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Contents


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 BIOSIG/T450 contains functions for multiple test statistics

 === MAIN FUNCTIONS === 
  FDR.M	false discovery rate
  FDP.M	false discovery proportion 
  gFWE.M	generalized familiy-wise error 
  GLOBTEST.M	global hypothesis test

 === UTILITY FUNCTIONS === 
    --- do not use them directly if you not know what to do. At least you are warned --- 



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 BIOSIG/T450 contains functions for multiple test statistics



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bh95


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 The function [AaH,pup,adpval] = bh95(psd,indexsd,k,alpha) is a subfunction 
 in fdr.m.
 In fdr.m is bh95.m used as an procedure named 'B-H' for Benjamini and Hochberg.
 For help use the main-function fdr.m.

 REFERENCES:

 [1] Hemmelmann C, Horn M, Suesse T, Vollandt R, Weiss S.
	New concepts of multiple tests and their use for evaluating 
	high-dimensional EEG data.
	J Neurosci Methods. 2005 Mar 30;142(2):209-17.

 [2]

 Copyright (C) 2006 Claudia Hemmelmann <claudia.hemmelmann@mti.uni-jena.de>
 Adapted by A Schloegl <alois.schloegl@gmail.com> Dec 2006

***
 This library is free software; you can redistribute it and/or
 modify it under the terms of the GNU Library General Public
 License as published by the Free Software Foundation; either
 Version 2 of the License, or (at your option) any later version.

 This library is distributed in the hope that it will be useful,
 but WITHOUT ANY WARRANTY; without even the implied warranty of
 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 Library General Public License for more details.

 You should have received a copy of the GNU Library General Public
 License along with this library; if not, write to the
 Free Software Foundation, Inc., 59 Temple Place - Suite 330,
 Boston, MA  02111-1307, USA.

--------------------------------------------------------------------------



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 The function [AaH,pup,adpval] = bh95(psd,indexsd,k,alpha) is a subfunction ...



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bl01


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 The function [AaH,pup,adpval] = bl01(psd,indexsd,k,alpha) is a 
 subfunction in fdr.m.
 In fdr.m is bl01.m used as an procedure named 'B-L' for Benjamini and Liu
 (2001).
 For help use the main-function fdr.m.

 REFERENCES:

 [1] Hemmelmann C, Horn M, Suesse T, Vollandt R, Weiss S.
	New concepts of multiple tests and their use for evaluating 
	high-dimensional EEG data.
	J Neurosci Methods. 2005 Mar 30;142(2):209-17.


 Copyright (C) 2006,2007 Claudia Hemmelmann <claudia.hemmelmann@mti.uni-jena.de>
 Adapted by A Schloegl <alois.schloegl@gmail.com> 2006,2007

***
 This library is free software; you can redistribute it and/or
 modify it under the terms of the GNU Library General Public
 License as published by the Free Software Foundation; either
 Version 2 of the License, or (at your option) any later version.

 This library is distributed in the hope that it will be useful,
 but WITHOUT ANY WARRANTY; without even the implied warranty of
 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 Library General Public License for more details.

 You should have received a copy of the GNU Library General Public
 License along with this library; if not, write to the
 Free Software Foundation, Inc., 59 Temple Place - Suite 330,
 Boston, MA  02111-1307, USA.

--------------------------------------------------------------------------



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 The function [AaH,pup,adpval] = bl01(psd,indexsd,k,alpha) is a 
 subfunctio...



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exakteM_A


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The function [AaH,pup,adpval,q] = exakteM_A(Input,n1,samp,u,B,test,tail,alpha,k)
is a procedure used in the main-function gFWE.m.
The function exakteM_A is called 'Ae' for the procedure A-exact in the main-function gFWE. 
Use the main-function for help.
 Korn et al., exakte Methode


Copyright (C) 2006 by Claudia Hemmelmann <claudia.hemmelmann@mti.uni-jena.de>
Institute of Medical Statistics, Computer Sciences and Documantation
University of Jena
This work was supported by DFG Project VO 683/2-1
This is part of the BIOSIG-toolbox http://biosig.sf.net/
***
 This library is free software; you can redistribute it and/or
 modify it under the terms of the GNU Library General Public
 License as published by the Free Software Foundation; either
 Version 2 of the License, or (at your option) any later version.

 This library is distributed in the hope that it will be useful,
 but WITHOUT ANY WARRANTY; without even the implied warranty of
 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 Library General Public License for more details.

 You should have received a copy of the GNU Library General Public
 License along with this library; if not, write to the
 Free Software Foundation, Inc., 59 Temple Place - Suite 330,
 Boston, MA  02111-1307, USA.

--------------------------------------------------------------------------



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The function [AaH,pup,adpval,q] = exakteM_A(Input,n1,samp,u,B,test,tail,alph...



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exakteM_B


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The function [AaH,pup,adpval,q] = exakteM_B(Input,n1,samp,gamma,B,test,tail,alpha,k)
is a procedure used in the main-function fdp.m.
The function exakteM_B is called 'Be' for the procedure B (conservative) of Korn et al. (2004) in the main-function fdp. 
Use the main-function for help.



