algo_leverage: Subsampling regression methods
In sophiaycl/6520HW2: STSCI6520HW
Description
Usage
Arguments
Value
Examples
Description
Implements algorithmic leveraging for linear regression using uniform or
leverage score based subsampling of rows, i.e, fit y = X beta + E.
Usage
1
2
algo_leverage(X, y, samplePct = 0.1, sampSize = floor(samplePct *
length(y)), sampleType = "Lev")
Arguments
X
The covariates matrix
y
The response vector
samplePct
The percentage of subsamples
sampSize
Number of subsamples
sampleType
The type of subsampling rows
Value
The coefficient vector beta.
Examples
1
algo_leverage(matrix(rnorm(1000), nrow = 100), rnorm(100), sampleType = 'Unif')
sophiaycl/6520HW2 documentation built on June 6, 2019, 8:36 p.m.
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Description Usage Arguments Value Examples
Description
Implements algorithmic leveraging for linear regression using uniform or
leverage score based subsampling of rows, i.e, fit y = X beta + E.
Usage
1 2 | algo_leverage(X, y, samplePct = 0.1, sampSize = floor(samplePct *
length(y)), sampleType = "Lev")
|
Arguments
X |
The covariates matrix |
y |
The response vector |
samplePct |
The percentage of subsamples |
sampSize |
Number of subsamples |
sampleType |
The type of subsampling rows |
Value
The coefficient vector beta.
Examples
1 | algo_leverage(matrix(rnorm(1000), nrow = 100), rnorm(100), sampleType = 'Unif')
|
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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