Least Median Square Regression

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Least Median Square Regression

 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 [hidden email]         [[alternative HTML version deleted]] ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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Re: Least Median Square Regression

 Hello, Use package quantreg, function rq(). install.packages("quantreg") ?rq Hope this helps, Rui Barradas Citando Bryan Mac <[hidden email]>: > 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 > [hidden email] > > > > > [[alternative HTML version deleted]] > > ______________________________________________ > [hidden email] 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. ______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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Re: Least Median Square Regression

 In reply to this post by bmac On Sat, 08 Oct 2016, Bryan Mac <[hidden email]> 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 > [hidden email] > 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______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.
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Re: Least Median Square Regression

 I am confused reading the document. I have installed and added the package (MASS). What is the function for LMS Regression? Bryan Mac [hidden email] > On Oct 8, 2016, at 6:17 AM, Enrico Schumann <[hidden email]> wrote: > > On Sat, 08 Oct 2016, Bryan Mac <[hidden email]> 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 >> [hidden email] >> > > 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______________________________________________ [hidden email] mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code.