Error when knitting to a PDF

Error message in R:
Error in cv.glmnet(x[train, ], y[train], alpha = 0) :
could not find function "cv.glmnet"
Calls: ... handle -> withCallingHandlers -> withVisible -> eval -> eval
In addition: Warning messages:
1: package 'knitr' was built under R version 3.6.3
2: package 'ISLR' was built under R version 3.6.3
3: In block_exec(params) :
Failed to tidy R code in chunk 'unnamed-chunk-2'. Reason:
Error in loadNamespace(name) : there is no package called 'formatR'

4: In block_exec(params) :
Failed to tidy R code in chunk 'unnamed-chunk-3'. Reason:
Error in loadNamespace(name) : there is no package called 'formatR'

5: In block_exec(params) :
Failed to tidy R code in chunk 'unnamed-chunk-4'. Reason:
Error in loadNamespace(name) : there is no package called 'formatR'

Execution halted


title: "HW3"
author:
- Me
header-includes:

  • \usepackage{bbm}
  • \usepackage{amssymb}
  • \usepackage{amsmath}
  • \usepackage{graphicx}
  • \usepackage{natbib}
  • \usepackage{float}
  • \floatplacement{figure}{H}
    output:
    pdf_document: default
    fontsize: 11pt

library(knitr); library(ISLR)

opts_chunk$set(tidy.opts=list(width.cutoff=60),tidy=TRUE)

1. Exercise 9(a), 9(b), 9(c), 9(d) and 9(g) in Section 6.8 of the Text. Please run set.seed(1) before you run any other codes, so that your results are reproducible for grading. Please answer 9(g) with respect to the results obtained in 9(a), 9(b), 9(c) and 9(d). The College data set is in the library ISLR

set.seed(1)
data(College)
n = 1:nrow(College)

train = sample(n, 777*.7)
index = n[-train]

test = sample(index, 777*.3)

train_set = College[train, ]
test_set = College[test, ]
summary(College)
lm.fit = lm(Apps~., data = train_set)

p = predict(lm.fit, test_set)

MSE = mean((p - test_set$Apps)^2)
MSE
x=model.matrix(Apps~.,College)[,-1]
y=College$Apps

set.seed(1)
train=sample(1:nrow(x), nrow(x)/2)

test=(-train)

y.test=y[test]

cv.out=cv.glmnet(x[train,],y[train],alpha=0)

plot(cv.out)

bestlam=cv.out$lambda.min
bestlam

ridge.pred=predict(ridge.mod,s=bestlam,newx=x[test,])

MSE = mean((ridge.pred-y.test)^2)

out=glmnet(x,y,alpha=0)

predict(out,type="coefficients",s=bestlam)[1:18,]

MSE
lasso.mod=glmnet(x[train,],y[train],alpha=1,lambda=grid)

plot(lasso.mod)

set.seed(1)
cv.out=cv.glmnet(x[train,],y[train],alpha=1)

plot(cv.out)

bestlam=cv.out$lambda.min

lasso.pred=predict(lasso.mod,s=bestlam,newx=x[test,])

MSE = mean((lasso.pred-y.test)^2)
MSE

out=glmnet(x,y,alpha=1,lambda=grid)

lasso.coef=predict(out,type="coefficients",s=bestlam)[1:18,]

lasso.coef

lasso.coef[lasso.coef!=0]

try installing the package formatR and then running library(formatR)

1 Like

Indeed, you need the formatR :package: for this to work. No need to call library(formatR) though.

Have you loaded the package where this function lives ?