Copyright (C) 2006 by Claudia Hemmelmann <claudia.hemmelmann@mti.uni-jena.de>
Institute of Medical Statistics, Computer Sciences and Documantation
University of Jena
This work was supported by DFG Project VO 683/2-1
This is part of the BIOSIG-toolbox http://biosig.sf.net/
***
 This library is free software; you can redistribute it and/or
 modify it under the terms of the GNU Library General Public
 License as published by the Free Software Foundation; either
 Version 2 of the License, or (at your option) any later version.

 This library is distributed in the hope that it will be useful,
 but WITHOUT ANY WARRANTY; without even the implied warranty of
 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 Library General Public License for more details.

 You should have received a copy of the GNU Library General Public
 License along with this library; if not, write to the
 Free Software Foundation, Inc., 59 Temple Place - Suite 330,
 Boston, MA  02111-1307, USA.

--------------------------------------------------------------------------



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The function [AaH,pup,adpval,q] = exakteM_B(Input,n1,samp,gamma,B,test,tail,...



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fdp


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 The function fdp performs different multiple test procedures for 
 controlling the false discovery proportion (FDP). 
 
 function [O] = fdp(Input,n1,samp) returns the number of rejected hypotheses,
 the rank (O(:,1)), the indices of the rejected hypotheses (O(:,2)) and the unadjusted 
 p-values (O(:,3)) for the procedure B (conservative) of Korn et al. (2004)
 with the significance level alpha=0.05.


----------
INPUT

 These input arguments are required:
 Input: data matrix with the size [n,k]               
 n1:	number of patients in group one (0 < n1 <= n ), 
	restricted by the kind of samp
 samp: kind of sample         
                             
           single sample       'single' (n1 = n)
           paired sample       'paired' (n1 = n/2; n must be even)
           independent sample  'indept' (n1 < n)

 [...] = fdp(...,'PARAM1',VAL1,'PARAM2',VAL2,...) specifies additional
 parameters and their values. Valid parameters are the following:
   
    Parameter        Value

    'gamma'        gamma = 0.1; (the default)
                     for an other value: 0< gamma <= 0.5

     'B'            number of permutations
		     default: 500 
                    B must be in the intervall
                       500 <= B <= 2^n1   for single and paired sample
                           		   (for 2^n1 < 500 : B = min(B,2^n1)) 

                       500 <= B <= n! / n1!*(n-1)  for independent sample
                       (for n! / n1!*(n-n1)! < 500 : B = min(B,n!/n1!*(n-n1)!))

     'test'         Value for single sample
    		          'ttest'               to compute the t-Test
                                           assumption : normal(gaussian) distribution   
                     'wilcox'              to compute the Wilcoxen signed rank test
                                           assumption : symmetrical distribution
                     'sign' (the default)  to compute the sign-test 
                                           assumption : none  
            
                    Value for paired sample
                     'ttest'                to compute the t-Test
                                            assumption : normal(gaussian) distribution
                     'wilcox'               to compute the Wilcoxen signed rank test
                                            assumption : symmetrical distribution
                     'sign' (the default)   to compute the sign-test
                                            assumption : none  
              
                    Value for independent sample
                     'ttest'                to compute the t-Test
                                            assumption : normal(gaussian) distribution 
                     'wilcox' (the default) to compute the Wilcoxen rank test (Wilcoxen-Man-Whitney-Test)
                                            assumption : none

      'tail'       The alternative hypothesis against which to compute
                   p-values for testing the hypothesis of no differences.
                   Choices are:

		       tail		 Alternative Hypothesis			
			'~=' (the default)  "there is a significant difference" (two-sided test)
            '>'                "the values of group 1 are higher than the values of group 2" (one-sided test)
            '<'                "the values of group 1 are smaller than the values of group 2" (one-sided test)    

---

      'proc'        'ProcBv' (the default)  chooses the procedure B (conservative) of Korn et al. (2004)
                    'ProcBe'                chooses the procedure B of Korn et al. (2004)
                    'TL'                    chooses the procedure of Troendle (1995) and the extention of van der Laan et al.
                    'LR1'                   chooses the procedure of Lehmann and Romano (2005) with some dependence
                                                    assumptions or asymtotic control (see Romano and Wolf
                                                    (2005) "Control of Generalized Error Rates in Multiple Tetsing")
                    'LR2'                   chooses the procedure of Lehmann and Romano (2005) without any dependence assumptions (conservative!)             
                    'HL'                    chooses the procedure of Holm and the extention of van der Laan et al.
---

      'alpha'       0.05 (the default)    significance level
                    alpha must be a scalar and in the interval 0 < alpha <= 0.2

 OUTPUT

 [O] = fdp(Input,n1,samp) returns the rank (O(:,1)), 
 the indices of the rejected hypotheses (O(:,2)) and 
 the adjusted p-values (O(:,3)).


