Well, first of all, note that there is no "lms" method for the stats package's lm() function. You can't just make stuff up, you know!
And second, ?lmsreg -- after loading MASS via library(MASS), if you haven't already done this after your install -- is what you want. Other than ?lmsreg and what Enrico pointed you to, however, you'll have to manage on your own. Statistical tutorials are not the remit of this list. You might wish to consult with someone locally for help. You may be able to get an answer to a post of a specific question about usage **if you post code that fails** and otherwise follow the posting guide (below). Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Sat, Oct 8, 2016 at 1:10 PM, Bryan Mac <[email protected]> wrote: > I am confused reading the document. > > I have installed and added the package (MASS). > > What is the function for LMS Regression? > > > Bryan Mac > [email protected] > > > >> On Oct 8, 2016, at 6:17 AM, Enrico Schumann <[email protected]> wrote: >> >> On Sat, 08 Oct 2016, Bryan Mac <[email protected]> writes: >> >>> Hi R-help, >>> >>> How do you perform least median square regression in R? Here is what I have >>> but received no output. >>> >>> LMSRegression <- function(df, indices){ >>> sample <- df[indices, ] >>> LMS_NAR_NIC_relation <- lm(sample$NAR~sample$NIC, data = sample, method = >>> "lms") >>> rsquared_lms_nar_nic <- summary(LMS_NAR_NIC_relation)$r.square >>> >>> LMS_SQRTNAR_SQRTNIC_relation <- lm(sample$SQRTNAR~sample$SQRTNIC, data = >>> sample, method = "lms") >>> rsquared_lms_sqrtnar_sqrtnic <- >>> summary(LMS_SQRTNAR_SQRTNIC_relation)$r.square >>> >>> out <- c(rsquared_lms_nar_nic, rsquared_lms_sqrtnar_sqrtnic) >>> return(out) >>> } >>> >>> Also, which value should be looked at decide whether this is best >>> regression model to use? >>> >>> Bryan Mac >>> [email protected] >>> >> >> A tutorial on how to run such regressions is included >> in the NMOF package. >> >> https://cran.r-project.org/package=NMOF/vignettes/PSlms.pdf >> >> >> -- >> Enrico Schumann >> Lucerne, Switzerland >> http://enricoschumann.net > > ______________________________________________ > [email protected] 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. ______________________________________________ [email protected] 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.
