Use R language Use R language Suppose we have the following small dataset: x <- c(30, 37, 38, 40, 50, 53, 57, 63, 67, 76) y <- c(18, 20.9, 19.4, 20.3, 19.8, 20.6, 19.5, 17.3, 15.2, 10.9) a. Plot the data. b. The triangular kernel with bandwidth h, centered at the location xo has the formula K((x-xo)/h) = 1- is zero outside this range. For a bandwidth of h = 10 and centered on xo = 55, find weights for all of the data values. c. Using the Nadaraya-Watson Kernel approach, use the weights to find an estimate of the true curve g(55). d. Find the variance of the estimate of g(55). I'll let you assume that = 0.5 and all data are independent. on the range x ±h, and
Use R language Use R language Suppose we have the following small dataset: x <- c(30, 37, 38, 40, 50, 53, 57, 63, 67, 76) y <- c(18, 20.9, 19.4, 20.3, 19.8, 20.6, 19.5, 17.3, 15.2, 10.9) a. Plot the data. b. The triangular kernel with bandwidth h, centered at the location xo has the formula K((x-xo)/h) = 1- is zero outside this range. For a bandwidth of h = 10 and centered on xo = 55, find weights for all of the data values. c. Using the Nadaraya-Watson Kernel approach, use the weights to find an estimate of the true curve g(55). d. Find the variance of the estimate of g(55). I'll let you assume that = 0.5 and all data are independent. on the range x ±h, and
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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Transcribed Image Text:Use R language Use R language
Suppose we have the following small dataset:
x <- c(30, 37, 38, 40, 50, 53, 57, 63, 67, 76)
y <- c(18, 20.9, 19.4, 20.3, 19.8, 20.6, 19.5, 17.3, 15.2, 10.9)
a. Plot the data.
b. The triangular kernel with bandwidth h, centered at the location xo has the formula K((x – xo)/h) = 1- | on the range xo +h, and
is zero outside this range. For a bandwidth of h = 10 and centered on xo = 55, find weights for all of the data values.
c. Using the Nadaraya-Watson Kernel approach, use the weights to find an estimate of the true curve g(55).
d. Find the variance of the estimate of g(55). I'll let you assume that o = 0.5 and all data are independent.
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