On Sat, 08 Oct 2016, Bryan Mac <bryanmac...@gmail.com> writes:
> I am confused reading the document.
>
> I have installed and added the package (MASS).
>
> What is the function for LMS Regression?
>
In MASS, it is 'lqs'.
But the vignette provides a code example for how to
compute 'manually' an LMS-regression, i.e. how to do
the actual optimisation.
>
>> On Oct 8, 2016, at 6:17 AM, Enrico Schumann <e...@enricoschumann.net> wrote:
>>
>> On Sat, 08 Oct 2016, Bryan Mac <bryanmac...@gmail.com> 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
>>> bryanmac...@gmail.com
>>>
>>
>> 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
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