Description Usage Arguments Details Value
summary
method for class "ptsr"
.
1 2 3 4 5 6 
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, zstatistic and corresponding (twosided) pvalue. 
sigma.res 
the square root of the estimated variance of the random error σ^2 = \frac{1}{nk} ∑_i r[i]^2, where r[i] is the ith residual, 
df 
degrees of freedom, a 3vector (k, nk, k*), the first being the number of nonaliased 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 loglikelihood 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. 
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