Kk5. You estimate the following model.Dependent Variable: DRATEMethod: ARMA Conditional Least Squares (Gauss-Newton / Marquardtsteps)Date: 02/24/20 Time: 20:21Sample (adjusted): 1962M02 2019M07Included observations: 690 after adjustmentsFailure to Improve likelihood (non-zero gradients) after 11 iterationsCoefficient covariance computed using outer product of gradientsMA Backcast: 1962M01VariableCMA(1)R-squaredAdjusted R-squaredS.E. of regressionSum squared residLog likelihoodF-statisticProb(F-statistic)Inverted MA RootsO-0.002872O-0.002933O.0.439867Coefficient Std. Error t-StatisticO 0.261752-0.0028720.4398670.1338010.1325420.26175247.13757-53.21823106.27480.000000-440.014344-0.2002290.034251 12.84247Mean dependent varS.D. dependent varAkaike Info criterionSchwarz criterionHannan-Quinn criter.Durbin-Watson statProb.0.84140.0000The unconditional mean of the above process (from Eviews output above) is-0.0029330.2810380.1600530.1732030.1651392.088358

In ARMA conditional least squares, the unconditional mean of the process is the mean of dependent…

Answered: You estimate the following model.…

Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter7: Distance And Approximation

Section7.3: Least Squares Approximation

Problem 31EQ

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he scatter plot below shows the average cost of a designer jacket in a sample of years between 2000 and 2015. The least squares regression line modeling this data is given by yˆ=−4815+3.765x. A scatterplot has a horizontal axis labeled Year from 2005 to 2015 in increments of 5 and a vertical axis labeled Price ($) from 2660 to 2780 in increments of 20. The following points are plotted: (2003, 2736); (2004, 2715); (2007, 2675); (2009, 2719); (2013, 270). All coordinates are approximate. Interpret the y-intercept of the least squares regression line. Is it feasible? Select the correct answer below: The y-intercept is −4815, which is not feasible because a product cannot have a negative cost. The y-intercept is 3.765, which is not feasible because an expensive product such as a designer jacket cannot have such a low cost. The y-intercept is −4815, which is feasible because it is the value from the regression equation. The y-intercept is…
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