-----------

 REFERENCES
  [1]	Hemmelmann, C., Horn, M., Süße, T., Vollandt, R., Weiss, S. (2005):
       New concepts of multiple tests and their use for evaluating
       high-dimensional EEG data, Vol 142/2 pp 209-217.



Copyright (C) 2006 by Claudia Hemmelmann <claudia.hemmelmann@mti.uni-jena.de>
Institute of Medical Statistics, Computer Sciences and Documantation
University of Jena
This work was supported by DFG Project VO 683/2-1
This is part of the BIOSIG-toolbox http://biosig.sf.net/
---
***
 This library is free software; you can redistribute it and/or
 modify it under the terms of the GNU Library General Public
 License as published by the Free Software Foundation; either
 Version 2 of the License, or (at your option) any later version.

 This library is distributed in the hope that it will be useful,
 but WITHOUT ANY WARRANTY; without even the implied warranty of
 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 Library General Public License for more details.

 You should have received a copy of the GNU Library General Public
 License along with this library; if not, write to the
 Free Software Foundation, Inc., 59 Temple Place - Suite 330,
 Boston, MA  02111-1307, USA.

--------------------------------------------------------------------------



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 The function fdp performs different multiple test procedures for 
 controll...



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fdr


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 The function FDR performs different multiple test procedures for 
 controlling the false discovery rate (FDR). 
 
 function [O] = fdr(Input,n1,samp) returns the number of rejected hypotheses,
 the rank (O(:,1)), the indices of the rejected hypotheses (O(:,2)), the adjusted p-values
 (O(:,3)) and the unadjusted p-values (O(:,4)) for the procedure of Benjamini
 and Yekutieli (1995) with the significance level alpha=0.05.

----------
INPUT

These input arguments are required:
 Input: data matrix with the size [n,k]               
 n1:	number of patients in group one (0 < n1 <= n ), 
	restricted by the kind of samp
 samp: kind of sample         
                             
           single sample       'single' (n1 = n)
           paired sample       'paired' (n1 = n/2; n must be even)
           independent sample  'indept' (n1 < n)
-----

   [...] = fdr(...,'PARAM1',VAL1,'PARAM2',VAL2,...) specifies additional
   parameters and their values.  Valid parameters are the following:
   
    Parameter        Value

     'test'         Value for single sample
    		          'ttest'               to compute the t-Test
                                           assumption : normal(gaussian) distribution   
                     'wilcox'              to compute the Wilcoxen signed rank test
                                           assumption : symmetrical distribution
                     'sign' (the default)  to compute the sign-test 
                                           assumption : none  
            
                    Value for paired sample
                     'ttest'                to compute the t-Test
                                            assumption : normal(gaussian) distribution
                     'wilcox'               to compute the Wilcoxen signed rank test
                                            assumption : symmetrical distribution
                     'sign' (the default)   to compute the sign-test
                                            assumption : none  
              
                    Value for independent sample
                     'ttest'                to compute the t-Test
                                            assumption : normal(gaussian) distribution 
                     'wilcox' (the default) to compute the Wilcoxen rank test (Wilcoxen-Man-Whitney-Test)
                                            assumption : none

      'tail'       The alternative hypothesis against which to compute
                   p-values for testing the hypothesis of no differences.
                   Choices are:

		       tail		 Alternative Hypothesis			
		'~=' (the default) "there is a significant difference" (two-sided test)
               '>'                "the values of group 1 are higher than the values of group 2" (one-sided test)
               '<'                "the values of group 1 are smaller than the values of group 2" (one-sided test)    

---
      'proc'        'BH' (the default)     chooses the procedure of Benjamini and Hochberg (1995)
                    'BL'                   chooses the procedure of Benjamini and Liu (2001)
                    'BKY'                  chooses the procedure of Benjamini, Krieger and Yekutieli (2001)
---
      'alpha'       0.05 (the default)    significance level
                     for a other value: 0<alpha<=0.2
-----------

 OUTPUT

 [O] = fdr(Input,n1,samp) returns the rank (O(:,1)), 
 the indices of the rejected hypotheses (O(:,2)), 
 the adjusted p-values (O(:,3)) and the unadjusted p-values (O(:,4)).

-----------

 REFERENCES:

  [1] Hemmelmann C, Horn M, Suesse T, Vollandt R, Weiss S.
	New concepts of multiple tests and their use for evaluating high-dimensional EEG data.
	J Neurosci Methods. 2005 Mar 30;142(2):209-17.
  [2] Hemmelmann C, Horn M, Reiterer S, Schack B, Suesse T, Weiss S.
	Multivariate tests for the evaluation of high-dimensional EEG data.
	J Neurosci Methods. 2004 Oct 15;139(1):111-20. 


 Copyright (C) 2006,2007 Claudia Hemmelmann <claudia.hemmelmann@mti.uni-jena.de>
 Adapted by A Schloegl <alois.schloegl@gmail.com> 2006,2007

***
 This library is free software; you can redistribute it and/or
 modify it under the terms of the GNU Library General Public
 License as published by the Free Software Foundation; either
 Version 2 of the License, or (at your option) any later version.

