Exact(1)
Step change in R, increase in explained variance at the given step; adjusted R, R2 - (k - 1)/(n - k) × (1 - R), where n is the number of observations and k is the number of independent variables; β for final model, β value after all variables have been entered; P value, significance of final β value for the stated variable.
Similar(59)
chanexp : number for exponentiating the state variable; e.g. of the 2 state variables are varying.
The state variable of the master system synchronizes with an alternate state variable of the slave system.
Namely, the estimation algorithms use the observation matrix, the system matrix for the state variable and the crossvariance function between the state variable and the signal.
A distributed optimal control problem is considered with an inequality constraint on the state variable.
This paper considers a class of optimal control problems that allows jumps in the state variable.
Moreover the cutoff frequency of the state variable filter are also designed by GA.
For this second option, the state variable does not have a direct physical representation.
The disturbance observer estimated the disturbance and the state variable.
The current is dependent on the state variable itself.
We then index the state variable γ with time.
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