score_rank: Numerical Rank of the Entity-Level Score Matrix
In badp: Bayesian Averaging for Dynamic Panels
score_rank R Documentation
Numerical Rank of the Entity-Level Score Matrix
Description
The sandwich covariance uses J = G'G, where the rows of G are
the entity-level score vectors. At the maximum the rows of G sum to
zero, so J is unchanged by centering them and its rank is the rank of
the centered matrix: only the variation across entities of the scores
contributes. Parameters that enter the log-likelihood solely through terms
common to every entity have no such variation and contribute nothing,
whatever the number of entities.
Usage
score_rank(Gmat)
Arguments
Gmat
Matrix of entity-level scores, one row per entity.
Value
Integer, the numerical rank.
badp documentation built on Sept. 15, 2026, 1:08 a.m.
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| score_rank | R Documentation |
Numerical Rank of the Entity-Level Score Matrix
Description
The sandwich covariance uses J = G'G, where the rows of G are
the entity-level score vectors. At the maximum the rows of G sum to
zero, so J is unchanged by centering them and its rank is the rank of
the centered matrix: only the variation across entities of the scores
contributes. Parameters that enter the log-likelihood solely through terms
common to every entity have no such variation and contribute nothing,
whatever the number of entities.
Usage
score_rank(Gmat)
Arguments
Gmat |
Matrix of entity-level scores, one row per entity. |
Value
Integer, the numerical rank.
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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