Explain the FGLS (Feasible Generalized Least Squares) method and how we can apply it step by step. The following notation is suggested :V(u) =σ2Ω(explain what areσandΩ). Then how do we interpret it?
ECONOMETRICS
Generalized least squares(GLS) is a method for estimating the unknown parameters in a linear regression model when there is a certain degree of correlation between the residuals in a regression model.
If the covariance of the errors
f the covariance of the errors
is unknown, we can get a consistent estimate of
,
using an implementable version of GLS known as the feasible
generalized least squares (FGLS) estimator.
In FGLS, modeling proceeds in two stages:
(1) the model is estimated by OLS or another consistent (but inefficient) estimator, and the residuals are used to build a consistent estimator of the errors covariance matrix
(2) using the consistent estimator of the covariance matrix of the errors, one can implement GLS ideas.
is a non-singular covariance matrix and σ2 is a variance of the
error term.
V(u) =σ2Ω is the consistent estimator of the variance term.
Explain the FGLS (Feasible Generalized Least Squares) method and how we can apply it step by step. The following notatio...
In the class, we discussed the generalized least squares approximation for higher-order (see example below). In this homework problem, you will need to (1) Repeat the example by preparing a Matlab code. That is, the code will first read the x and y vectors and then call (your) function to calculate a of the polynomial. (2) Calculate the standard deviation. Least Squares Approximation-higher-degree Example: Find the LS polynomial of degree three (3) that fits the following data in the table...
Suppose we developed the following least squares regression equation: can we conclude? What The dependent variable increases 3.5 for each unit increase in X.! The equation crosses the Y-axis at 2.1. If X= 5, then is 14. There is a significant positive relationship between the dependent and independent variables.
Please step by step solution!!!
Cholesky factorization versus QR factorization. In this problem we compare the accuracy of the two methods for solving a least-squares problem minimize Ar - b We take b10- 1-10-k ke A10 0 10k for k 6, k- 7 and k 8. (a) Write the normal equations, and solve them analytically (i.e., on paper, without using MATLAB). (b) Solve the least-squares problem in MATLAB, for k = 6. K-7 and k = 8, using the recommended...
we use the form y a + bx for the least-squares line. In some computer printouts, the least-squares equation is not given directly. Instead, the value of the constant a is given, and the coefficient b of the explanatory or predictor variable is displayed. Sometimes a is referred to as the constant, and sometimes as the intercept. Data from a report showed the following relationship between elevation (in thousands of feet) and average number of frost-free days per year in...
1. How does sweeping meshing method work? Can all bodies be meshed using this method? Explain. 2. How does multizone meshing method works? 3. What is skewness as a measure of mesh quality? 4. Explain stress stiffening effect. 5. What is buckling and why do we need to perform buckling or stability analysis? 6. What is a load multiplier provided as a result of buckling analysis? Explain with examples. 7. What are buckling modes and how to interpret them? Explain...
can someone explain this step
by step? especially don't understand how they got m/px? why we
can't use the lagrange. and not sure how they drew the graph for
this question. SOMEONE PLEASE HELP MIDTERM SOON AND WILL GIVE BIG
THUMBS UP!!!! confused where 4x20+5x0 is coming from
Problem 4 Eric's preferences for goods x and y are represented by the following utility function: U(X,Y) = 4X +5Y. The price of good X is px = 2 and the price...
3. (25 pts) Consider the data points: t y 0 1.20 1 1.16 2 2.34 3 6.08 ake a least squares fitting of these data using the model yü)- Be + Be-. Suppose we want to m (a) Explain how you would compute the parameters β | 1 . Namely, if β is the least squares solution of the system Χβ y, what are the matrix X and the right-hand side vector y? what quantity does such β minimize? (b)...
can
you please explain how we solved for V1 and V2 step by step?
Tev Sale -B ۱۷= ا KCL at vi 60, + 15 (vi-uz) + s(v.- l o o 90k 26v, 1502-520 264,- 15%2=5 to KeL at vi 12V2 + 14 la-V) + (0-1) . suk -luv, +33 V2 = 7 - + sowe o V = 0.4167 V2 = 0.3889 KCL at us: Is + Us + Us V2 = 0 18 Is - 04167+ - 0.3889...
Please explain your answer
Suppose that we use least-squares to fit a polynomial trend to this time series. Figure 4 displays the original time series plot along with the fitted values. Time Series and Polynomial Fit of the Trend 10 15 Time Figure 4 Which of the following characteristics is the model able to capture? Trend Seasonality Trend and seasonality Seasonality and heteroskedasticity
Please explain your answer
Suppose that we use least-squares to fit a seasonal-means trend to this time series. Figure 3 displays the original time series plot along wtih the fitted values. Time Series and Seasonal-Means Fit 10 15 Time Figure 3 Which of the following characteristics is the model able to capture? Trend Seasonality ● Trend and seasonality Seasonality and heteroskedasticity