Hi CE.KA,
Take a look at the following:
# Data
set.seed(123)
x - rnorm(100)
y - 2 + 1.5*x + rnorm(100)
# Regression model
reg - lm(y ~ x)
# The summary
summary(reg)
# Objects present in the summary()
names(summary(reg))
# Extracting the coefficients
summary(reg)$coeff
HTH,
Jorge
On Wed, Oct 21, 2009 at 5:07 AM, CE.KA wrote:
Hi R users
I used R to get the results of a linear regression
reg-lm(y~x)
here are the results:
# Call:
# lm(formula = donnees$txi7098 ~ donnees$txs7098)
#
# Residuals:
# Min1QMedian3Q Max
# -0.037971 -0.013373 -0.004947 0.010618 0.053235
#
# Coefficients:
# Estimate Std. Error t value Pr(|t|)
# (Intercept) 0.085470.03028 2.822 0.011738 *
# donnees$txs7098 0.623060.12847 4.850 0.000150 ***
# ---
# Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1
#
# Residual standard error: 0.02199 on 17 degrees of freedom
# Multiple R-squared: 0.5805, Adjusted R-squared: 0.5558
# F-statistic: 23.52 on 1 and 17 DF, p-value: 0.0001502
I know how to get the coefficients as variable
for exemple:
reg$coefficients[1]=0.08547 (Estimate )
reg$coefficients[2]=0.62306 (Estimate )
My question is:
Is there a way to get the other results of lm as variables?
-Std. Errors?
-t value?
-Pr(|t|) ?
-Residual standard error?
-Multiple R-squared?
-F-statistic?
Best regards
--
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