Ignore:
Timestamp:
Sep 14, 2006, 5:04:17 AM (15 years ago)
Author:
Peter
Message:

fixes #133 removed all errors reported from Doxygen. Only one error left which says Index is not documented but I don't want it to be documented actually we use the Doxygens preprocessor to skip documenting that class, yet Doxygen complains that class is not documented huh. Only solution would be to move that class to its own file and not keep it together with SVM.

File:
1 edited

Legend:

Unmodified
Added
Removed
  • trunk/c++_tools/statistics/Fisher.h

    r623 r648  
    1111namespace theplu {
    1212namespace statistics { 
    13   ///
    14   /// @brief Fisher's exact test.   
    15   /// Fisher's Exact test is a procedure that you can use for data
    16   /// in a two by two contingency table: \f[ \begin{tabular}{|c|c|}
    17   /// \hline a&b \tabularnewline \hline c&d \tabularnewline \hline
    18   /// \end{tabular} \f] Fisher's Exact Test is based on exact
    19   /// probabilities from a specific distribution (the hypergeometric
    20   /// distribution). There's really no lower bound on the amount of
    21   /// data that is needed for Fisher's Exact Test. You do have to
    22   /// have at least one data value in each row and one data value in
    23   /// each column. If an entire row or column is zero, then you
    24   /// don't really have a 2 by 2 table. But you can use Fisher's
    25   /// Exact Test when one of the cells in your table has a zero in
    26   /// it. Fisher's Exact Test is also very useful for highly
    27   /// imbalanced tables. If one or two of the cells in a two by two
    28   /// table have numbers in the thousands and one or two of the
    29   /// other cells has numbers less than 5, you can still use
    30   /// Fisher's Exact Test. For very large tables (where all four
    31   /// entries in the two by two table are large), your computer may
    32   /// take too much time to compute Fisher's Exact Test. In these
    33   /// situations, though, you might as well use the Chi-square test
    34   /// because a large sample approximation (that the Chi-square test
    35   /// relies on) is very reasonable. If all elements are larger than
    36   /// 10 a Chi-square test is reasonable to use.
    37   ///
    38   /// @note The statistica assumes that each column and row sum,
    39   /// respectively, are fixed. Just because you have a 2x2 table, this
    40   /// assumtion does not necessarily match you experimental upset. See
    41   /// e.g. Barnard's test for alternative.
    42   ///
     13  /**
     14     @brief Fisher's exact test.   
     15
     16     Fisher's Exact test is a procedure that you can use for data
     17     in a two by two contingency table: \f[ \begin{tabular}{|c|c|}
     18     \hline a&b \tabularnewline \hline c&d \tabularnewline \hline
     19     \end{tabular} \f] Fisher's Exact Test is based on exact
     20     probabilities from a specific distribution (the hypergeometric
     21     distribution). There's really no lower bound on the amount of
     22     data that is needed for Fisher's Exact Test. You do have to
     23     have at least one data value in each row and one data value in
     24     each column. If an entire row or column is zero, then you
     25     don't really have a 2 by 2 table. But you can use Fisher's
     26     Exact Test when one of the cells in your table has a zero in
     27     it. Fisher's Exact Test is also very useful for highly
     28     imbalanced tables. If one or two of the cells in a two by two
     29     table have numbers in the thousands and one or two of the
     30     other cells has numbers less than 5, you can still use
     31     Fisher's Exact Test. For very large tables (where all four
     32     entries in the two by two table are large), your computer may
     33     take too much time to compute Fisher's Exact Test. In these
     34     situations, though, you might as well use the Chi-square test
     35     because a large sample approximation (that the Chi-square test
     36     relies on) is very reasonable. If all elements are larger than
     37     10 a Chi-square test is reasonable to use.
     38     
     39     @note The statistica assumes that each column and row sum,
     40     respectively, are fixed. Just because you have a 2x2 table, this
     41     assumtion does not necessarily match you experimental upset. See
     42     e.g. Barnard's test for alternative.
     43  */
    4344 
    4445  class Fisher : public Score
Note: See TracChangeset for help on using the changeset viewer.