The use of install_github() from the devtools package allows quick cross platform package building and installation. Documenting all functions correctly is quite tedious, so this quick test package has minimal documentation. However this looks like a useful way of providing functions for use on courses.
The printr package allows help files to be printed in a compiled document, among other things. Looks very useful. http://yihui.name/printr/
So install this first from the yihui github repository.
library(devtools)
install_github("yihui/printr")
library(printr)
Now install my little test package “qecol”.
install_github("dgolicher/qecol")
## Downloading github repo dgolicher/qecol@master
## Installing qecol
## '/usr/lib/R/bin/R' --vanilla CMD INSTALL \
## '/tmp/RtmpMXfs23/devtools6ff08e15fc1/dgolicher-qecol-07a4ad4' \
## --library='/home/duncan/R/x86_64-pc-linux-gnu-library/3.1' \
## --install-tests
library(qecol)
data(mussels)
head(mussels)
Lshell | BTVolume | Site |
---|---|---|
122.1 | 39 | Site_6 |
100.1 | 21 | Site_6 |
100.7 | 23 | Site_6 |
102.3 | 22 | Site_6 |
94.9 | 20 | Site_6 |
116.9 | 22 | Site_6 |
?q_regres
q_regres | R Documentation |
Quickly run a regression with one command.
q_regres(x, y, xlab, ylab)
x
|
Numerical vector. |
y
|
A Numerical vector. |
xlab
|
Label for x axis. |
ylab
|
Label for y axis. |
Runs a quick regression and prints the results to a markdown report.
data(mussels) q_regres(mussels$Lshell,mussels$BTVolume,"Shell length","Body volume")
q_regres(mussels$Lshell,mussels$BTVolume,"Shell length","Body volume")
## Loading required package: ggplot2
##
## Call:
## lm(formula = y ~ x)
##
## Residuals:
## Min 1Q Median 3Q Max
## -11.828 -2.672 0.147 2.235 17.404
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -36.02385 3.33917 -10.79 <2e-16 ***
## x 0.59754 0.03096 19.30 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 4.864 on 111 degrees of freedom
## Multiple R-squared: 0.7704, Adjusted R-squared: 0.7684
## F-statistic: 372.5 on 1 and 111 DF, p-value: < 2.2e-16
##
## 2.5 % 97.5 %
## (Intercept) -42.6406346 -29.4070662
## x 0.5361881 0.6588891