Brian Albert Monroe
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|.Rbuildignore||4 years ago|
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|DESCRIPTION||2 years ago|
|NAMESPACE||2 years ago|
|README.md||2 years ago|
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Maximum Likelihood Estimation for Choice Under Risk
This package provides functions to directly estimate risk and time preferences, a generic function to do any maximum likelihood estimate, and delta method function to do non-linear wald tests.
The risk and time preference estimation functions were the initial purpose of this package and may either be expanded or cut off into a new package in the future.
The generic "top_llfun" function to do maximum likelihood estimation allows for clustering of standard errors and parameters to be made linear functions of observable covariates.
The delta methods were derived because the nlWaldtest package didn't allow for arbitrary functional transformations of parameters. The delta methods are provided here because they are most useful when combined with the results from the top_llfun, but can be used for any set of estimates and covariance matrix.
- Allow for parameters to be made linear functions of observable covariates.
- Create generic function to use in other packages so work isn't duplicated elsewhere.
- Create API to allow users to add any optimizer
- Progress has been made here, but not finished
- Create API to allow users to provide arbitrary parameter transformations.
- New delta methods provide a piece of this goal.
Optimizer Methods to Implement