By Christopher F. Baum
This paintings makes a speciality of 3 different types of Stata programming: do-file programming, ado-file programming, and Mata capabilities that paintings at the side of do- and ado-files. It explains how one can usefully automate paintings with Stata and the way to exploit Stata extra successfully via programming on a number of of those degrees. After featuring basic thoughts of the command-line interface and widespread instruments for operating with courses and knowledge units, the textual content follows a distinct layout via providing "cookbook" chapters after each one major bankruptcy. those cookbook chapters examine easy methods to practice a particular programming activity with Stata and supply a whole technique to the matter. The textual content additionally comprises various examples of Mata, Stata’s matrix programming language.
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Additional info for An Introduction to Stata Programming
We can use the Bernstein polynomials to generate parametric curves B(t)=(x1 (t), ... ,xd(t» in Rd by running the recursion in reverse as illustrated in Figure 4. At the base of the triangle place a sequence of points PO"",PN, where PK=(PK,1, ... ,PK,d)' K=O, ... ,N, and reverse all the arrows in Figure 3. Each element in the triangle is now an affine combination of the elements immediately below it to its left and right. Out the top at the apex of the triangle emerge points on the parametric curve B(t).
At the base of the triangle place a sequence of points PO"",PN, where PK=(PK,1, ... ,PK,d)' K=O, ... ,N, and reverse all the arrows in Figure 3. Each element in the triangle is now an affine combination of the elements immediately below it to its left and right. Out the top at the apex of the triangle emerge points on the parametric curve B(t). Clearly these points depend linearly on the input PO"",PN' Moreover the coefficient of PK in B(t) is just the sum of the paths from PK at the base to B(t) at the apex of the triangle.
B~(t) are called the blending functions of the curve B(t). The parametric curves whose blending functions are the Bernstein basis functions are known as Bezier curves. Thus Bezier curves are just parametric Bernstein polynomials. Because the Bernstein basis functions are linearly independent, Bezier curves are non-degenerate; that is, they never collapse to a single point unless all the control points are located at a single point. The recursive algorithm we have just described for evaluating points on a Bezier curve is known as the de Casteljau algorithm.
An Introduction to Stata Programming by Christopher F. Baum