Standard Group

Full Name

Brief Name

Short Description

Root Mean Squared Error

st_pen

Root Squared Error of Linear Loss scenarios calculated with Matrix of Scenarios or Expected Matrix of Products. By definition, it is an average of squared  loss scenarios.

Root Mean Squared Error Normal Independent

st_pen_ni

Root Squared Error of  Linear Loss with independent normally distributed random coefficients. It is calculated with Matrix of Means (one row matrix) and Matrix of Variances (one row matrix).

Root Mean Squared Error Normal Dependent

st_pen_nd

Root Squared 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.

Standard Risk

st_risk

(Standard Deviation of Linear Loss scenarios)+(Average of Linear Loss scenarios).  It is calculated with Matrix of Scenarios.

Standard Gain

st_risk_g

(Standard Deviation of Linear Loss scenarios)-(Average of Linear Loss scenarios).  It is calculated with Matrix of Scenarios.

Standard Risk Normal Independent

st_risk_ni

(Standard Deviation of Linear Loss)+(Average of Linear Loss).  It is calculated with Matrix of Means (one raw matrix) and Matrix of Variances (one row matrix).

Standard Gain Normal Independent

st_risk_ni_g

(Standard Deviation of Linear Loss)-(Average of Linear Loss).  It is calculated with Matrix of Means (one raw matrix) and Matrix of Variances (one row matrix).

Standard Risk Normal Dependent

st_risk_nd

(Standard Deviation of Linear Loss)+(Average of Linear Loss). It is calculated with Matrix of Means (one row matrix) and Covariance Symmetric Matrix.

Standard Gain Normal Dependent

st_risk_nd_g

(Standard Deviation of Linear Loss)-(Average of Linear Loss). It is calculated with Matrix of Means (one row matrix) and Covariance Symmetric Matrix.

Standard Deviation

st_dev

Standard Deviation of Linear Loss scenarios calculated with Matrix of Scenarios.

Mean Square Error

meansquare, meansquare_err

Mean Square of Linear Loss scenarios calculated with Matrix of Scenarios or Expected Matrix of Products.

Mean Square Error Normal Independent

meansquare_ni

Mean Square error of Linear  Loss with independent normally distributed random coefficients.   It is calculated with Matrix of Means (one row matrix) and Matrix of Variances (one row matrix).

Mean Square Error Normal Dependent

meansquare_nd

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.

Variance

variance

Variance of Linear Loss scenarios calculated with Matrix of Scenarios.

Root Squared Error Recourse

st_pen(recourse(.))

Root Squared Error of  Recourse scenarios. Recourse scenarios are obtained by solving LP at the second stage of two-stage stochastic programming problem for every scenario.

Standard Risk Recourse

st_risk(recourse(.))

(Standard Deviation of  Recourse scenarios)+(Average of Recourse scenarios). Recourse scenarios are obtained by solving LP at the second stage of two-stage stochastic programming problem for every scenario.

Standard Gain Recourse

st_risk_g(recourse(.))

(Standard Deviation of  Recourse scenarios)-(Average of Recourse scenarios). Recourse scenarios are obtained by solving LP at the second stage of two-stage stochastic programming problem for every scenario.

Standard Deviation Recourse

st_dev(recourse(.))

Standard Deviation of  Recourse scenarios. Recourse scenarios are obtained by solving LP at the second stage of two-stage stochastic programming problem for every scenario.

Meansquare Error Recourse

meansquare(recourse(.))

Meansquare error of Recourse scenarios. Recourse scenarios are obtained by solving LP at the second stage of two-stage stochastic programming problem for every scenario.

Variance Recourse

variance(recourse(.))

Variance of Recourse scenarios. Recourse scenarios are obtained by solving LP at the second stage of two-stage stochastic programming problem for every scenario.