which are core assumptions of a linear programming model? a-linearity, b-homoscedasticity, 3-stochastic parameters or 4- a...
Define: a. Model, Variables, Parameters b. Constraints in linear programming c. Mathematical relationships known with certainty and probabilistic conditions(risk model)
Which of the following components of a linear programming model is the overall performance measure? Multiple Choice O Constraints Decision variables O Parameters Objective
Model Assumptions: Question: • Assumption MLR.1 (Linear in the Parameters): The model in the population can be written as y = Bo + B1X + ... + BkXk+u where Bo, B1, ..., Bk are the unknown parameters of interest and u unobserved random error. Assumption MLR.2 (Random Sampling): We have a random samp n observations, {(Xi1, X12, ..., Xik, Yi) : 1 = 1,2,...,n}, following the population model in Assumption MLR.1. Assumption MLR.3 (No Perfect Collinearity): In the sample, none...
Question 20 (4 points) 2X, +X, E3 3x,+ ider the following linear programming model: Max: 4x,+2X2 +X, Subject to: 2E1 X X0 What is causing this problem to violate one of the properties or asumptions for curvilinear proportionality indivisiblilty linearity
Which of the following is NOT true about linear programming problems: When dealing with extremely complex real problems, there is no such thing as the perfectly correct linear programming model for the problem Approximations and simplifying assumptions generally are required to have a workable linear programming model Linear programming problems can be formulated both algebraically as a mathematical model and on spreadsheets None of the answers are accurate
c) Which theorem gives th (a) State the OLS assumptions in a simple linear regression model. (3) b] How do you modify the OLS assumptions if you have a control variable? (2) (c) Discuss the problem of omitted variable bias. (5)
1. Consider the following linear regression model: (a) Which assumptions are needed to make the B, unbiased estimators for the B, (b) Explain how one can test the hypothesis that A +As = 0 by means of a t-test. (c) Explain how one can test the hypothesis that A-A-0. Indicate the relevant test statistic. (d) Suppose that ri is an irrelevant explanatory variable in the population model and that you estimate the model including both and r2. What are the...
Which of the following mathematical relationships could be found in a linear programming model? Choose YES if the relationship could be, and NO if it could not.A. YES B. NO 1. B-2A + 7B = 45 2. 4A - B ¡Ü 103. A + 2B ¡Ý 224. 3A + 2B - AB = 125. 2A2 - 8B ¡Ý 14
Problem 3. Use Robust optimization to reformulate the following uncertain linear programming problem to a deterministic linear programming model. Maximize Z-5xr+cx2tcar Subject to aiuxi-3x2+2x3Sb 2x1-4x2+a3320 and xl, x2, x320 The estimates and ranges of uncertainty for the uncertain parameters are shown below. Parameter a11 422 a33 bi b2 C2 C3 Range of Uncertainty 3.6-4.4 1.4 to-1.6 2.5-3.5 27-33 19-22 9 to-7 3-5 Estimate 4 -1 30 20 -8 4 Problem 3. Use Robust optimization to reformulate the following uncertain linear...
A regression model that is linear in the unknown parameters is a linear regression model. A) True B) False The test for significance of regression in multiple regression involves testing the hypotheses Ho: B1=B2=B3=0 versus H1: B1≠B2≠B3≠0. A) True B) False The ANOVA is used to test for significance of regression in multiple regression. A) True B) False