mean_squared_error: Evaluates the mean square error loss function of a linear...
In cgaillac/MarginalFElogit: Estimation of Average Marginal Effects in Fixed Effect Logit Models
View source: R/mean_squared_error.R
mean_squared_error R Documentation
Evaluates the mean square error loss function of a linear regression.
Description
Evaluates the mean square error loss function of a linear regression.
Usage
mean_squared_error(beta, X, Y)
Arguments
beta
a vector of size dimX, the value at which the loss is computed
(i.e. we predict Y using X'beta)
X
an array of size n x Tmax x dimX containing the values of the covariates X
Y
a matrix of size n x Tmax containing the values of the dependent variable Y
Value
the value of the mean squared error loss function of the linear regression at beta
cgaillac/MarginalFElogit documentation built on Dec. 24, 2024, 3:23 p.m.
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View source: R/mean_squared_error.R
| mean_squared_error | R Documentation |
Evaluates the mean square error loss function of a linear regression.
Description
Evaluates the mean square error loss function of a linear regression.
Usage
mean_squared_error(beta, X, Y)
Arguments
beta |
a vector of size dimX, the value at which the loss is computed (i.e. we predict Y using X'beta) |
X |
an array of size n x Tmax x dimX containing the values of the covariates X |
Y |
a matrix of size n x Tmax containing the values of the dependent variable Y |
Value
the value of the mean squared error loss function of the linear regression at beta
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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