e-07, method=c('eigen','Cholesky','qr'), ...)

speedlm.wfit(y, X, w, intercept = FALSE, offset = NULL, row.chunk = NULL, 
             sparselim = 0.9, camp = 0.01, eigendec = TRUE, 
             tol.solve = .Machine$double.eps, sparse = NULL, tol.values = 1e-07, 
             tol.vectors = 1e-07, method=c('eigen','Cholesky','qr'), ...)
                      
# S3 method of class 'speedlm' (object) and 'data.frame' (data)                    
## S3 method for class 'speedlm'
update(object, formula, data, add=TRUE, evaluate=TRUE, 
                           subset=NULL, offset=NULL, weights=NULL,...)

# S3 method of class 'speedlm' (object) and 'data.frame' (data)                    
updateWithMoreData(object, data, weights = NULL, offset = NULL, sparse = NULL, 
                   all.levels = FALSE, set.default = list(), subset=NULL,...)

## Not run: 
n <- 1000
k <- 3
y <- rnorm(n)
x <- round(matrix(rnorm(n * k), n, k), digits = 3)
colnames(x) <- c("s1", "s2", "s3") 
da <- data.frame(y, x)
do1 <- da[1:300,]
do2 <- da[301:700,]
do3 <- da[701:1000,]

m1 <- speedlm(y ~ s1 + s2 + s3, data = do1)
m1 <- update(m1, data = do2)
m1 <- update(m1, data = do3)

m2 <- lm(y ~ s1 + s2 + s3, data = da)
summary(m1)
summary(m2)

## End(Not run)

## Not run: 
  # as before but recursively
  make.data <- function(filename, chunksize,...){       
    conn <- NULL
    function(reset=FALSE, header=TRUE){
      if(reset){
        if(!is.null(conn)) close(conn)
         conn<<-file(filename,open="r") 
      } else{
        rval <- read.table(conn, nrows=chunksize,header=header,...)
        if (nrow(rval)==0) {
          close(conn)
          conn<<-NULL
          rval<-NULL
        }
        return(rval)
      }
    }
  }

  write.table(da,"da.txt",col.names=TRUE,row.names=FALSE,quote=FALSE) 
  x.names <- c("s1", "s2", "s3")
  dat <- make.data("da.txt",chunksize=300,col.names=c("y",x.names))
  dat(reset=TRUE) 
  da2 <- dat(reset=FALSE)
  
  # the first model runs on the first 300 rows.
  m3 <- speedlm(y ~ s1 + s2 + s3, data=da2)

  # the last three models run on the subsequent 300, 300 and 100 rows, respectively
  for (i in 1:3){
    da2 <- dat(reset=FALSE, header=FALSE)
    m3 <- update(m3, data=da2, add=TRUE)
  }  
  all.equal(coef(m1),coef(m3))  
  file.remove("da.txt")

## End(Not run)