edu.ucla.stat.SOCR.analyses.command
Class MultiRegressionCSV

java.lang.Object
  edu.ucla.stat.SOCR.analyses.command.MultiRegressionCSV

public class MultiRegressionCSV
extends java.lang.Object

Usage: java -ms200m -mx500m -cp /SOCR_LibPath/SOCR_core.jar:/SOCR_LibPath/SOCR_plugin.jar \ edu.ucla.stat.SOCR.analyses.command.MultiRegressionCSV Input_Text_Data.txt -h \ -response ResponseVariableName -regressors Regressor1,Regressor2,Regressor1*Regressor2 See: http://wiki.stat.ucla.edu/socr/index.php/SOCR_EduMaterials_AnalysesCommandLineMultiRegression See: http://wiki.stat.ucla.edu/socr/index.php/SOCR_EduMaterials_AnalysesCommandLineVolumeMultipleRegression

Constructor Summary

MultiRegressionCSV()

Method Summary

static boolean	isRegressorValid(java.util.HashSet<java.lang.String> validRegressors, Regressor newRegressor) this method helps the parseRegressors method above in particular, it takes a list of validated regressor variables and a not-yet-validated regressor variable if the new variable is valid, this method returns true if not, then it returns false; the criteria for validity is described in the description of parseRegressors
static void	main(java.lang.String[] args)
static boolean	parseRegressors(java.util.StringTokenizer st) check regressor list for interactions in particular, each interaction variable must be composed of individual regressor variables that are also included in the regressor list; for instance, if we have an interaction variable A*B*C, we must have (minimally): -regressors A,B,C,A*B,B*C,A*C,A*B*C

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

MultiRegressionCSV

public MultiRegressionCSV()

Method Detail

main

public static void main(java.lang.String[] args)

parseRegressors

public static boolean parseRegressors(java.util.StringTokenizer st)

check regressor list for interactions in particular, each interaction variable must be composed of individual regressor variables that are also included in the regressor list; for instance, if we have an interaction variable A*B*C, we must have (minimally): -regressors A,B,C,A*B,B*C,A*C,A*B*C

isRegressorValid

public static boolean isRegressorValid(java.util.HashSet<java.lang.String> validRegressors,
                                       Regressor newRegressor)

this method helps the parseRegressors method above in particular, it takes a list of validated regressor variables and a not-yet-validated regressor variable if the new variable is valid, this method returns true if not, then it returns false; the criteria for validity is described in the description of parseRegressors