summary.speedlm | R Documentation |

`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

speedlm

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)

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