gradient_fun: Calculate the Gradient for Regression
In jtipton25/sgMRA: Multi-Resolution Gaussian Process Approximations with Stochastic Gradient Descent
gradient_fun R Documentation
Calculate the Gradient for Regression
Description
Calculate the Gradient for Regression
Usage
gradient_fun(y, tXy, tXX, beta)
Arguments
y
A vector of observations
tXy
A vector of the transpose of design matrix X times the output data y
tXX
A matrix of the transpose of design matrix X times the design matrix X
beta
A vector of regression parameters
Value
The gradient vector
jtipton25/sgMRA documentation built on Feb. 9, 2023, 4:53 a.m.
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| gradient_fun | R Documentation |
Calculate the Gradient for Regression
Description
Calculate the Gradient for Regression
Usage
gradient_fun(y, tXy, tXX, beta)
Arguments
y |
A vector of observations |
tXy |
A vector of the transpose of design matrix X times the output data y |
tXX |
A matrix of the transpose of design matrix X times the design matrix X |
beta |
A vector of regression parameters |
Value
The gradient vector
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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