Consider the MA(1) model x5 wt 0.6W-1 with the w assumed to be jid N0,02). A....
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please provide the calculation
. Consider the following MA(1) model with the errors Et having having zero mean, unit variance and being serially uncorrelated. Yt = 0.2 + E +0.5&t-1 The value of the autocorrelation coefficient at lag 1 is: 0.5 0.25 0 0.4
1. Consider a moving average MA(2) model: y(t) = e(t) +belt-1) + b,elt-2) Assume that the noise e(t) has is i.i.d. with variance = 1. (a) Compute the autocorrelation process r(k) for y(t). (b) Compute the PSD of y(t). (Hint: 12.4 +e=24 = 2 cos(24)) (c) Plot the spectral density from part (b) for at least FOUR different combinations of (b1,b2), where b and b take either positive or negative values. (d) Comment on where the peaks of the PSD...
1. Three different metal alloys were tested for tensile strength. The strength of some examples of each alloy measured (in hundreds of megapascals), as follows. was Alloy Tensile strength of some examples 19.8 12.4 1 15.2 14.8 2 8.9 11.6 10.0 11.9 3 10.5 13.8 12.1 Source: the data come from Berenson and Levine (1998), Business Statistics: A First Course, p. 449, Question 10.27, but shortened.) Taking the types of alloy one-way ANOVA. The following R commands were used: as...
write MATLAB scripts to solve differential equations.
Computing 1: ELE1053 Project 3E:Solving Differential Equations Project Principle Objective: Write MATLAB scripts to solve differential equations. Implementation: MatLab is an ideal environment for solving differential equations. Differential equations are a vital tool used by engineers to model, study and make predictions about the behavior of complex systems. It not only allows you to solve complex equations and systems of equations it also allows you to easily present the solutions in graphical form....