coef.greybox | R Documentation |
These are the basic methods for the alm and greybox models that extract coefficients, their covariance matrix, confidence intervals or generating the summary of the model. If the non-likelihood related loss was used in the process, then it is recommended to use bootstrap (which is slow, but more reliable).
## S3 method for class 'greybox'
coef(object, bootstrap = FALSE, ...)
## S3 method for class 'alm'
confint(object, parm, level = 0.95, bootstrap = FALSE, ...)
## S3 method for class 'scale'
confint(object, parm, level = 0.95, bootstrap = FALSE, ...)
## S3 method for class 'alm'
vcov(object, bootstrap = FALSE, ...)
## S3 method for class 'scale'
vcov(object, bootstrap = FALSE, ...)
## S3 method for class 'alm'
summary(object, level = 0.95, bootstrap = FALSE, ...)
object |
The model estimated using alm or other greybox function. |
bootstrap |
The logical, which determines, whether to use bootstrap in the process or not. |
... |
Parameters passed to coefbootstrap function. |
parm |
The parameters that need to be extracted. |
level |
The confidence level for the construction of the interval. |
The coef()
method returns the vector of parameters of the model. If
bootstrap=TRUE
, then the coefficients are calculated as the mean values of the
bootstrapped ones.
The vcov()
method returns the covariance matrix of parameters. If
bootstrap=TRUE
, then the bootstrap is done using coefbootstrap
function
The confint()
constructs the confidence intervals for parameters. Once again,
this can be done using bootstrap=TRUE
.
Finally, the summary()
returns the table with parameters, their standard errors,
confidence intervals and general information about the model.
Depending on the used method, different values are returned.
Ivan Svetunkov, ivan@svetunkov.com
alm, coefbootstrap
# An example with ALM
ourModel <- alm(mpg~., mtcars, distribution="dlnorm")
coef(ourModel)
vcov(ourModel)
confint(ourModel)
summary(ourModel)
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