algo_leverage: Algorithmic Leveraging Function
In xyzou685/STSCI6520_HW2: HW2
Usage
1
algo_leverage(xi, yi, r = floor(0.2 * length(yi)))
Arguments
xi
independent variables
yi
response variable
r
the sampling size,default=20
beta,the estimated regression coefficients
implements algorithmic leveraging for linear regression using uniform and leverage score based on subsampling of rows
x <- matrix(rnorm(500),100,5)
y <- x%*%rep(-1,5)+rnorm(100)
algo_leverage(x,y)
xyzou685/STSCI6520_HW2 documentation built on June 6, 2019, 2:29 p.m.
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Usage
1 | algo_leverage(xi, yi, r = floor(0.2 * length(yi)))
|
Arguments
xi |
independent variables |
yi |
response variable |
r |
the sampling size,default=20 |
beta,the estimated regression coefficients implements algorithmic leveraging for linear regression using uniform and leverage score based on subsampling of rows x <- matrix(rnorm(500),100,5) y <- x%*%rep(-1,5)+rnorm(100) algo_leverage(x,y)
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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