Displaying 3 results from an estimated 3 matches for "coefficient_of_determin".
2013 Jan 28
2
Adjusted R-squared formula in lm()
...seem to exist several formula's to calculate Adjusted R-squared.
Wherry’s formula [1-(1-R2)·(n-1)/(n-v)]
McNemar’s formula [1-(1-R2)·(n-1)/(n-v-1)]
Lord’s formula [1-(1-R2)(n+v-1)/(n-v-1)]
Stein 1-(n-1/n-k-1)(n-2)/n-k-2) (n+1/n)
Theil's formula (found here: http://en.wikipedia.org/wiki/Coefficient_of_determination)
According to the textbook Field, Discovering Statistics Using R (2012, p. 273) R uses Wherry's equation which "tells us how much variance in Y would be accounted for if the model had been derived from th. population from which the sample was taken". He does not give the formula...
2008 Apr 24
0
Coefficient of determination in a regression model with AR(1) residuals
...(and therefore contradicting
the i.i.d. assumption of the regression model). I then used gls()
[library nlme] to fit a linear regression model with AR(1)-residuals.
The residuals look perfect (residual plot, ACF, PACF, QQPlot, Ljung-
Box test).
As mentioned on http://en.wikipedia.org/wiki/
Coefficient_of_determination (citation [2008-04-24]: "For cases other
than fitting by ordinary least squares, the R^2 statistic can be
calculated as above" and later: "Values for R^2 can be calculated for
any type of predictive model"), I tried to calculate the standard R^2
for the model with A...
2011 Mar 04
1
linear model - lm (Adjusted R-squared)?
Hi,
Sorry for the naive question, but what exactly does the 'Adjusted R-squared'
coefficient in the summary of linear model adjust for?
Sample code:
> x <- rnorm(15)
> y <- rnorm(15)
> lmr <- lm(y~x)
> summary(lmr)
Call:
lm(formula = y ~ x)
Residuals:
Min 1Q Median 3Q Max
-1.7828 -0.7379 -0.4485 0.7563 2.1570
Coefficients: