Please forgive my re-sending this question. I did not see any replies from my prior post. My apologies if I missed something.
Is the sigma from a lm, i.e.
fit1 <- lm(y~x)
summary(fit1)
summary(fit1)$sigma
the RMSE (root mean square error)
Thanks,
John
John David Sorkin M.D., Ph.D.
Chief, Biostatistics and Informatics
University of Maryland School of Medicine Division of Gerontology
Baltimore VA Medical Center
10 North Greene Street
GRECC (BT/18/GR)
Baltimore, MD 21201-1524
(Phone) 410-605-7119
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meaning of sigma from LM, is it the same as RMSE
3 messages · John Sorkin, Roy Mendelssohn - NOAA Federal, Mark Difford
?summary.lm -Roy
On Apr 4, 2012, at 4:47 PM, John Sorkin wrote:
Please forgive my re-sending this question. I did not see any replies from my prior post. My apologies if I missed something.
Is the sigma from a lm, i.e.
fit1 <- lm(y~x)
summary(fit1)
summary(fit1)$sigma
the RMSE (root mean square error)
Thanks,
John
John David Sorkin M.D., Ph.D.
Chief, Biostatistics and Informatics
University of Maryland School of Medicine Division of Gerontology
Baltimore VA Medical Center
10 North Greene Street
GRECC (BT/18/GR)
Baltimore, MD 21201-1524
(Phone) 410-605-7119
(Fax) 410-605-7913 (Please call phone number above prior to faxing)
Confidentiality Statement:
This email message, including any attachments, is for th...{{dropped:6}}
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On Apr 05, 2012; 1:47am John Sorkin wrote:
Is the sigma from a lm...the RMSE (root mean square error)
John, RMSE is usually calculated using the number of observations/cases, whereas summary.lm()$sigma is calculated using the residual degrees of freedom. See below: ## Helps to study the output of anova() set.seed(231) x <- rnorm(20, 2, .5) y <- rnorm(20, 2, .7) T.lm <- lm(y ~ x)
summary(T.lm)$sigma
[1] 0.7403162
anova(T.lm)
Analysis of Variance Table
Response: y
Df Sum Sq Mean Sq F value Pr(>F)
x 1 0.0036 0.00360 0.0066 0.9363
Residuals 18 9.8652 0.54807
sum(resid(T.lm)^2)
[1] 9.865225
sqrt(sum(resid(T.lm)^2)/18)
[1] 0.7403162
sqrt(sum(resid(T.lm)^2)/20) ## RMSE (y = 20)
[1] 0.7023256 ## OR
sqrt(mean((y-fitted(T.lm))^2))
[1] 0.7023256 Regards, Mark. ----- Mark Difford (Ph.D.) Research Associate Botany Department Nelson Mandela Metropolitan University Port Elizabeth, South Africa -- View this message in context: http://r.789695.n4.nabble.com/meaning-of-sigma-from-LM-is-it-the-same-as-RMSE-tp4533515p4534165.html Sent from the R help mailing list archive at Nabble.com.