It may be simpler to specify the order in the contrasts rather than trying to order the data. See the C function (notice capitol C). I have never tried this with the bigglm function, so I don't know if it will work the same way or not. But if it works, then that may be a simpler approach.
On Tue, Mar 3, 2015 at 1:02 PM, Glenn Schultz <glennmschu...@me.com> wrote: > I can get bigglm working with the following code. > > ModelFit <- bigglm(SMM ~ > I(1-.88 * exp(-.192 * LoanAge))+ > ns(Incentive, df = 5)+ > Purpose + > Occupancy + > TPO + > Servicer, > data = sqlQuery(Train.Data, ModelData), > family = binomial(link = "logit"), > chuncksize = 10000, > maxit = 100) > > However, I would like to order the factors so I wrote the following code > to make data. However, it is not working. I have read through the manual > as well as some examples provided and I am not having much success with the > revised code below. I think I need to make data and provide ordering of > the factors in the make data but so far this scheme has not worked. I > think I am missing somethin any insights are appreciated. > > Best Regards, > Glenn > > make.data <- function(connection, query, chunksize,...){ > > function(reset = FALSE) { > if (reset) { > if (got > 0) { > dbClearResult(result) > result <<- dbSendQuery(Train.Data, ModelData) > got <<- 0 > } > return(TRUE) > } > rval <- fetch(result, n = chunksize) > got <<- got + nrow(rval) > if (nrow(rval) == 0) > return(NULL) > return(rval) > } > } > > data <- make.data(connection = Train.Data, query = ModelData, chunksize = > 10000) > > ModelFit <- bigglm(SMM ~ > I(1-.88 * exp(-.192 * LoanAge))+ > ns(Incentive, df = 5)+ > Purpose + > Occupancy + > TPO + > Servicer, > data = data, > family = binomial(link = "logit"), > maxit = 100) > > > > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/ > posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Gregory (Greg) L. Snow Ph.D. 538...@gmail.com [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.