Mean Square Error Normal Dependent (meansquare_nd_err)
Contents
Mean Square Error Normal Dependent. Mean Square error of Linear Loss with mutually dependent normally distributed random coefficients. It is calculated with Matrix of Means (one row matrix) and Covariance Symmetric Matrix
Syntax
meansquare_nd_err(matrix_mn,matrix_cov) |
short call; |
meansquare_nd_err_name(matrix_mn,matrix_cov) |
call with optional name. |
Parameters
matrix_mn is a PSG matrix of mean values:
where the header row contains names of variables. The second row contains numerical data.
matrix_cov is a PSG matrix of covariance values:
where the header row contains names of variables. Other rows contain numerical data.
Output
When function Mean Square Error Normal Dependent is used in optimization or calculation problems PSG automatically calculates and includes in the solution report two outputs:
pseudo_R2_function_name |
|
contributions(function_name) |
Mathematical Definition
Mean Square Error Normal Dependent function is calculated as follows:
,
where
is a mean of the loss function,
is a variance of the loss function,
is Loss Function (See section Loss and Gain Functions);
is an argument of function.
Example
See also
Mean Absolute Error, Mean Absolute Error Normal Independent, Mean Absolute Error Normal Dependent, Mean Square Error, Mean Square Error Normal Independent , Root Mean Squared Error, Root Mean Squared Error Normal Independent, Root Mean Squared Error Normal Dependent, Koenker and Basset Error, Rockafellar Error