summary.gpls: Summary method for gpls models
In abnormally-distributed/cvreg: Cross Validation and Robust Estimation Utilities
Description
Usage
Arguments
Value
Description
Summary method for gpls models
Usage
1
2
## S3 method for class 'gpls'
summary(model, se.type = "HC4m")
Arguments
model
a fitted model object
se.type
One of the robust standard error methods described in vcovHC.gpls. This defaults
to the HC4m method, which I have found to give the most accurate results. Note that typical standard errors are
not available for partial least squares. Another option to HC standard errors is to utilize the boot package to bootstrap
standard errors.
Value
a summary
abnormally-distributed/cvreg documentation built on May 3, 2020, 3:45 p.m.
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Description Usage Arguments Value
Description
Summary method for gpls models
Usage
1 2 | ## S3 method for class 'gpls'
summary(model, se.type = "HC4m")
|
Arguments
model |
a fitted model object |
se.type |
One of the robust standard error methods described in vcovHC.gpls. This defaults to the HC4m method, which I have found to give the most accurate results. Note that typical standard errors are not available for partial least squares. Another option to HC standard errors is to utilize the boot package to bootstrap standard errors. |
Value
a summary
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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