norm_errors: Generate heteroskedastic Gaussian errors based on the norm of...
In Yu-Group/dgpoix: Generate synthetic data that is as fresh as the real thing
View source: R/dgp-lib-errors.R
norm_errors R Documentation
Generate heteroskedastic Gaussian errors based on the norm of X.
Description
Generate independent Gaussian errors with variance proportional
to norm of row observations in the data matrix X. That is,
epsilon_i ~ N(0, scale * ||x_i||_2^2).
Usage
norm_errors(X, scale = 1)
Arguments
X
Data matrix or data frame.
scale
Multiplicative scale factor.
Value
A vector of simulated errors with length n.
Examples
errs <- norm_errors(X = iris %>% dplyr::select(-Species))
Yu-Group/dgpoix documentation built on June 3, 2022, 1:40 a.m.
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View source: R/dgp-lib-errors.R
| norm_errors | R Documentation |
Generate heteroskedastic Gaussian errors based on the norm of X.
Description
Generate independent Gaussian errors with variance proportional to norm of row observations in the data matrix X. That is, epsilon_i ~ N(0, scale * ||x_i||_2^2).
Usage
norm_errors(X, scale = 1)
Arguments
X |
Data matrix or data frame. |
scale |
Multiplicative scale factor. |
Value
A vector of simulated errors with length n.
Examples
errs <- norm_errors(X = iris %>% dplyr::select(-Species))
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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