lse.beta: Compute the least squares estimate on a given index set
In tilting: Variable Selection via Tilted Correlation Screening Algorithm
Description
Usage
Arguments
Value
Author(s)
Description
The function returns an estimate of the coefficient vector for a linear regression problem by setting the coefficients corresponding to a given index set to be the least squares estimate and the rest to be equal to zero.
Usage
1
Arguments
X
design matrix.
y
response vector.
active
the index set on which the least squares estimate is computed.
Value
An estimate of the coefficient vector is returned as above.
If active==NULL, a vector of zeros is returned.
Author(s)
Haeran Cho
tilting documentation built on May 2, 2019, 8:53 a.m.
R Package Documentation
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Description Usage Arguments Value Author(s)
Description
The function returns an estimate of the coefficient vector for a linear regression problem by setting the coefficients corresponding to a given index set to be the least squares estimate and the rest to be equal to zero.
Usage
1 |
Arguments
X |
design matrix. |
y |
response vector. |
active |
the index set on which the least squares estimate is computed. |
Value
An estimate of the coefficient vector is returned as above. If active==NULL, a vector of zeros is returned.
Author(s)
Haeran Cho
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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