Lecture 11, coding style etc.Rmd

---
title: "Lecture 11 coding styles, gotchas etc"
author: "David McAllister"
date: "31st October 2016"
output:
  slidy_presentation: default
---

## Objectives

- consider coding style as an issue
- discuss some gotchas
- talk about the help menu

## Coding style

- Write ugly difficult to understand code
- More difficult to do that in some languages such as python
- Read and be happy with a style
- https://google-styleguide.googlecode.com/svn/trunk/Rguide.xml

## Gotchas
- Missing values
- Dropping down to a different object type
- Forgetting quotes
- writing row/column numbers inadvertantly
- factors
- thinking a character vector is a double or integer vector


## Help menu, what it is
- Some help pages teach statistics and use of software
- R uses technical language and discusses software only
- Dense, but concise
- Vignettes and published papers
- Much help elsewhere quickR, stackoverflow, google (tricks)
![alt text](figures/rbooks2.png)

## Help menu, example 
glm is used to fit generalized linear models, specified by giving a symbolic description of the linear predictor and a description of the error distribution.

```{r, eval=FALSE}
## Dobson (1990) Page 93: Randomized Controlled Trial :
counts <- c(18,17,15,20,10,20,25,13,12)
outcome <- gl(3,1,9)
treatment <- gl(3,3)
print(d.AD <- data.frame(treatment, outcome, counts))
glm.D93 <- glm(counts ~ outcome + treatment, family = poisson())
anova(glm.D93); summary(glm.D93)
```
Look at examples, default arguments, values