eDist | R Documentation |
S3 methods for manipulating eDist objects
## S3 method for class 'eDist'
logLik(object, ...)
## S3 method for class 'eDist'
AIC(object, ..., k = 2)
AICc(object)
## S3 method for class 'eDist'
AICc(object, ...)
## S3 method for class 'eDist'
vcov(object, ..., corr = FALSE)
BIC(object)
## S3 method for class 'eDist'
BIC(object, ...)
MDL(object)
## S3 method for class 'eDist'
MDL(object, ...)
## S3 method for class 'eDist'
print(x, ...)
## S3 method for class 'eDist'
plot(x, ...)
object, |
x An object of class eDist, usually the output of a parameter estimation function. |
... |
Additional parameters |
k |
numeric, The penalty per parameter to be used; the default k = 2 is the classical AIC. |
corr |
logical; should vcov() return correlation matrix (instead of variance-covariance matrix). |
x, |
A list to be returned as class eDist. |
plot |
logical; if TRUE histogram, P-P and Q-Q plot of the distribution returned else only parameter estimation is returned. |
The MDL only works for parameter estimation by numerical maximum likelihood.
A. Jonathan R. Godfrey, Sarah Pirikahu, and Haizhen Wu.
Myung, I. (2000). The Importance of Complexity in Model Selection. Journal of mathematical psychology, 44(1), 190-204.
X <- rnorm(20)
est.par <- eNormal(X, method ="numerical.MLE")
logLik(est.par)
AIC(est.par)
AICc(est.par)
BIC(est.par)
MDL(est.par)
vcov(est.par)
vcov(est.par,corr=TRUE)
print(est.par)
plot(est.par)
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