I have posted a series of entries about programming an estimation command in Stata. They are best read in order. The comprehensive list below allows you to read them from first to last at your own pace.

Programming estimators in Stata: Why you should
To help you write Stata commands that people want to use, I illustrate how Stata syntax is predictable and give an overview of the estimationpostestimation structure that you will want to emulate in your programs.

Programming an estimation command in Stata: Where to store your stuff
I discuss the difference between scripts and commands, and I introduce some essential programming concepts and constructions that I use to write the scripts and commands.

Programming an estimation command in Stata: Global macros versus local macros
I discuss a pair of examples that illustrate the differences between global macros and local macros.

Programming an estimation command in Stata: A first adocommand
I discuss the code for a simple estimation command to focus on the details of how to implement an estimation command. The command that I discuss estimates the mean by the sample average. I begin by reviewing the formulas and a dofile that implements them. I subsequently introduce Read more…
I discuss a command that computes ordinary leastsquares (OLS) results in Mata, paying special attention to the structure of Stata programs that use Mata work functions.
This command builds on several previous posts; at a minimum, you should be familiar with Programming an estimation command in Stata: A first adocommand using Mata and Programming an estimation command in Stata: Computing OLS objects in Mata.
This is the fifteenth post in the series Programming an estimation command in Stata. I recommend that you start at the beginning. See Programming an estimation command in Stata: A map to posted entries for a map to all the posts in this series.
An OLS command with Mata computations
The Stata command myregress11 computes the results in Mata. The syntax of the myregress11 command is
myregress11 depvar [indepvars] [if] [in] [, noconstant]
where indepvars can contain factor variables or timeseries variables.
In the remainder of this post, I discuss the code for myregress11.ado. I recommend that you click on the file name to download the code. To avoid scrolling, view the code in the dofile editor, or your favorite text editor, to see the line numbers.
I do not discuss Read more…
\(\newcommand{\epsilonb}{\boldsymbol{\epsilon}}
\newcommand{\ebi}{\boldsymbol{\epsilon}_i}
\newcommand{\Sigmab}{\boldsymbol{\Sigma}}
\newcommand{\betab}{\boldsymbol{\beta}}
\newcommand{\eb}{{\bf e}}
\newcommand{\xb}{{\bf x}}
\newcommand{\xbit}{{\bf x}_{it}}
\newcommand{\xbi}{{\bf x}_{i}}
\newcommand{\zb}{{\bf z}}
\newcommand{\zbi}{{\bf z}_i}
\newcommand{\wb}{{\bf w}}
\newcommand{\yb}{{\bf y}}
\newcommand{\ub}{{\bf u}}
\newcommand{\Xb}{{\bf X}}
\newcommand{\Mb}{{\bf M}}
\newcommand{\Xtb}{\tilde{\bf X}}
\newcommand{\Wb}{{\bf W}}
\newcommand{\Vb}{{\bf V}}\)I present the formulas for computing the ordinary leastsquares (OLS) estimator and show how to compute them in Mata. This post is a Mata version of Programming an estimation command in Stata: Using Stata matrix commands and functions to compute OLS objects. I discuss the formulas and the computation of independencebased standard errors, robust standard errors, and clusterrobust standard errors.
This is the fourteenth post in the series Programming an estimation command in Stata. I recommend that you start at the beginning. See Programming an estimation command in Stata: A map to posted entries for a map to all the posts in this series.
OLS formulas
Recall that the OLS point estimates are given by
\[
\widehat{\betab} =
\left( \sum_{i=1}^N \xb_i’\xb_i \right)^{1}
\left(
\sum_{i=1}^N \xb_i’y_i
\right)
\]
where \(\xb_i\) is the \(1\times k\) vector of independent variables, \(y_i\) is the dependent variable for each of the \(N\) sample observations, and the model for \(y_i\) is
\[
y_i = \xb_i\betab’ + \epsilon_i
\]
If the \(\epsilon_i\) are independently and identically distributed (IID), we estimate Read more…
I discuss a sequence of adocommands that use Mata to estimate the mean of a variable. The commands illustrate a general structure for Stata/Mata programs. This post builds on Programming an estimation command in Stata: Mata 101, Programming an estimation command in Stata: Mata functions, and Programming an estimation command in Stata: A first adocommand.
This is the thirteenth post in the series Programming an estimation command in Stata. I recommend that you start at the beginning. See Programming an estimation command in Stata: A map to posted entries for a map to all the posts in this series.
Using Mata in adoprograms
I begin by reviewing the structure in mymean5.ado, which I discussed Read more…
I show how to write a function in Mata, the matrix programming language that is part of Stata. This post uses concepts introduced in Programming an estimation command in Stata: Mata 101.
This is the twelfth post in the series Programming an estimation command in Stata. I recommend that you start at the beginning. See Programming an estimation command in Stata: A map to posted entries for a map to all the posts in this series.
Mata functions
Commands do work in Stata. Functions do work in Mata. Commands operate on Stata objects, like variables, and users specify options to alter the behavior. Mata functions accept arguments, operate on the arguments, and may return a result or alter the value of an argument to contain a result.
Consider myadd() defined below.
Code block 1: myadd()
mata:
function myadd(X, Y)
{
A = X + Y
return(A)
}
end
myadd() accepts two arguments, X and Y, puts the sum of X and Y into A, and returns A. For example, Read more…
I introduce Mata, the matrix programming language that is part of Stata.
This is the eleventh post in the series Programming an estimation command in Stata. I recommend that you start at the beginning. See Programming an estimation command in Stata: A map to posted entries for a map to all the posts in this series. Read more…
Distributing a Stata command that implements a statistical method will get that method used by lots of people. They will thank you. And, they will cite you!
This post is the first in the series #StataProgramming about programing an estimation command in Stata that uses Mata to do the numerical work. In the process of showing you how to program an estimation command in Stata, I will discuss dofile programming, adofile programming, and Mata programming. When the series ends, you will be able to write Stata commands.
Stata users like its predictable syntax and its estimationpostestimation structure that facilitates hypothesis testing, specification tests, and parameter interpretation. To help you write Stata commands that people want to use, I illustrate how Stata syntax is predictable and give an overview of the estimationpostestimation structure that you will want to emulate in your programs. Read more…
I’m still recycling my talk called “Mata, The Missing Manual” at user meetings, a talk designed to make Mata more approachable. One of the things I say late in the talk is, “Unless you already know what pointers are and know you need them, ignore them. You don’t need them.” And here I am writing about, of all things, pointers. Well, I exaggerated a little in my talk, but just a little.
Before you take my previous advice and stop reading, let me explain: Mata serves a number of purposes and one of them is as the primary langugage we at StataCorp use to implement new features in Stata. I’m not referring to mock ups, toys, and experiments, I’m talking about readytoship code. Stata 12’s Structural Equation Modeling features are written in Mata, so is Multiple Imputation, so is Stata’s optimizer that is used by nearly all estimation commands, and so are most features. Mata has a side to it that is exceedingly serious and intended for use by serious developers, and every one of those features are available to users just as they are to StataCorp developers. This is one of the reasons there are so many userwritten commands are available for Stata. Even if you don’t use the serious features, you benefit. Read more…
I gave a 1.5 hour talk on Mata at the 2010 UK Stata Users Group Meeting in September. The slides are available in pdf form here. The talk was well received, which of course pleased me. If you’re interested in Mata, I predict you will find the slides useful even if you didn’t attend the meeting. Read more…