Function - Revision history

Rb: /* How are functions used? */

2014-11-21T11:39:15Z

‎How are functions used?

Admin: /* OLSest in detail */

2013-05-30T09:00:04Z

‎OLSest in detail

78.144.158.205: /* How are functions used? */

2012-09-25T18:47:54Z

‎How are functions used?

Admin at 14:08, 25 September 2012

2012-09-25T14:08:16Z

Admin at 14:03, 25 September 2012

2012-09-25T14:03:57Z

Admin: /* How are functions used? */

2012-09-25T14:03:34Z

‎How are functions used?

Admin at 14:03, 25 September 2012

2012-09-25T14:03:09Z

Admin at 14:01, 25 September 2012

2012-09-25T14:01:33Z

Admin: /* OLSest in detail */

2012-09-25T13:58:31Z

‎OLSest in detail

Admin at 13:54, 25 September 2012

2012-09-25T13:54:56Z

Show changes

@@ Line 114: / Line 114: @@
 = <div id="FuncUse"></div>How are functions used?  =
-So far we have described how to write a function and we understand that it is the equivalent of a drinks machine ready to be used (receiving some inputs and handing back outputs). The question remains how to use it. The best way to use them is to save the function into a new mfile (*.m) that has the same file as the function name (here <source enclose=none>OLSest.m</source>).<br />
+So far we have described how to write a function and we understand that it is the equivalent of a drinks machine ready to be used (receiving some inputs and handing back outputs). The question remains how to use it. The best way to use them is to save the function into a new mfile (*.m) that has the same file as the function name (here <code>OLSest.m</code>).<br />
 Having done that you can use that function (say in a MATLAB script, an example of which you can find [[FctExampleCode#FunctionExamplem|here]]) as demonstrated in the following code extract:
@@ Line 124: / Line 123: @@
          [bhat,bhatse,resids,obs,resss,rsq] = OLSest(depvar,expvar,0);
          disp(bhat)</source>
-As you can see here all input and output variables have names different to those used in the code of the function itself. Let’s take the first input variable <source enclose=none>depvar</source> which contains a vector with the dependent variable. In this script this vector is known as <source enclose=none>depvar</source>. In this function call it is handed over to the function and there it adopts the name <source enclose=none>y</source> as that is the name given to the first input variable into the function <source enclose=none>OLSest</source>. Inside the function the variable <source enclose=none>depvar</source> is actually unknown. Also note that the third input variable was given the value 0. By doing so we ensure that the function does not print the regression output. The first output variable is given the name <source enclose=none>bhat</source> in the above script. The function <source enclose=none>OLSest</source> itself actually does not know that variable. However, it did calculate the OLS parameter estimate, saved it (inside the function) as <source enclose=none>b</source> and then handed this value back as the first output variable. Here in the script file this is then known as <source enclose=none>bhat</source> and you can continue using that value.<br />
+As you can see here all input and output variables have names different to those used in the code of the function itself. Let’s take the first input variable <code>depvar</code> which contains a vector with the dependent variable. In this script this vector is known as <code>depvar</code>. In this function call it is handed over to the function and there it adopts the name <code>y</code> as that is the name given to the first input variable into the function <code>OLSest</code>. Inside the function the variable <code>depvar</code> is actually unknown. Also note that the third input variable was given the value 0. By doing so we ensure that the function does not print the regression output. The first output variable is given the name <code>bhat</code> in the above script. The function <code>OLSest</code> itself actually does not know that variable. However, it did calculate the OLS parameter estimate, saved it (inside the function) as <code>b</code> and then handed this value back as the first output variable. Here in the script file this is then known as <code>bhat</code> and you can continue using that value.<br />
 = Numerical test example =

@@ Line 89: / Line 89: @@
      ym    = y - mean(y);
      r2    = 1 - (res'*res)/(ym'*ym);
-     }</source>
+     </source>
 The commands in this section calculate the residuals (<source enclose=none>res</source>), the residual sum of squares (<source enclose=none>rss</source>), the coefficient estimates standard error (<source enclose=none>bse</source>) and the regressionś <math>R^2</math> (<source enclose=none>r2</source>). Again we refer to standard econometric textbooks for the details of these calculations.<br />

@@ Line 125: / Line 125: @@
          disp(bhat)</source>
 As you can see here all input and output variables have names different to those used in the code of the function itself. Let’s take the first input variable <source enclose=none>depvar</source> which contains a vector with the dependent variable. In this script this vector is known as <source enclose=none>depvar</source>. In this function call it is handed over to the function and there it adopts the name <source enclose=none>y</source> as that is the name given to the first input variable into the function <source enclose=none>OLSest</source>. Inside the function the variable <source enclose=none>depvar</source> is actually unknown. Also note that the third input variable was given the value 0. By doing so we ensure that the function does not print the regression output. The first output variable is given the name <source enclose=none>bhat</source> in the above script. The function <source enclose=none>OLSest</source> itself actually does not know that variable. However, it did calculate the OLS parameter estimate, saved it (inside the function) as <source enclose=none>b</source> and then handed this value back as the first output variable. Here in the script file this is then known as <source enclose=none>bhat</source> and you can continue using that value.<br />
 = Numerical test example =

