The main difference between linear (LP) and nonlinear programming problems (NLP) is that a. No interaction terms
Question:
The main difference between linear (LP) and nonlinear programming problems (NLP) is that
a. | No interaction terms are allowed in NLP | |
b. | NLP must have a nonlinear objective function | |
c. | Only one constraint in NLP can be nonlinear | |
d. | Some constraints in NLP may be nonlinear |
The standard prediction error is
a. | always smaller than the standard error. | |
b. | used to construct confidence intervals for predicted values. | |
c. | measures the variability in the predicted values. | |
d. | all of these. |
The GRG algorithm terminates when it
a. | has reached the global optimal solution. | |
b. | has completed 100 iterations. | |
c. | when it detects no feasible direction for improvement. | |
d. | when it reaches the steepest gradient. |
The regression function indicates the
a. | average value the dependent variable assumes for a given value of the independent variable. | |
b. | average value the dependent variable assumes for a given value of the dependent variable | |
c. | actual value the dependent variable assumes for a given value of the independent variable | |
d. | actual value the independent variable assumes for a given value of the dependent variable |
Which of the following is an advantage of using the TREND() function versus the regression tool?
a. | The TREND() function handles multiple dependent variable data. | |
b. | The TREND() function does not use a least squares regression line. | |
c. | The TREND() function provides more statistical information. | |
d. | The TREND() function is dynamically updated when input to the function changes. |