| summary | R Documentation |
summary method for class "ptsr".
## S3 method for class 'ptsr'
summary(object, ...)
## S3 method for class 'summary.ptsr'
print(x, digits = max(3L, getOption("digits") - 3L),
signif.stars = getOption("show.signif.stars"), ...)
object |
object of class |
... |
further arguments passed to or from other methods. |
x |
an object of class |
digits |
minimal number of significant digits, see
|
signif.stars |
logical. If |
print.summary.btsr tries to be smart about formatting the
coefficients, standard errors, etc. and additionally provides
‘significance stars’.
The function summary.ptsr computes and returns a list
of summary statistics of the fitted model given in object.
Returns a list of class summary.ptsr, which contains the
following components:
residuals |
the residuals of the model. |
coefficients |
a k x 4 matrix with columns for the estimated coefficient, its standard error, z-statistic and corresponding (two-sided) p-value. |
sigma.res |
the square root of the estimated variance of the random error σ^2 = \frac{1}{n-k} ∑_i r[i]^2, where r[i] is the i-th residual, |
df |
degrees of freedom, a 3-vector (k, n-k, k*), the first being the number of non-aliased coefficients, the last being the total number of coefficients. |
vcov |
a k \times k matrix of (unscaled) covariances. The inverse ov the information matrix. |
loglik |
the sum of the log-likelihood values |
aic |
the AIC value. AIC = -2*loglik+2*k. |
bic |
the BIC value. BIC = -2*loglik + log(n)*k. |
hqc |
the HQC value. HQC = -2*loglik + log(log(n))*k. |