@@ Line 117: / Line 117: @@
-Having done that you can use that function (say in a MATLAB script) as demonstrated in the following code extract:
+Having done that you can use that function (say in a MATLAB script, an example of which you can find [[FctExampleCode#FunctionExamplem|here]]) as demonstrated in the following code extract:
 <source>        depvar = ...; \% a vector which contains the dependent variable
@@ Line 125: / Line 125: @@
          disp(bhat)</source>
 As you can see here all input and output variables have names different to those used in the code of the function itself. Let’s take the first input variable <source enclose=none>depvar</source> which contains a vector with the dependent variable. In this script this vector is known as <source enclose=none>depvar</source>. In this function call it is handed over to the function and there it adopts the name <source enclose=none>y</source> as that is the name given to the first input variable into the function <source enclose=none>OLSest</source>. Inside the function the variable <source enclose=none>depvar</source> is actually unknown. Also note that the third input variable was given the value 0. By doing so we ensure that the function does not print the regression output. The first output variable is given the name <source enclose=none>bhat</source> in the above script. The function <source enclose=none>OLSest</source> itself actually does not know that variable. However, it did calculate the OLS parameter estimate, saved it (inside the function) as <source enclose=none>b</source> and then handed this value back as the first output variable. Here in the script file this is then known as <source enclose=none>bhat</source> and you can continue using that value.<br />
 = Numerical test example =

← Older revision		Revision as of 14:03, 25 September 2012
Line 1:		Line 1:
−	~~=1.0~~
−
	= Overview =		= Overview =

@@ Line 114: / Line 114: @@
 The actual example <source enclose=none>OLSest</source> function in the file <source enclose=none>OLSest.m</source> is a somewhat expanded version of this as it also calculates t-statistics, p-values and Durbin-Watson test statistics. But all these extra stats only appear in the output (if <source enclose=none>output</source> = 1). It also checks whether the input matrix <source enclose=none>X</source> contains a column of constants (and if not adds one) and checks for missing observations.
-= How are functions used?<div id=&quot;FuncUse&quot;></div>  =
+= How are functions used?<div id="FuncUse"></div>  =
 So far we have described how to write a function and we understand that it is the equivalent of a drinks machine ready to be used (receiving some inputs and handing back outputs). The question remains how to use it. The best way to use them is to save the function into a new mfile (*.m) that has the same file as the function name (here <source enclose=none>OLSest.m</source>).<br />

@@ Line 1: / Line 1: @@
-= Overview =
+=1.0
 = Overview =
@@ Line 78: / Line 31: @@
      programming commands;
      end</source>
-We have a set of input variables (<source enclose=none>in1, in2, etc.</source>) which will be used in a set of calculations (<source enclose=none>programming commands</source>). These calculations will use the input variables to calculate some outputs (<source enclose=none>out1, out2, etc.</source>). The function then hands back the values for these variables (<source enclose=none>out1,out2,...</source>) such that they can be used later in any subsequent calculations. More on this in Section How are functions used) CREATE LINK!!!!. Where should you save this code? It is best to save this code in a m-file that has exactly the same name as the function, i.e. FunctionName.m. If you do that you can call that function from any other code, which is very useful for a OLS function which we are about to write, as that will be used very often.
+We have a set of input variables (<source enclose=none>in1, in2, etc.</source>) which will be used in a set of calculations (<source enclose=none>programming commands</source>). These calculations will use the input variables to calculate some outputs (<source enclose=none>out1, out2, etc.</source>). The function then hands back the values for these variables (<source enclose=none>out1,out2,...</source>) such that they can be used later in any subsequent calculations. More on this [[#FuncUse|here]]. Where should you save this code? It is best to save this code in a m-file that has exactly the same name as the function, i.e. FunctionName.m. If you do that you can call that function from any other code, which is very useful for a OLS function which we are about to write, as that will be used very often.
 So, before we continue we need to specify what the inputs ought to be and what outputs we should expect from our function. The input that is required to estimate a regression is the following:
@@ Line 161: / Line 114: @@
 The actual example <source enclose=none>OLSest</source> function in the file <source enclose=none>OLSest.m</source> is a somewhat expanded version of this as it also calculates t-statistics, p-values and Durbin-Watson test statistics. But all these extra stats only appear in the output (if <source enclose=none>output</source> = 1). It also checks whether the input matrix <source enclose=none>X</source> contains a column of constants (and if not adds one) and checks for missing observations.
-= How are functions used? =
+= How are functions used?<div id=&quot;FuncUse&quot;></div>  =
 So far we have described how to write a function and we understand that it is the equivalent of a drinks machine ready to be used (receiving some inputs and handing back outputs). The question remains how to use it. The best way to use them is to save the function into a new mfile (*.m) that has the same file as the function name (here <source enclose=none>OLSest.m</source>).<br />

@@ Line 1: / Line 1: @@
 = Overview =
@@ Line 50: / Line 99: @@
 = OLSest in detail =
-With the above list of in-and outputs we know that our function (which we will call <source enclose=none>OLSest</source>) will have the following architecture:
+You can obtain the complete function code from [[FctExampleCode#OLSestm|here]]. With the above list of in-and outputs we know that our function (which we will call <source enclose=none>OLSest</source>) will have the following architecture:
 <source>    function [b,bse,res,n,rss,r2] = OLSest(y,x,output)
@@ Line 111: / Line 160: @@
 The actual example <source enclose=none>OLSest</source> function in the file <source enclose=none>OLSest.m</source> is a somewhat expanded version of this as it also calculates t-statistics, p-values and Durbin-Watson test statistics. But all these extra stats only appear in the output (if <source enclose=none>output</source> = 1). It also checks whether the input matrix <source enclose=none>X</source> contains a column of constants (and if not adds one) and checks for missing observations.
 = How are functions used? =