Please see attached file10/22/2020 Final Project file:///C:/Users/leesu/Downloads/project.html 1/2...

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Please see attached file10/22/2020 Final Project file:///C:/Users/leesu/Downloads/project.html 1/2 Final Project Important: Please create your GitHub repository on the AU-R-Programming organization by Monday (Nov. 2nd 2020) at 2pm and use this repository to work on this assignment. Your final submission will be done via Canvas in a single html file (in which you will specify the name of the corresponding GitHub repository) and is due by Friday, Dec. 4th 2020 at 11.59pm (no late work is accepted). The version submitted on Canvas will have to correspond to the last version on the GitHub repository and you will receive zero points if you make modifications to your work after Dec. 4th 2020 at 11.59pm. The final project will be evaluated on 100 points and the goal is to develop an R package implementing linear regression as highlighted in Section 6.4 of the book (https://smac-group.github.io/ds/section- functions.html#section-example-continued-least-squares-function). The package must contain the basic functions to perform linear regression (e.g. estimate the coefficient vector ) and obtain different statistics from the procedure. Using the notation from the book and without using any of the linear regression functions already available in R (i.e. all outputs must be produced using formulas provided in the book and in this document), the basic outputs from the procedure must be the following: Confidence intervals: the user must be able to choose the significance level  to obtain for the  confidence intervals for  and whether to use the asymptotic or bootstrap approach for this. Plots (with e.g. ggplot2) including: 1. Residuals vs fitted-values (fitted values are ). 2. qq-plot of residuals 3. Histogram (or density) of residuals Mean Square Prediction Error (MSPE) computed in matrix form: where  is the number of observations in the data (i.e. number of rows). F-test: compute the statistic in matrix form and output the corresponding p-value. With  representing the sample mean of , let and  and . Then we can define  and   and obtain the F-statistic as follows: Using the appropriate distribution in R, compute  which corresponds to the p-value. Help documentation for all functions (for example using the roxygen2  package) β α 1 − α β = Xŷ β̂ MSPE := ( − 1 n ∑ i=1 n yi ŷ i) 2 n ȳ y SSM := ( − ,∑ i=1 n ŷ i ȳ) 2 SSE := ( − ,∑ i=1 n yi ŷ i) 2 DFM = p − 1 DFE = n − p MSM = SSM/DFM MSE = SSE/DFE = .F ∗ MSM MSE P (F > )F ∗ https://smac-group.github.io/ds/section-functions.html#section-example-continued-least-squares-function 10/22/2020 Final Project file:///C:/Users/leesu/Downloads/project.html 2/2 The package will be made available for download on a GitHub repository in the AU-R- Programming organization and the submission will be an html file on Canvas. The html file wil be a so-called vignette which indicates the name of the GitHub repository (and package) where you explain and give examples of how to use the package functions for all the desired outputs using one of the datasets on the Canvas course page. Up to 20 bonus points will be given for the final projects if other features are added for the package (e.g. a website with vignette, an example Shiny app that uses the package, the use of the Rcpp  package).

Naveen · Accepted Answer

Testing1/.Rbuildignore
^.*\.Rproj$
^\.Rproj\.user$
Testing1/.Rproj.user/E408E4C2/build_options
auto_roxygenize_for_build_and_reload="1"
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auto_roxygenize_for_check="1"
live_preview_website="1"
makefile_args=""
preview_website="1"
website_output_format="all"
Testing1/.Rproj.user/E408E4C2/cpp-definition-cache
[]
Testing1/.Rproj.user/E408E4C2/pcs/debug-breakpoints.pper
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Testing1/.Rproj.user/E408E4C2/pcs/files-pane.pper
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Testing1/.Rproj.user/E408E4C2/pcs/windowlayoutstate.pper
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Testing1/.Rproj.user/E408E4C2/pcs/workbench-pane.pper
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Testing1/.Rproj.user/E408E4C2/persistent-state
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build-last-errors-base-dir="F:/Projects/GreyNodes/69502/Testing1/"
build-last-outputs="[{"type":0,"output":"==> devtools::document(roclets = c('rd', 'collate', 'namespace'))\n\n"},{"type":2,"output":"Updating Testing1 documentation\r\n"},{"type":2,"output":"Loading Testing1\r\n"},{"type":1,"output":"Writing my_lm.Rd\r\nWriting my_qqplot.Rd\r\nWriting my_resid_fit.Rd\r\nWriting my_hist_resid.Rd\r\nWriting my_MSPE.Rd\r\nWriting my_F.Rd\r\n"},{"type":2,"output":"Warning: The existing 'NAMESPACE' file was not generated by roxygen2, and will not be overwritten.\r\n"},{"type":1,"output":"Documentation completed\n\n"},{"type":0,"output":"==> Rcmd.exe INSTALL --no-multiarch --with-keep.source Testing1\n\n"},{"type":1,"output":"* installing to library 'C:

10/22/2020 Final Project file:///C:/Users/leesu/Downloads/project.html 1/2 Final Project Important: Please create your GitHub repository on the AU-R-Programming organization by Monday (Nov. 2nd 2020)...

Answer To: 10/22/2020 Final Project file:///C:/Users/leesu/Downloads/project.html 1/2 Final Project Important:...

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