 This library is distributed in the hope that it will be useful,
 but WITHOUT ANY WARRANTY; without even the implied warranty of
 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 Library General Public License for more details.

 You should have received a copy of the GNU Library General Public
 License along with this library; if not, write to the
 Free Software Foundation, Inc., 59 Temple Place - Suite 330,
 Boston, MA  02111-1307, USA.

--------------------------------------------------------------------------



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 The function FDR performs different multiple test procedures for 
 controll...



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gFWE


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 The function gFWE performs different multiple test procedures for controlling
 the generalized family-wise error rate (gFWE), i.e. the probability of rejecting at
 least u+1 (default: u=0) true hypotheses is less than or equal to alpha=0.05.

 [O] = gFWE(Input,n1,samp) returns the number of rejected hypotheses,
 the rank (O(:,1)), the indices of the rejected hypotheses (0(:,2)) and the corresponding
 p-values (O(:,3)) for the procedure of Troendle (1995) with the significance level 
 alpha=0.05. Note, the default is a procedure for controlling the family-wise error
 rate, i.e. the probability of rejecting at least one true hypotheses is less 
 than or equal to alpha=0.05.

----------
INPUT

 These input arguments are required:
 Input: data matrix with the size [n,k]               
 n1:	number of patients in group one (0 < n1 <= n ), 
	restricted by the kind of samp
 samp: kind of sample         
                             
           single sample       'single' (n1 = n)
           paired sample       'paired' (n1 = n/2; n must be even)
           independent sample  'indept' (n1 < n)

 [...] = gFWE(...,'PARAM1',VAL1,'PARAM2',VAL2,...) specifies additional
 parameters and their values. Valid parameters are the following:
   
    Parameter        Value

     'u'            number of accepted type 1 errors; 
		     default: u = 0 (i.e. no type 1 error is accepted!)
                    u must be in the interval 0 <= u <= k/2


     'test'         Value for single sample
    		          'ttest'               to compute the t-Test
                                           assumption : normal(gaussian) distribution   
                     'wilcox'              to compute the Wilcoxen signed rank test
                                           assumption : symmetrical distribution
                     'sign' (the default)  to compute the sign-test 
                                           assumption : none  
            
                    Value for paired sample
                     'ttest'                to compute the t-Test
                                            assumption : normal(gaussian) distribution
                     'wilcox'               to compute the Wilcoxen signed rank test
                                            assumption : symmetrical distribution
                     'sign' (the default)   to compute the sign-test
                                            assumption : none  
              
                    Value for independent sample
                     'ttest'                to compute the t-Test
                                            assumption : normal(gaussian) distribution 
                     'wilcox' (the default) to compute the Wilcoxen rank test (Wilcoxen-Man-Whitney-Test)
                                            assumption : none

      'tail'       The alternative hypothesis against which to compute
                   p-values for testing the hypothesis of no differences.
                   Choices are:

		       tail		 Alternative Hypothesis			
			'~=' (the default)  "there is a significant difference" (two-sided test)
            '>'                "the values of group 1 are higher than the values of group 2" (one-sided test)
            '<'                "the values of group 1 are smaller than the values of group 2" (one-sided test)    

      'proc'        Values for u > 0

                    'Av' (the default)  chooses the procedure A
                    (conservative) of Korn et. al (2004)
                    'Ae'                chooses the procedure A of Korn et al. (2004)
                    'TL'                chooses the procedure of Troendle (1995) and the extention of van der Laan et al.
                    'HH'                chooses the procedure of Hommel and Hoffmann (1987)
                    'HL'                chooses the procedure of Holm and the extention of van der Laan et al.
                    ---
                    Values for u = 0 (the default value for u)

                    'Av' (the default)       chooses the procedure of Troendle (1995)
                    'Ho'                     chooses the procedure of Holm

     'B'            number of permutations (for procedures with permutation tests: Av; Ae; TL)
		     default: 500 
                    B must be in the intervall
                       500 <= B <= 2^n1   for single and paired sample
                           		   (for 2^n1 < 500 : B = min(B,2^n1)) 

                       500 <= B <= n! / n1!*(n-1)  for independent sample
                       (for n! / n1!*(n-n1)! < 500 : B = min(B,n!/n1!*(n-n1)!))


      'alpha'       0.05 (the default)    significance level
                    alpha must be a scalar and in the interval 0 < alpha <= 0.2

 OUTPUT

 [O] = gFWE(Input,n1,samp) returns the rank (O(:,1)), 
 the indices of the rejected hypotheses (O(:,2)) and 
 the adjusted p-values (O(:,3)).

-----------

 REFERENCES
  [1]	Hemmelmann, C., Horn, M., Süße, T., Vollandt, R., Weiss, S. (2005):
       New concepts of multiple tests and their use for evaluating
       high-dimensional EEG data, Vol 142/2 pp 209-217.


