My r-markdoun sudently stopped to work: when I knit a code into any type of document it doesen't produce any output instead of the titel of the document and the presetted code.
No error message is given.
Does anyone know what could be te problem?
can you provide a reproducible example (https://www.tidyverse.org/help/)? Or at least part of your rmd file?
title: "exercise 3"
knitr::opts_chunk$set(echo = TRUE) #b) library(rmarkdown) x <- c(0:20) d <- ppois(1:22, 1, sort) #we use a discrete distribution otherwise we'd have p=0 d_2 <- ppois(1:22, 5.5, sort) steps <- stepfun(x,d) steps_2 <- stepfun(x,d_2) plot(steps, main = "cdf for a Poisson distributed random variable ", col.points = "red") plot(steps_2, add=TRUE, col.points = "blue") axis(side=1, 1:20) m <- dpois(0:20, 1, sort) m_2 <- dpois(0:20, 5.5, sort) plot(x, m, type = "l", col="red", main = "pmf for a Poisson distributed random variable", ylab = "f(x)") par(new=TRUE) plot(x, m_2, type = "l", col="blue", ylab = "f(x)" ) axis(side=2) #When lambda increases, the shape of the pmf gets flatter, and the cdf moves right. #c) random_pois<-rpois(1000, 1) hist(random_pois) lines(density(random_pois), adjust = 2, col="red") random_p<-rpois(1000, 5.5) hist(random_p, prob=TRUE) lines(density(random_p), adjust = 2, col="red") #When m increases, the shape of the cdf and pmf get more similar to the one's in the case of Normal distribution. Infact, when m takes large values, the Poisson distribution aproximates the Gaussian distribution.
This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.
When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:
You can also embed plots, for example:
Note that the
echo = FALSE parameter was added to the code chunk to prevent printing of the R code that generated the plot.