Methods to summarize Linear Models fits
summary method for class 'speedlm'.
## S3 method for class 'speedlm' summary(object, correlation = FALSE,...) ## S3 method for class 'speedlm' coef(object,...) ## S3 method for class 'speedlm' vcov(object,...) ## S3 method for class 'speedlm' logLik(object,...) ## S3 method for class 'speedlm' AIC(object,...,k = 2)
object |
an object of class 'speedlm'. |
correlation |
logical. Do you want to print the correlation matrix? By default it is false. |
k |
numeric, the penalty per parameter to be used; the default k = 2 is the classical AIC. |
... |
further optional arguments |
coefficients |
the matrix of coefficients, standard errors, t-statistics and two-side p-values. |
rdf |
degrees of freedom of the fitted model. It is a component from |
call |
the component from |
r.squared |
R^2, the fraction of variance explained by the model. |
adj.r.squared |
the "adjusted" R^2 statistic, penalizing for higher p. |
fstatistic |
(for models including non-intercept terms) a 3-vector with the value of the F-statistic with its numerator and denominator degrees of freedom. |
f.pvalue |
p-value of the F-statistic. |
RSS |
Residual sum of squares. |
var.res |
estimated variance of residuals. |
rank |
the component from |
correlation |
(only if |
... |
the results from the functions |
Marco ENEA
y <- rnorm(100,1.5,1)
x <- round(matrix(rnorm(200), 100, 2), digits = 3)
colnames(x) <- c("s1","s2")
da <- data.frame(y, x)
m <- speedlm(y ~ s1 + s2,da)
summary(m)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.