Copyright (C) 2006 by Claudia Hemmelmann <claudia.hemmelmann@mti.uni-jena.de>
Institute of Medical Statistics, Computer Sciences and Documantation
University of Jena
This work was supported by DFG Project VO 683/2-1
This is part of the BIOSIG-toolbox http://biosig.sf.net/

***
 This library is free software; you can redistribute it and/or
 modify it under the terms of the GNU Library General Public
 License as published by the Free Software Foundation; either
 Version 2 of the License, or (at your option) any later version.

 This library is distributed in the hope that it will be useful,
 but WITHOUT ANY WARRANTY; without even the implied warranty of
 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 Library General Public License for more details.

 You should have received a copy of the GNU Library General Public
 License along with this library; if not, write to the
 Free Software Foundation, Inc., 59 Temple Place - Suite 330,
 Boston, MA  02111-1307, USA.



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 The function gFWE performs different multiple test procedures for controlli...



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globtest


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 GLOBTEST performs different global tests. A global test provides one
 joint statement on all endpoints, i.e. the global hypotheses is testing. 
 This function returns the corresponding p-value.
 
 
 
----------
INPUT

These input arguments are required:
 Input: data matrix with the size [n,k]               
 n1:	number of patients in group one (0 < n1 <= n ), 
	restricted by the kind of samp
 samp: kind of sample         
                             
           single sample       'single' (n1 = n)
           paired sample       'paired' (n1 = n/2; n must be even)
           independent sample  'indept' (n1 < n)
-----

   [...] = globtest(...,'PARAM1',VAL1,'PARAM2',VAL2,...) specifies additional
   parameters and their values.  Valid parameters are the following:
   
    Parameter        Value  

      'tail'       The alternative hypothesis against which to compute
                   p-values for testing the hypothesis of no differences.
                   Choices are:

		       tail		 Alternative Hypothesis			
		'~=' (the default) "there is a significant difference" (two-sided test)
               '>'                "the values of group 1 are higher than the values of group 2" (one-sided test)
               '<'                "the values of group 1 are smaller than the values of group 2" (one-sided test)    


       'B'            number of permutations
		                default: 500 
                       B must be in the intervall
                       500 <= B <= 2^n1   for single and paired sample
                       (for 2^n1 < 500 : B = min(B,2^n1)) 

                       500 <= B <= n! / n1!*(n-1)  for independent sample
                       (for n! / n1!*(n-n1)! < 500 : B = min(B,n!/n1!*(n-n1)!))

---

    'tstat'              teststatistic
                         'tmax' => is sensitive to departures in only a few endpoints 
                         'tsum' => is sensitive to departures of all endpoints in the same direction
                         'tsumabs' (the default) => is sensitive to departures of all endpoints (independent of the
		                                direction); only two-sided!!!
                         'ta' => choose this test statistic if the relative number of false hypotheses is
		                                small; only independent!
-----------

 OUTPUT

 [p] = globtest(Input,n1,samp) returns the p-value of the global test.

-----------

 REFERENCES:

  [1] Hemmelmann C, Horn M, Reiterer S, Schack B, Suesse T, Weiss S.
	Multivariate tests for the evaluation of high-dimensional EEG data.
	J Neurosci Methods. 2004 Oct 15;139(1):111-20. 


 Copyright (C) 2006,2007 Claudia Hemmelmann <claudia.hemmelmann@mti.uni-jena.de>
 Adapted by A Schloegl <alois.schloegl@gmail.com> 2006,2007

***
 This library is free software; you can redistribute it and/or
 modify it under the terms of the GNU Library General Public
 License as published by the Free Software Foundation; either
 Version 2 of the License, or (at your option) any later version.

 This library is distributed in the hope that it will be useful,
 but WITHOUT ANY WARRANTY; without even the implied warranty of
 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 Library General Public License for more details.

 You should have received a copy of the GNU Library General Public
 License along with this library; if not, write to the
 Free Software Foundation, Inc., 59 Temple Place - Suite 330,
 Boston, MA  02111-1307, USA.

--------------------------------------------------------------------------



# name: <cell-element>
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 GLOBTEST performs different global tests.



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homhof


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The function[AaH,pwert] = homhof(p,k,alpha,u)) is a subfunction in the main-function fdp.m.
Use the main-function for help.

Erweiterung von Holm für u=1,2,3... nach Hommel und Hoffmann (1987)


Copyright (C) 2006 by Claudia Hemmelmann <claudia.hemmelmann@mti.uni-jena.de>
Institute of Medical Statistics, Computer Sciences and Documantation
University of Jena
This work was supported by DFG Project VO 683/2-1
This is part of the BIOSIG-toolbox http://biosig.sf.net/


***
 This library is free software; you can redistribute it and/or
 modify it under the terms of the GNU Library General Public
 License as published by the Free Software Foundation; either
 Version 2 of the License, or (at your option) any later version.

 This library is distributed in the hope that it will be useful,
 but WITHOUT ANY WARRANTY; without even the implied warranty of
 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 Library General Public License for more details.

