Consider the following ARMA model for {y}:P+ Źay. +²+ ÉbeΣbetj=11=1y₁₂ = a₁ +where {} is the residual.Which of the following assumption(s) on the residuals {⁹} is needed to enable forecasting with this model in practice?O a. & is normally distributed.tIt-lO b. is mean-independent of y₁-11-2².. and &td. All of the above.t-1¹²1-2²...C. & and & are stochastically independent for all t‡ s.tS

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Answered: on the residuals {} is needed to enable…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Question 2. Show that, for a simple linear regression, R² = ry, where R² is the coefficient of determination and rxy is the sample correlation between Y and X. Hint: Σ" (Υ - Y)2 Σ1(Y₁-Y)²¹ SxY √SXXSYY' where Sxy = 1 (X; — X)(Y; — Y), Sxx = ₁1(X; - X)², Syy = ₁₁(Y₁ - Y)². R² = "XY =
1
You test some components with a Weibull distribution at temperatures of 100 Celcius and 60 Celcius. At those temperatures you estimate a characteristic life of 15000 hours and 25000 hours respectively. hint: Boltzmann's constant is k = 8.617 x 10-5. Temperature in Celcius + 273.15 = temperature in Kelvin. If n is an integer, T(n) = (n – 1) a) Using linear regression, estimate the Arrhenius model parameters A and AH. b) Give the MTTF, median, and 90th percentile at T = 20 Celcius. Assume that the shape parameter is 0.5
Plzz give the answer of all questions
Prove this statement "Regression models used for forecasting need not have a causal interpretation".?
The following Table summarizes the main estimation results for the below model: C- Bo + B,R + Balet E.where (C) denotes total household Consumption in SL, (R) is the national Incorme, and (1) denotes the Taxes collected from the private sector. The time span goes from 1974, 1st quarter, to 2010, 4th quarter and all the variables are expressed in million Rupees. Dependent variable C Constant R. Coefficient Sd. Eror t-statisties 128 40 3.2 0.90 0.48 0.67 6.0 32 0.15 0.15 R squared Residual Std. 1.35 Deviation Given the information in above table and the null that the Given the information in above table and the null that the Taxes collected from the private sector (B2) is not equal to zero, O a. There is not enough information to test this hypothesis. O b. The test statistic can be computed and the null is rejected in favor of the alternative hypothesis with a 5% significance. O . None cof the these O d. The test statistic can be computed and the null is not rejected in favor of the…
D. Only OLS assumption #2 is satisfied. The estimated regression is Y = 39+0.45X; Compute the estimated regression's prediction for the average score of students given 99, 129, or 155 minutes to complete the exam. Given 99 minutes, the estimated regression's prediction for the average score of students is Given 129 minutes, the estimated regression's prediction for the average score of students is Given 155 minutes, the estimated regression's prediction for the average score of students is (Round your responses to two decimal places.) Compute the estimated gain in score for a student who is given an additional 19 minutes on the exam. The estimated gain in score for a student who is given an additional 19 minutes on the exam is (Round your response to two decimal places.) Click to select your answer(s). W (DELL] o search PROU II
Suppose you obtain the following regression model, E[y]=91+79*x1 +20*x1*x2. What is the impact of a 39 unit change of x1 on the expected value of y when x2 is at its mean of 40?
7. a) What are residual plots and box plots? b) Do the stability analysis of the following model which is formulated to study the effect of toxicant on one competing species where the environmental toxicant concentration is being taken to change w.r.t. time. dN = rN, - α,Ν,N, - d,C,N , dt dN2 = rN, - α,N,., dt dCo = k,P - g,C, – m¡C, dt dP Q- hp – kPN, + gC,N . dt along with the initial conditions. N, (0) = N10,N2 (0)= N20,C, (0)= 0, P(0)= P, > 0 %3D Here, N1 (t) = Density of prey population
Suppose the analyst constructs the simple linear regression model In(y) = a + Bx+e. She estimates it to be In() = -1- 1.3x. What is the residual in Excel output for the pair of observations x= 1.5 and y = 27 O a. 6. O b. 1.98 O c. -2. O d. 403.43 e. 4.29
Suppose that n= 195 I.I.d. observations for (Y, X;) yleld the following regression results: v= 32.68 + 67.55Xx, SER= 18.63, R = 0.84 (15.7) (12.5) Another researcher is interested in the same regression, but he makes an error when he enters the data into the regression: He enters each observation twice, so he has 390 observations (with observation 1 entered twice, observation 2 entered twice, and so forth). Which of the following eatimated parameters change result? (Check all that apply) O A. The estimated intercept and slope. O B. The R of the regression. Yc. The standard error of the regrussion (SER). YD. The standard errors of the estimated coefficients. Using the 390 observations, what results will be produced by his regression program? Ý= 32.68 + 67.55X, SER =.R = 0.84 (Round your responses to two decimal places)
2

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on the residuals {} is needed to enable forecasting with this model in practice? 1¹-2... and e 1-1¹e1-2... ependent for all t# s.