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- How does the particle used in FastSLAM differ from the one used in Monte Carlo localization?What is the value of Y if C = 200, a = 20, and b = 0.9?All questions utilize the multivariate demand function for Smooth Sailing sailboats in C6 on text page 83. Compute to three decimal places. Initial values are: PX = $9500 PY = $10000 I = $15000 A = $170000 W = 160 This function is: Qs = 89830 -40PS +20PX +15PY +2I +.001A +10W 1.(a). Use the above to calculate the arc price elasticity of demand between PS = $9000 decreasing to PS = $8000. The arc elasticity formula is: 1.(b). Judging from the computation in (a), do you expect the revenue resulting from the decrease in Ps to $8000 to increase, remain the same, or decrease relative to the revenue at Ps = $9000. (Hint: see the table on page 65 of Truett). Explain your choice. 1.(c). Calculate the point elasticity of demand for Smooth Sailing sailboats at PS = $9000 (which should make Qs = 101600). The formula is: 1.(d). Does this elasticity value indicate that Smooth Sailing demand is relatively responsive to changes in the price of these sailboats? Explain…
- π = 10kl - k²1² +1 dk 5 dn dk - dπ dk dπ dk Find and dπ dl dπ = : 100 - 10kl + and = 1012kl² and = 10l-2kl² and dl dπ dl dπ dl dπ = = 100-10lk² 10k 2lk²+1 - = 10k - 2lk²Solve for x for the following equation: 4ln(3x-8) = 60The height (in inches) of a random sample of 28 players in NCAA Division 1 basketball teams is shown to the left. x 75 80 75 87 77 77 67 83 77 80 73 82 73 71 80 76 72 78 68 74 74 72 76 86 77 77 78 5 Sum of squared x minus n times squared mean: ∑x² − nx̅² =_____ a 590.74 b 582.01 c 573.41 d 564.94
- Use General Linear Proce ss to determine the Emean functon and ARC2) given the autocovariance function of ky XE 七ート 2ヒー2X(t) is a wide sense stationary stochastic process with autocorrelation function sin(271000r) R„(T)=10- 271000r The process Y(t) is a version of X(t) delayed by 50 micro seconds. {Y(t) = X(t - t0)} (a) Derive the autocorrelation function of Y (t). (b) Derive the cross-correlation function of X(t) and Y (t). (c) Are X(t) and Y (t) jointly wide sense stationary? IUnloaded File Details4. The estimation of the model with quarterly car sales in the U.S. from 1975 to 1990 gives: Source | df MS Number of obs = 64 F( 2, Prob > F 61) = 12.21 Model .32720224 2 .16360112 0.0000 Residual | .817286587 61 .013398141 R-squared Adj R-squared = 0.2625 Root MSE 0.2859 Total | 1.14448883 63 .018166489 .11575 lqne | cCoef. t P>|t| std. Err. [95% Conf. Interval] 1price lincome -.4604611 3.37186 6.89398 -.8280926 .1838504 -4.50 0.000 -1.195724 2.399991 . 4860261 4.94 0.000 1.428121 _cons 5.92543 .4843662 12.23 0.000 4.95688 Based on the parameter estimates, what is the predicted effect of a 10% increase in price on the number of cars sold? What would be the effect of that price increase on the value of car sales?