 You should have received a copy of the GNU Library General Public
 License along with this library; if not, write to the
 Free Software Foundation, Inc., 59 Temple Place - Suite 330,
 Boston, MA  02111-1307, USA.

--------------------------------------------------------------------------



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 80

The function[AaH,pwert] = homhof(p,k,alpha,u)) is a subfunction in the main-...



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 6
lehrom


# name: <cell-element>
# type: sq_string
# elements: 1
# length: 1262

The function [AaH,pwert] = lehrom(p,k,alpha,gamma,vari)
is a procedure used in the main-function fdp.m.
There are two variants of this procedure: LR1 and LR2.
Use the main-function for help.



Copyright (C) 2006 by Claudia Hemmelmann <claudia.hemmelmann@mti.uni-jena.de>
Institute of Medical Statistics, Computer Sciences and Documantation
University of Jena
This work was supported by DFG Project VO 683/2-1
This is part of the BIOSIG-toolbox http://biosig.sf.net/
***
 This library is free software; you can redistribute it and/or
 modify it under the terms of the GNU Library General Public
 License as published by the Free Software Foundation; either
 Version 2 of the License, or (at your option) any later version.

 This library is distributed in the hope that it will be useful,
 but WITHOUT ANY WARRANTY; without even the implied warranty of
 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 Library General Public License for more details.

 You should have received a copy of the GNU Library General Public
 License along with this library; if not, write to the
 Free Software Foundation, Inc., 59 Temple Place - Suite 330,
 Boston, MA  02111-1307, USA.

--------------------------------------------------------------------------



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 80

The function [AaH,pwert] = lehrom(p,k,alpha,gamma,vari)
is a procedure used ...



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 8
nextcomb


# name: <cell-element>
# type: sq_string
# elements: 1
# length: 50
undocumented function: [a, y] = nextcomb (y, N, k)


# name: <cell-element>
# type: sq_string
# elements: 1
# length: 50
undocumented function: [a, y] = nextcomb (y, N, k)



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 9
perm_gfwe


# name: <cell-element>
# type: sq_string
# elements: 1
# length: 1224

The function[P,M,q,Richtung] = pwerte(Input,n1,samp,M,test,tail,alpha) 
 is a subfunction in the main-function gFWE.m.
For help use the main-function.


Copyright (C) 2006 by Claudia Hemmelmann <claudia.hemmelmann@mti.uni-jena.de>
Institute of Medical Statistics, Computer Sciences and Documantation
University of Jena
This work was supported by DFG Project VO 683/2-1
This is part of the BIOSIG-toolbox http://biosig.sf.net/



***
 This library is free software; you can redistribute it and/or
 modify it under the terms of the GNU Library General Public
 License as published by the Free Software Foundation; either
 Version 2 of the License, or (at your option) any later version.

 This library is distributed in the hope that it will be useful,
 but WITHOUT ANY WARRANTY; without even the implied warranty of
 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 Library General Public License for more details.

 You should have received a copy of the GNU Library General Public
 License along with this library; if not, write to the
 Free Software Foundation, Inc., 59 Temple Place - Suite 330,
 Boston, MA  02111-1307, USA.

--------------------------------------------------------------------------



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 80

The function[P,M,q,Richtung] = pwerte(Input,n1,samp,M,test,tail,alpha) 
 is ...



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 6
pwerte


# name: <cell-element>
# type: sq_string
# elements: 1
# length: 1060

The function[P,M,q,Richtung] = pwerte(Input,n1,samp,M,test,tail,alpha) is a subfunction in the main-function fdp.m.
For help use the main-function.


Copyright (C) 2006 by Claudia Hemmelmann <claudia.hemmelmann@mti.uni-jena.de>
Institute of Medical Statistics, Computer Sciences and Documantation
University of Jena
This work was supported by DFG Project VO 683/2-1
This is part of the BIOSIG-toolbox http://biosig.sf.net/


    BioSig is free software: you can redistribute it and/or modify
    it under the terms of the GNU General Public License as published by
    the Free Software Foundation, either version 3 of the License, or
    (at your option) any later version.

    BioSig is distributed in the hope that it will be useful,
    but WITHOUT ANY WARRANTY; without even the implied warranty of
    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
    GNU General Public License for more details.

    You should have received a copy of the GNU General Public License
    along with BioSig.  If not, see <http://www.gnu.org/licenses/>.



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 80

The function[P,M,q,Richtung] = pwerte(Input,n1,samp,M,test,tail,alpha) is a ...



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 8
signtest


# name: <cell-element>
# type: sq_string
# elements: 1
# length: 1076
 -- Function File: [PVAL, B, N] = signtest (X, Y, ALT)
     For two matched-pair samples X and Y, perform a sign test of the
     null hypothesis PROB (X > Y) == PROB (X < Y) == 1/2.  Under the
     null, the test statistic B roughly follows a binomial distribution
     with parameters ‘N = sum (X ~= Y)’ and P = 1/2.

