This is supposed to be a brief tutorial to introduce you to basic 3D transformation matrices and the matrix stack editor in the newer (>=1.5) versions of my modification to jonwil's RCT3 importer.

Introduction On Used Terms
Transformation Matrix Types
Matrix Editor Tutorial (to be written)

In this section I'll give a short introduction on the terms you'll need to understand 3D matrix transformations. I'll start with the mathematical definition and then try to explain in easy words what it means and how it applies to 3D objects and their manipulation.

Coordinate System

A system for specifying points using coordinates measured in some specified way. The simplest coordinate system consists of coordinate axes oriented perpendicularly to each other, known as Cartesian coordinates. Depending on the type of problem under consideration, coordinate systems possessing special properties may allow particularly simple solution.
Weisstein, Eric W. "Coordinate System." From MathWorld--A Wolfram Web Resource.

In short, a coordinate system is a way to describe a point in space. As we want to work with 3D objects, we use a three dimensional coordinate system with three axes (sing. axis) called x, y and z. We also use a cartesian coordinate system, which means that all axes are, like stated above, perpendicular to each other (If you're not familar with the term, it means they form right (90 degree) angles with each-other).
What needs further explanation are the terms right-handed and left-handed coordinate system. This arises from the fact that there are two possible ways to form a cartesian coordinate system in 3D space. Whether a coordinate system is left- or rightshanded can be easily determined with syou guessed it- your hand. Using your right hand, point the thumb in the direction of the x-axis and your index finger in the direction of the y-axis. If you now can point your middle finger in the direction of the z-axis without hurting yourself (or overbending if you're flexible enough :-) ), it's a right-handed coordinate system. Here are two pictures to practice:

Left-handed coordinate system	Right-handed coordinate system

Which way is up is only a matter of perspective, not a real difference in coordinate systems :-)
Why do we need to discuss this? Many modelers (eg Blender) use a right-handed z-up coordinate system. This is the mathematical standart. It probably originates from 2D drawing. If you plot on a paper you use a 2D coordinate system where usually the x-axis points to the right and the y-axis points to the top of the sheet. If you now envision 3D space to "pop-out" of the paper along a z-axis you arrive at a right-handed, z-up system.
In 3D games, things are different. First, envision the 2D drawing on your screen. To switch to 3D, treat your screen as a window. Now the z-axis streches out into the "depth" of the screen. Jiggle your fingers, and you'll see that this constitutes a left-handed, y-up coordinate system, which is the standart in 3D gaming. RCT3 uses such a system.
This is the reason I added the fixup to the importer. If you model in a right-handed z-up system and import into RCT3, your model will end up lying on the side, being burried half in the earth and mirrored.
(Note: MilkShape uses a right-handed, y-up coordinate system. Don't ask me why.)

Vertex (pl. vertices)

A vertex is a special point of a mathematical object, and is usually a location where two or more lines or edges meet. Vertices are most commonly encountered in angles, polygons, polyhedra, and graphs. Graph vertices are also known as nodes.
Weisstein, Eric W. "Vertex." From MathWorld--A Wolfram Web Resource. http://mathworld.wolfram.com/Vertex.html

In short easy words, for us a vertex is a point in three-dimensional space. It's the basic building block of 3D objects.
To get a full 3D object, vertices are connected by edges that form faces (sometimes also called Polygons or Polys). Current 3D graphic cards use only triangular faces, therefore faces are often also called triangles or tris. Some 3D modelers can also work with 4 vertex faces (quads) or even larger ones, but these need to be converted to triangles before you can use them for 3D games. This usually happens automatically when you save to a file format that only supports triangular faces. In some cases you might want to do this manually to get a certain look.
I will not discuss edges and faces further because they are not really relevant for 3D transformation matrices.

Vector (pl. vectors)

A vector is formally defined as an element of a vector space. In the commonly encountered vector space Rⁿ (i.e., Euclidean n-space), a vector is given by n coordinates and can be specified as (A₁, A₂, ..., A_n). Vectors are sometimes referred to by the number of coordinates they have, so a 2-dimensional vector (x₁,x₂) is often called a two-vector, an n-dimensional vector is often called an n-vector, and so on.
Weisstein, Eric W. "Vector." From MathWorld--A Wolfram Web Resource. http://mathworld.wolfram.com/Vector.html

So far the formal definition. I cited this mainly to show you that by definition a vertex and a vector are different things, while in 3D programming slang they are often used as the same. Formally a vector is an arrow, ie it has a direction and a length. In 3D space it has three coordinates.
I'll stop here so I don't confuse you :-) For our purpose, you can safley assume that a vector and a vertex are the same. If you want to be more precise, imagine the vector to be the arrow that points from the origin to the vertex.

Matrix (pl. matrices)

A matrix is a concise and useful way of uniquely representing and working with linear transformations. In particular, for every linear transformation, there exists exactly one corresponding matrix, and every matrix corresponds to a unique linear transformation. The matrix, and its close relative the determinant, are extremely important concepts in linear algebra, and were first formulated by Sylvester and Cayley.
Weisstein, Eric W. "Matrix." From MathWorld--A Wolfram Web Resource. http://mathworld.wolfram.com/Matrix.html

To sum it up for our purpose, a matrix is a way to move around vertices in a certain way. Usually a matrix in 3D space would be 3 x 3 big. As you will see later, we'll use 4 x 4 matrices, which makes linear translation (= linear movement) much easier.
To transform a vertex (or vector in this case) it needs to be multiplied with the matrix. The exact procedure is beyond this brief introduction, but what you should know is, that it's mathematically impossible to multiply a 3D vector with a 4D matrix. To apply a 4D matrix we need a small trick. We just make the vector 4D by adding a fourth coordinate which we set to 1 (That's actually what makes the translation matrices work).
So why are matrices so convenient for 3D transformations? The reason is that you can merge several matrices into one, that in one step does all the transformations of the ones you merged. The mathematical operation behind this is called a matrix multiplication and, like the vector-matrix multiplication, differs from the multiplication of numbers. The most important difference is that matrix multiplication is not commutative. This means the order of multiplication does matter, if A and B are matrices, A•B is not equal to B•A. The matrix that results fom the multiplication A•B does the same as applying A first and then B. If you think a bit about it, it should be clear that in many cases you'll get a different result if you do it the other way around.

All the transformation matrices I'll explain now work with the origin as center of operation. This doesn't matter for translation matrices, but is important for rotation and scaling matrices (see there).