help tryem ------------------------------------------------------------------------------- Title tryem Description Finds "best" subset of size k (by brute force) in terms of minimizing or maximizing user-supplied "e"-statistic when estimating a regression model with the distribtion of depvar depending on a linear combination of n potential explanatory variables. Shows variable number(s) (order in varlist), best (min or max) value of "e"-statistic , and identity of best subset Syntax tryem depvar varlist [if] [in] , k(integer) [cmd(string) stat(string) best(string) cmdoptions(string)] options description ------------------------------------------------------------------------- k subset size (required) cmd estimation command (default = reg) stat estimation output "e"-statistic (default = r2) best min or max (default = max) cmdoptions options to be added to estimation command ------------------------------------------------------------------------- Remarks Uses -mktime.ado- (provided) to cycle through the subsets. Warning: / n \ If | | is large, where n is the number of potential regressors, \ k / this may take a prohibitive amount of time. Options Detail ------------------------------------------------------------------------- With only the k( ) option (required), tryem finds subset with maximum r^2 in ordinary linear regression. Other estimation commands are permitted with the cmd( ) option, but then the appropriate estimation statistic ("e"-statistic) has to be specified. For example specifying ..cmd(logit) stat(ll).. as options will find the subset that maximizes the log likelihood under logistic regression If you want to minimize an estimation statistic (such as Pearson deviance in a glm) specify best(min) as an option; e.g. ..cmd(glm) best(min) stat(deviance_p).. If there are options specific to the estimation command, they may be included using cmdoptions( ) - for example for glm with a gamma family and identity link function: ..cmd(glm) cmdoptions(family(gamma) link(identity)) best(min) stat(deviance_p) Examples a) Ordinary linear regression, maximize r^2 . tryem ym3 radex hs12 x* hs43-hs51,k(3) -------------------------------------------- Best r^2 is 0.361193. Best subset of size 3 is: radex xsun xrg Variable numbers for best subset are: 1 7 9 -------------------------------------------- b) ordinary linear regression, find subset with minimum RMSE . tryem ym3 hs1-hs7,k(2) best(min) stat(rmse) [output omitted] c) GLM - minimize Pearson deviance . tryem ym3 x*,k(2) cmd(glm) cmdoptions(family(gamma) link(iden)) best(min) stat(deviance_p) [output omitted] Author(s) --------- Al Feiveson, Johnson Spaceflight Center Email: alan.h.feiveson@nasa.gov Also see Manual: [U] 18.11.6 Writing online help Online: help, summarize