     With the optional argument ‘alt’, the alternative of interest can
     be selected.  If ALT is ‘'~='’ or ‘'<>'’, the null hypothesis is
     tested against the two-sided alternative PROB (X < Y) ~= 1/2.  If
     ALT is ‘'>'’, the one-sided alternative PROB (X > Y) > 1/2 (’x is
     stochastically greater than y’) is considered.  Similarly for
     ‘'<'’, the one-sided alternative PROB (X > Y) < 1/2 (’x is
     stochastically less than y’) is considered.  The default is the
     two-sided case.  If X and Y are matrices (must have same size), the
     test is applied to each column.

     The p-value of the test is returned in PVAL.

     If no output argument is given, the p-value of the test is
     displayed.


# name: <cell-element>
# type: sq_string
# elements: 1
# length: 80
For two matched-pair samples X and Y, perform a sign test of the null
hypothe...



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 6
ttest3


# name: <cell-element>
# type: sq_string
# elements: 1
# length: 45
undocumented function: t = ttest3 (Input, n1)


# name: <cell-element>
# type: sq_string
# elements: 1
# length: 45
undocumented function: t = ttest3 (Input, n1)



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 6
ttestC


# name: <cell-element>
# type: sq_string
# elements: 1
# length: 37
undocumented function: t = ttestC (z)


# name: <cell-element>
# type: sq_string
# elements: 1
# length: 37
undocumented function: t = ttestC (z)



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 6
u_test


# name: <cell-element>
# type: sq_string
# elements: 1
# length: 907
 -- Function File: [PVAL, Z] = u_test (X, Y, ALT)
     For two samples X and Y, perform a Mann-Whitney U-test of the null
     hypothesis PROB (X > Y) == 1/2 == PROB (X < Y).  Under the null,
     the test statistic Z approximately follows a standard normal
     distribution.  Note that this test is equivalent to the Wilcoxon
     rank-sum test.

     With the optional argument string ALT, the alternative of interest
     can be selected.  If ALT is ‘'~='’ or ‘'<>'’, the null is tested
     against the two-sided alternative PROB (X > Y) ~= 1/2.  If ALT is
     ‘'>'’, the one-sided alternative PROB (X > Y) > 1/2 is considered.
     Similarly for ‘'<'’, the one-sided alternative PROB (X > Y) < 1/2
     is considered, The default is the two-sided case.

     The p-value of the test is returned in PVAL.

     If no output argument is given, the p-value of the test is
     displayed.


# name: <cell-element>
# type: sq_string
# elements: 1
# length: 80
For two samples X and Y, perform a Mann-Whitney U-test of the null
hypothesis...



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 5
umord


# name: <cell-element>
# type: sq_string
# elements: 1
# length: 47
undocumented function: [zahl, U] = umord (X, m)


# name: <cell-element>
# type: sq_string
# elements: 1
# length: 47
undocumented function: [zahl, U] = umord (X, m)



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 9
vereinM_A


# name: <cell-element>
# type: sq_string
# elements: 1
# length: 1356

The function [AaH,pup,adpval,q] = vereinM_A(Input,n1,samp,u,B,test,tail,alpha,k)
is a procedure used in the main-function fdp.m.
The function vereinM_A is called 'Av' for the procedure A (conservative) of Korn et al. (2004) in the main-function fdp. 
Use the main-function for help.
 

Copyright (C) 2006 by Claudia Hemmelmann <claudia.hemmelmann@mti.uni-jena.de>
Institute of Medical Statistics, Computer Sciences and Documantation
University of Jena
This work was supported by DFG Project VO 683/2-1
This is part of the BIOSIG-toolbox http://biosig.sf.net/


***
 This library is free software; you can redistribute it and/or
 modify it under the terms of the GNU Library General Public
 License as published by the Free Software Foundation; either
 Version 2 of the License, or (at your option) any later version.

 This library is distributed in the hope that it will be useful,
 but WITHOUT ANY WARRANTY; without even the implied warranty of
 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 Library General Public License for more details.

 You should have received a copy of the GNU Library General Public
 License along with this library; if not, write to the
 Free Software Foundation, Inc., 59 Temple Place - Suite 330,
 Boston, MA  02111-1307, USA.

--------------------------------------------------------------------------



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 80

The function [AaH,pup,adpval,q] = vereinM_A(Input,n1,samp,u,B,test,tail,alph...



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 9
vereinM_B


# name: <cell-element>
# type: sq_string
# elements: 1
# length: 1360

The function [AaH,pup,adpval,q] = vereinM_B(Input,n1,samp,gamma,B,test,tail,alpha,k)
is a procedure used in the main-function fdp.m.
The function vereinM_B is called 'Bv' for the procedure B (conservative) of Korn et al. (2004) in the main-function fdp. 
Use the main-function for help.
 

Copyright (C) 2006 by Claudia Hemmelmann <claudia.hemmelmann@mti.uni-jena.de>
Institute of Medical Statistics, Computer Sciences and Documantation
University of Jena
This work was supported by DFG Project VO 683/2-1
This is part of the BIOSIG-toolbox http://biosig.sf.net/


***
 This library is free software; you can redistribute it and/or
 modify it under the terms of the GNU Library General Public
 License as published by the Free Software Foundation; either
 Version 2 of the License, or (at your option) any later version.

