(30pts total) This problem involves the Boston housing dataset BostonHousing in the R package mlbench. The...
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(30pts total) This problem involves the Boston housing dataset BostonHousing in the R package mlbench. The goal is to predict per capita crime rate using the other variables in this dataset. In other words, per capital crime rate is the response, and the other variables are the predictors. You need to write your own R function called my. 1m () to get the parameter estimates. In your function, you need to compute the parameter estimates of the regression coefficients 3 using least squares methods and compute the mean squared error (MSE) as an unbiased estimator of o2. Verify your results (i.e., parameter estimates) with the output from 1m(), and you do not need to replicate the output from 1m () with your function my.1m (). (30pts total) This problem involves the Boston housing dataset BostonHousing in the R package mlbench. The goal is to predict per capita crime rate using the other variables in this dataset. In other words, per capital crime rate is the response, and the other variables are the predictors. You need to write your own R function called my. 1m () to get the parameter estimates. In your function, you need to compute the parameter estimates of the regression coefficients 3 using least squares methods and compute the mean squared error (MSE) as an unbiased estimator of o2. Verify your results (i.e., parameter estimates) with the output from 1m(), and you do not need to replicate the output from 1m () with your function my.1m ().
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Related Book For
Business Statistics For Contemporary Decision Making
ISBN: 978-1118749647
8th edition
Authors: Black Ken
Posted Date:
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(30pts total) This problem involves the Boston housing dataset BostonHousing in the R package mlbench. The goal is to predict per capita crime rate using the other variables in this dataset. In other...
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