Give and simplify the regression equations of thefollowing ARIMA models of four Y time series.a. ARIMA(0, 1, 0)(0, 0, 1)4 without constantb. ARIMA(0, 0, 1)(0, 0, 1)4 without constantc. ARIMA(1, 1, 1)(0, 1, 0)4d. ARIMA(1, 1, 1)(1, 1, 1)4

The regression equation for the ARIMA model can be simplified as given below

Answered: Give and simplify the regression…

Algebra & Trigonometry with Analytic Geometry

13th Edition

ISBN:9781133382119

Author:Swokowski

Publisher:Swokowski

Chapter11: Topics From Analytic Geometry

Section11.4: Plane Curves And Parametric Equations

Problem 43E

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Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.
2. Suppose that in Example 2.27, 400 units of food A, 500 units of B, and 600 units of C are placed in the test tube each day and the data on daily food consumption by the bacteria (in units per day) are as shown in Table 2.7. How many bacteria of each strain can coexist in the test tube and consume all of the food? Table 2.7 Bacteria Strain I Bacteria Strain II Bacteria Strain III Food A 1 2 0 Food B 2 1 3 Food C 1 1 1
5. Consider the following two simple regression models: Model I : Y, = B,+B,X, +H, Model II : Y,=a, +a, (X,- X)+v, (1) Derive the estimators for B, and a,. Are they the same? (2) Derive the estimators for B, and a, . Are they the same?
(New Question) Consider the following regression equation with panel data: Yt = Bo + B1 Xt + y2 D2; + ys D3; + + Yn Dn; + uit Where X is our regressor of interest and D2; is a binary variable that equals to 1 when i=2 and O otherwise. Binary variables D3; ,. , Dn¡ are defined similarly. Which of the followings is not correct? O Assuming there's no other omitted variables, the OLS estimator for B1 is unbiased and consistent. O The equation should be estimated by OLS with clustered heteroskedasticity-robust standard errors. O The intercept for entity j (j + 1) is Vj. O The estimation of the above equation is only possible if n is not too large.
23) The values of the regression coefficients are found such the sum of the residuals is ___________.
1. (a) Show that the regression sum of squares can be written as n SSR = Σ(; - y)2 i=1 SSR S² STE
1. Consider the linear regression models. The p-values are shown in parentheses [5 points]. Model 1 Y = 123.2 +0.89X₂ R² = 0.600 Model 2 Model 3 (0.0005) (0.00001) Y = 40.1 +0.14X₂ + 0.61X3 (0.003) (0.008) (0.0004) Y=-1.7+2.57X₁-1.78X₂ (0.006) (0.04) (0.2) R² = 0.825 R² = 0.876 Where Y is the number of trips, X₁ is the total employment, X₂ is the industrial employment, Xs is the commercial employment. Choose the most appropriate model and explain why this model is selected as the most appropriate model. Hint: Consider both goodness-of-fit and coefficient significance.

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Give and simplify the regression equations of the following ARIMA models of four Y time series. a. ARIMA(0, 1, 0)(0, 0, 1)4 without constant b. ARIMA(0, 0, 1)(0, 0, 1)4 without constant c. ARIMA(1, 1, 1)(0, 1, 0)4 d. ARIMA(1, 1, 1)(1, 1, 1)4