Introduction
I was thinking recently about how best to help someone transitioning
from Matlab(TM) to R, and did my best to recall what sorts of things I
struggled with when I made the switch. Though I resisted for quite a
while, when I finally committed to making the change I recall that it
mostly happened in a matter of weeks. It helped that my thesis
supervisor exclusively used R, and we were working on code for a paper
together at the time, but in the end I found that the switch was
easier than I had anticipated.
Tips
 Don’t be afraid of the assign
<
operator. It means exactly the
same thing as you would use=
in matlab, as in
a < 1:10 # in matlab a=1:10;
except that it make more logical sense.
The only place you should use =
is in logical comparisons like a ==
(as in matlab), or for specifying argument values in a function
b
(see number 5).
 Vectors are truly 1 dimensional. This is different from matlab in
the way that you could not add together an Nx1 and a 1xN vector. In
R it would be just two vectors of length N. The transpose in R is
by doingt()
, and the transpose of a vector (or class numeric)
is the same as the original. 
Array indices use square brackets, like
a[1:5] < 2 # assign the value 2 to the first 5 indices of a
This is one of the things that drove me crazy about matlab, that it
used ()
for indices as well as function arguments. It makes mixed
array indexing and function calls very confusing to look at and
interpret.
 By default arithmetic operations are done elementwise. If you have
two MxN matrices (say A and B), and you doC < A*B
, every
element in C is the product of the corresponding elements in A and
B. No need to do the.*
stuff as in matlab. To get matrix
multiplication, you use the%*%
operator. 
Function arguments are named, so the order isn’t super
important. If you don’t name them, then you have to give them in
the order they appear (do?function
to see the help page). For
example if a function took arguments like:
foo < function(a, b, c, type, bar) { # function code here }
You could call it with something like:
junk < foo(1, 2, bar = "whatever")
where a
and b
are given the values of 1 and 2, and c
and type
are left unspecified. This would be equivalent:
junk < foo(a = 1, b = 2, bar = "whatever")
You could also do:
junk < foo(bar = "whatever", a = 1, b = 2)
 No semicolons needed (except where you’d like to have more than one
operation per line, likea < 1; b < 2

In R, the equivalent to a matlab structure is called a
“list”. Instead of separating the levels with a.
, it is
generally done with a$
. So the structure of a list could be
something like:
a < junk$stuff$whatever
Use the str()
command to look at the structure of a list object.
 Most functions that return more than just a single value will
return in a list. Unlike matlab there isn’t a simple way returning
separate values to separate variables, like[a, b] =
. For example, using the histogram function:
foo('bar')
a < rnorm(1000) h < hist(a)
str(h)
## List of 6
## $ breaks : num [1:16] 4 3.5 3 2.5 2 1.5 1 0.5 0 0.5 ...
## $ counts : int [1:15] 1 1 3 24 47 80 147 186 206 134 ...
## $ density : num [1:15] 0.002 0.002 0.006 0.048 0.094 0.16 0.294 0.372 0.412 0.268 ...
## $ mids : num [1:15] 3.75 3.25 2.75 2.25 1.75 1.25 0.75 0.25 0.25 0.75 ...
## $ xname : chr "a"
## $ equidist: logi TRUE
##  attr(*, "class")= chr "histogram"
If I wanted to extract something from that I could use
b < h$breaks
If you really only want one thing out of the list, you could do
something like
b < hist(a, plot = FALSE)$breaks
 You can use
.
‘s in variable and function names, but I don’t
recommend you do. Often a function with a.
in it means that it
applies a “generic” operation to a specific class. For example, the
plot()
function is a straightforward way of plotting data, much
like in matlab. However, there exist lots of variants ofplot
for
different classes, which are usually specified as
plot.class()
. E.g. for the histogram object I created above, if I
want to plot it, I can just do
h2 < hist(a, plot = FALSE, breaks = 100) plot(h2, main = "A plot with more breaks")
and it will plot it as a histogram, using the generic function
plot.histogram()
, as well as accept the arguments appropriate to
that generic function.
Thoughts on topics for future editions of matlab2R

plotting, including:

points, lines, styles, etc
 “image”style plots, contours, filled contours, colormaps, etc

POSIX times vs Matlab
datenum

… suggestions in comments?