 This library is distributed in the hope that it will be useful,
 but WITHOUT ANY WARRANTY; without even the implied warranty of
 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 Library General Public License for more details.

 You should have received a copy of the GNU Library General Public
 License along with this library; if not, write to the
 Free Software Foundation, Inc., 59 Temple Place - Suite 330,
 Boston, MA  02111-1307, USA.

--------------------------------------------------------------------------



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 80

The function [AaH,pup,adpval,q] = vereinM_B(Input,n1,samp,gamma,B,test,tail,...



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 13
wilcoxon_test


# name: <cell-element>
# type: sq_string
# elements: 1
# length: 973
 -- Function File: [PVAL, Z] = wilcoxon_test (X, Y, ALT)
     For two matched-pair sample vectors X and Y, perform a Wilcoxon
     signed-rank test of the null hypothesis PROB (X > Y) == 1/2.  Under
     the null, the test statistic Z approximately follows a standard
     normal distribution.

     With the optional argument string ALT, the alternative of interest
     can be selected.  If ALT is ‘'~='’ or ‘'<>'’, the null is tested
     against the two-sided alternative PROB (X > Y) ~= 1/2.  If alt is
     ‘'>'’, the one-sided alternative PROB (X > Y) > 1/2 is considered.
     Similarly for ‘'<'’, the one-sided alternative PROB (X > Y) < 1/2
     is considered.  The default is the two-sided case.  If X and Y are
     matrices (must have same size), the test is applied to each column.

     The p-value and z-score of the test are returned in PVAL and Z,
     resp.

     If no output argument is given, the p-value of the test is
     displayed.


# name: <cell-element>
# type: sq_string
# elements: 1
# length: 80
For two matched-pair sample vectors X and Y, perform a Wilcoxon
signed-rank t...



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 6
zahlen


# name: <cell-element>
# type: sq_string
# elements: 1
# length: 1223
 M1-1 Zufallszahlen aus dem Intervall [1,N]
 The function [g] = zahlen(M,N) is a subfunction in the main-function fdp.m.
For help use the main-function.


Copyright (C) 2006 by Claudia Hemmelmann <claudia.hemmelmann@mti.uni-jena.de>
Institute of Medical Statistics, Computer Sciences and Documantation
University of Jena
This work was supported by DFG Project VO 683/2-1
This is part of the BIOSIG-toolbox http://biosig.sf.net/

***
 This library is free software; you can redistribute it and/or
 modify it under the terms of the GNU Library General Public
 License as published by the Free Software Foundation; either
 Version 2 of the License, or (at your option) any later version.

 This library is distributed in the hope that it will be useful,
 but WITHOUT ANY WARRANTY; without even the implied warranty of
 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 Library General Public License for more details.

 You should have received a copy of the GNU Library General Public
 License along with this library; if not, write to the
 Free Software Foundation, Inc., 59 Temple Place - Suite 330,
 Boston, MA  02111-1307, USA.

--------------------------------------------------------------------------



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 80
 M1-1 Zufallszahlen aus dem Intervall [1,N]
 The function [g] = zahlen(M,N) i...



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 10
zweistufen


# name: <cell-element>
# type: sq_string
# elements: 1
# length: 1388

 The function [AaH,pup,adpval] = zweistufen(psd,indexsd,k,alpha) is a 
 subfunction in fdr.m.
 In fdr.m is zweistufen.m used as an procedure named 'BKY' for 
 Benjamini. Krieger and Yekutieli (2001).
 For help use the main-function fdr.m.

 REFERENCES:

 [1] Hemmelmann C, Horn M, Suesse T, Vollandt R, Weiss S.
	New concepts of multiple tests and their use for evaluating 
	high-dimensional EEG data.
	J Neurosci Methods. 2005 Mar 30;142(2):209-17.

 [2]

 Copyright (C) 2006 Claudia Hemmelmann <claudia.hemmelmann@mti.uni-jena.de>
 Adapted by A Schloegl <alois.schloegl@gmail.com> Dec 2006

***
 This library is free software; you can redistribute it and/or
 modify it under the terms of the GNU Library General Public
 License as published by the Free Software Foundation; either
 Version 2 of the License, or (at your option) any later version.

 This library is distributed in the hope that it will be useful,
 but WITHOUT ANY WARRANTY; without even the implied warranty of
 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 Library General Public License for more details.

 You should have received a copy of the GNU Library General Public
 License along with this library; if not, write to the
 Free Software Foundation, Inc., 59 Temple Place - Suite 330,
 Boston, MA  02111-1307, USA.

--------------------------------------------------------------------------



# name: <cell-element>
# type: sq_string
# elements: 1
# length: 80

 The function [AaH,pup,adpval] = zweistufen(psd,indexsd,k,alpha) is a 
 subf...





