To use the matrices later, we need to first store the matrices: To list the matrices of stored results, we can ![]() Predicted probabilities on samples used in the previous estimation outreg2 using myfile, adds(F-test, r(F), Prob > F, r(p)) replace twoway (lfitci mpg weight) (scatter mpg weight), note(R-squared =`r2')Īdding stats from postestimation in tables In order to be able to use the mean of mpg later, we can: The results will be lost the next time you run another r-class command. Let’s review some examples below where we use the stored results for various purposes. Which gives us the full lists of the results that the command regress offers. To see what the result lists actually look like, try typing Matrices: e(b) coefficient vector and e(V) variance–covariance matrix of the estimates (VCE)įunctions: the only function existing is e(sample), which evaluates to 1 (true) if the observation was used in the previous estimation and to 0 (false) otherwise. If we need to store the returned results, we need to use a macro. Results will be replaced the next time you execute another command of the same class. N-class commands that do not store in r(), e(), or s()Ĭ-class system parameters and settings that store in c()Ĭommands producing statistical results are either r-class or e-class: e-class for estimation results and r-class otherwise.įollowing the r-class or e-class commands, we can obtain all the stored results of a command by typing return list or ereturn list respectively. S-class parsing commands that store results in s() used by programmers R-class general commands that store results in r()Į-class estimation commands that store results in e() There are five classes of Stata commands: Results of calculations are stored by Stata commands so that they can be accessed in other commands and calculations later. Replace the var_i with your real variables here.Stored Results r-class and e-class commands You can add as many variables as you wish or that you would like to use in reports. Postfile `anees_uroot' str12 name dfuller_statistic dfuller_pvalue dfuller_lags perron_statistic pperron_rho pperron_pvalue pperron_lags using `unitroots' Also you need to specify which file to use and what to add to the file as headers. ![]() ![]() Then you need to write to the temporary files as to what should be the names of the headers of the table. You can change the path to your desired detination of the file/folder where your data exists. ![]() Load the data, I have used the example location folder and files. The steps in this tutorial will help you extend this do file to include many other tests like summary statistics to be exported into the same files. The code will do the job to test the variable for unit root or stationarity and compile the results from all the individual tests into a single table and export it to your desired format like MS Word or MS Excel sheet for further use and modifications. To help these querries, I have written the following simplest do file which you can use after modifiying for the relevant places like file_paths and variables_names. There is commonly a question on many forums as to how can one test unit root of several variables and export the results of all these tests into a single file in Word or Excel sheet.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |