我在其他问题中建议使用OSX Yosemite和XQuartz,我一直试图发布一个笔记本,但每次都会得到同样的错误.这就是.R文件的样子:
#' ---
#' title: "MLB Payroll Analysis"
#' author: "Steven Quartz Universe"
#' date: "21 March 2015"
#' output: pdf_document
#' ---
#loading the payroll data from the Python document
payroll <- read.table("~/Documents/payroll.txt", header=TRUE, quote="\"")
View(payroll)
summary(payroll)
bank <- payroll$PayrollMillions
wins <- payroll$X2014Wins
#loading the payroll data from the Python document
payroll <- read.table("~/Documents/payroll.txt", header=TRUE, quote="\"")
summary(payroll)
bank <- payroll$PayrollMillions
wins <- payroll$X2014Wins
#displaying the mean and sd of payroll and wins (out of 162, of course)
mean(bank)
sd(bank)
mean(wins)
sd(wins)
#setting a linear regression
reg <- lm(wins ~ bank)
summary(reg)
#the regression is valid to significance < .10 (p-value .05072),
#but the R-squared is only .1296, a weak correlation
#a means of comparing the histogram to a normal distribution
histNorm <- function(x, densCol = "darkblue"){
m <- mean(x)
std <- sqrt(var(x))
h <- max(hist(x,plot=FALSE)$density)
d <- dnorm(x, mean=m, sd=std)
maxY <- max(h,d)
hist(x, prob=TRUE,
xlab="x", ylim=c(0, maxY),
main="(Probability) Histogram with Normal Density")
curve(dnorm(x, mean=m, sd=std),
col=densCol, lwd=2, add=TRUE)
}
#showing the histogram with normal distribution line
histNorm(reg$residuals, "purple")
#QQplots and Shapiro-Wilk test
qqnorm(reg$residuals)
qqline(reg$residuals)
shapiro.test(reg$residuals)
#p-value is .383; this can be considered a normal distribution
plot(reg$fitted.values,reg$residuals)
abline(h = 0)
#variances are wide, but in a channel
install.packages("lmtest")
library(lmtest)
bptest(reg)
#p-value of .849 given; we can assume variances are constant throughout the distribution
hats <- hatvalues(reg)
hatmu <- mean(hats)
hats[hats > 2 * hatmu]
#we get teams 14 and 19 with high leverage; the Dodgers and Yankees with their astronomical payrolls
treg <- rstudent(reg)
n <- length(treg)
p <- reg$coefficients
df <- n - p - 1
alpha <- 0.05
#no bonferroni correction for outliers
crit <- qt(1 - alpha/2,df)
treg[abs(treg) > crit]
#no outliers are found
#with bonferroni correction
crit <- qt(1 - (alpha/2)/n,df)
treg[abs(treg) > crit]
#no outliers are found
#comparison of outlier tests
pvals <- pt(-abs(treg),df)*2
padjb <- p.adjust(pvals, method = "bonferroni")
padjf <- p.adjust(pvals, method = "fdr")
cbind(pvals,padjb,padjf)
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当我点击编译笔记本时,这是输出:
|...................... | 33%
ordinary text without R code
|........................................... | 67%
label: unnamed-chunk-1
processing file: payroll.spin.Rmd
Quitting from lines 9-90 (payroll.spin.Rmd)
Error in contrib.url(repos, "source") :
trying to use CRAN without setting a mirror
Calls: <Anonymous> ... withVisible -> eval -> eval -> install.packages -> contrib.url
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我已经查看了有关如何纠正这个问题的其他问题,但无济于事.我已完成命令行修复,再次无济于事.有人能指出我做错了什么吗?谢天谢地.
Dom*_*ois 17
这条线
install.packages("lmtest")
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这是问题所在.正如错误消息所暗示的那样
Error in contrib.url(repos, "source") :
trying to use CRAN without setting a mirror
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期望您提供包裹的回购链接.所以改成它(例如):
install.packages("lmtest", repos = "http://cran.us.r-project.org")
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应该做的伎俩.但正如MrFlick和Ben Bolkers在他们的评论中指出的那样,应该在尚未安装软件包时完成.
我在Knit HTML发布时遇到了同样的问题,我修改了文件的最开头,如下所示:
---
title: "dialectic"
author: "micah smith"
date: "3/4/2017"
output: html_document
---
```{r setup, include=FALSE}
chooseCRANmirror(graphics=FALSE, ind=1)
knitr::opts_chunk$set(echo = TRUE)
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的chooseCRANmirror(graphics=FALSE, ind=1)
是,固定它的行
小智 5
chooseCRANmirror(graphics=FALSE, ind=1)
knitr::opts_chunk$set(echo = TRUE)
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如果您已经安装了该软件包,请将其写在块的开头。