ReducedRankRegressions: Construct a poset of reduced rank regression models.
In Lucaweihs/sBIC: Computing the Singular BIC for Multiple Models
Description
Creates an object representing a collection of reduced rank regression
models. There is one model for each fixed rank from 1 to some specified
maximum. In particular each model is identified by a single number
specifiying the rank of the regression matrix in the model. Models are
naturally ordered by inclusion so that, for example, a model with 2
rank 2 comes before before a model with rank 3 or greater.
Arguments
numResponses
the number of response variables.
numCovariates
the number of covariates.
maxRank
the largest rank model to be included in the collection.
Value
An object representing the collection.
Lucaweihs/sBIC documentation built on May 9, 2019, 10:07 a.m.
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Description
Creates an object representing a collection of reduced rank regression models. There is one model for each fixed rank from 1 to some specified maximum. In particular each model is identified by a single number specifiying the rank of the regression matrix in the model. Models are naturally ordered by inclusion so that, for example, a model with 2 rank 2 comes before before a model with rank 3 or greater.
Arguments
numResponses |
the number of response variables. |
numCovariates |
the number of covariates. |
maxRank |
the largest rank model to be included in the collection. |
Value
An object representing the collection.
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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