Description Usage Arguments Value Author(s) See Also Examples
Summary the maximum-likelihood estimation.
1 2 |
object |
object of class |
... |
currently not used. |
summary.sgtest
returns an
object of class 'summary.sgtest'
with the following components:
maximum |
log-likelihood value of estimates (the last calculated value if not converged) of the method that achieved the greatest log-likelihood value. |
estimate |
estimated parameter value with the method that achieved the greatest log-likelihood value. |
convcode |
|
niter |
The amount of iterations that the method which achieved the the greatest log-likelihood value used to reach its estimate. |
best.method.used |
name of the method that achieved the greatest log-likelihood value. |
optimx |
A |
gradient |
vector, gradient value of the estimates with the method that achieved the greatest log-likelihood value. |
hessian |
matrix, hessian of the estimates with the method that achieved the greatest log-likelihood value. |
varcov |
variance/covariance matrix of the maximimum likelihood estimates |
std.error |
standard errors of the estimates |
z.score |
the z score of the estimates |
p.value |
the p-values of the estimates |
summary.table |
a |
Carter Davis, cdavis40@chicagobooth.edu
the optimx
CRAN package
1 2 3 4 5 6 7 8 9 10 11 | # SINGLE VARIABLE ESTIMATION:
### generate random variable
set.seed(7900)
n = 1000
x = rsgt(n, mu = 2, sigma = 2, lambda = -0.25, p = 1.7, q = 7)
### Get starting values and estimate the parameter values
start = list(mu = 0, sigma = 1, lambda = 0, p = 2, q = 10)
result = sgt.mle(X.f = ~ x, start = start, method = "nlminb")
print(result)
print(summary(result))
|
Loading required package: optimx
Loading required package: numDeriv
Skewed Generalized T MLE Fit
Best Result with nlminb Maximization
Convergence Code 0: Successful Convergence
Iterations: 24, Log-Likelihood: -2076.966
Estimate(s):
mu sigma lambda p q
1.9735 2.0075 -0.2761 1.7199 7.7856
Skewed Generalized T MLE Fit
Best Result with nlminb Maximization
Convergence Code 0: Successful Convergence
Iterations: 24, Log-Likelihood: -2076.966
Est. Std. Err. z P>|z|
mu 1.9735 0.0634 31.1041 0.0000 ***
sigma 2.0075 0.0594 33.7782 0.0000 ***
lambda -0.2761 0.0410 -6.7376 0.0000 ***
p 1.7199 0.2673 6.4333 0.0000 ***
q 7.7856 7.5662 1.0290 0.3035
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
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