Abstract:
A method and system for computing statistical parameters for sets of data items, by executing instructions of a computer program that is coded within a spreadsheet. Each set is generated in a time sequence that is specific to each set. For each time sequence, each data item is one data value or a pair of data values. The data items appears one-at-a-time in only one cell structure of the spreadsheet at each time in the time sequence. The one cell structure is a single cell or two cells. A loop of iterations is performed for each set. In each iteration, a command is responded to by updating the statistical parameters based on the latest data item in the one cell structure in the spreadsheet. The updated statistical parameter are stored in a parameter field of the spreadsheet assigned to each statistical parameter.

Description:
BACKGROUND OF THE INVENTION 
     1. Technical Field 
     The present invention relates generally to the field of information processing by digital computers, and more particularly to a method and system, in an electronic spreadsheet, for computing statistical data on a set of values taken over time either by a given cell or by a pair of cells. 
     2. Related Art 
     Before computers, numerical analyses, particularly financial analyses, were usually prepared on an accountant&#39;s columnar pad or spreadsheet, with pencil and calculator in hand. By organizing data into columns and rows, spreadsheets afford the rapid assimilation of information by a reader. The task of preparing a spreadsheet on paper, however, is not quite so fast. Instead, the process tends to be very slow, as each entry must be tediously calculated and entered into the spreadsheet. Manually prepared spreadsheets are also prone to errors. Hence, preparation of spreadsheets by hand is slow, tedious, and unreliable. 
     With the advent of microcomputers, a solution was forthcoming in the form of “electronic spreadsheets.” Better known simply as “spreadsheets,” these software programs provide a computerized replacement for the traditional financial modelling tools: the accountant&#39;s columnar pad, pencil, and calculator. In some regards, spreadsheet programs are to those tools what word processors are to typewriters. Spreadsheets offer dramatic improvements in ease of creating, editing, and using financial models. 
     A typical spreadsheet program configures the memory of a computer to resemble the column/row or grid format of an accountant&#39;s columnar pad, thus providing a visible calculator for a user. Because this “pad” exists dynamically in the computer&#39;s memory, however, it differs from paper pads in several important ways. Locations in the electronic spreadsheet, for example, must be communicated to the computer in a format which it can understand. A common scheme for accomplishing this is to assign a number to each row in a spreadsheet, and a letter to each column. To reference a location at column A and row  1  (i.e., the upper-left-hand corner), for example, the user types in “A1”. In this manner, the spreadsheet defines an addressable storage location or “cell” at each intersection of a row with a column. 
     Data entry into an electronic spreadsheet occurs in much the same manner that information would be entered on an accountant&#39;s pad. After a screen cursor is positioned at a desired location, the user can enter alphanumeric information. Besides holding text and numeric information, however, spreadsheet cells can store special instructions or “formulas” specifying calculations to be performed on the numbers stored in spreadsheet cells. In this fashion, cell references can serve as variables in an equation, thereby allowing precise mathematical relationships to be defined between cells. The structure and operation of a spreadsheet program, including advanced functions such as functions and macros, are documented in the technical, trade, and patent literature. For an overview, see e.g., Cobb, S.,  Using Quattro Pro  2, Borland-OsbomeIMcGraw-Mll, 1990; and LeBlond, G. and Cobb, D.,  Using  1-2-3, Que corp., 1985. The disclosures of each of the foregoing are hereby incorporated by reference. 
     Electronic spreadsheets offer many advantages over their paper counterparts. For one, electronic spreadsheets are much larger (i.e., hold more information) than their paper counterparts; electronic spreadsheets having thousands or even millions of cells are not uncommon. Spreadsheet programs also allow users to perform “what-if” scenarios. After a set of computational relationships has been entered into a worksheet, thanks to imbedded formulas for instance, the spread of information can be recalculated using different sets of assumptions, with the results of each recalculation appearing almost instantaneously. Performing this operation manually, with paper and pencil, would require the recalculation of every relationship in the model with each change made. Electronic spreadsheet systems are well suited to solve “what-if’ problems, that is, changing an input and seeing what happens to an output. 
     Electronic spreadsheets have become a tool of choice for computing statistics from a set of data. For a set of data arranged in a column, conventional electronic spreadsheet tools include means, in the form of statistical functions, to compute the average of the data set, or the maximum value of the data set, or the minimum value of the data set, or the standard deviation of the data set. For a couple of data ranges arranged for instance as a pair of columns, conventional electronic spreadsheet tools include means, in the form of statistical functions, to compute the covariance of the two data sets, or the correlation of the two data sets. When electronic spreadsheets are used to perform simulations of a model (business model, or industrial model, or nature life model), these statistical functions are very useful for deriving statistical information relative to the different simulation instances of the modelled process. Typically such simulations are performed by feeding a model with inputs which can either be randomly generated, or imported from external sources. Unfortunately these statistical functions operate on the base of a set of data, recorded within data ranges, so that each simulation must be first properly recorded onto a simulation result array, to eventually build a complete array of results upon which the statistical functions can operate. When the number of simulations increases (this is required to increase the confidence in the statistical results), the volume of information that may result may be prohibitive (and even reach the built-in limitations of the commercially available electronic spreadsheet tools). As the desired information relies to the statistical data, and not to each individual simulation output, the conventional statistical means available in electronic spreadsheet environment, are not suited for computing simulation statistics. 
     SUMMARY OF THE INVENTION 
     The present invention provides a method for computing at least one statistical parameter for at least one set of data items, said method comprising performing a loop having a plurality of iterations for each set of data items, said method being performed by execution of instructions by a processor of a computer system, said instructions comprised by a computer program that is coded within a spreadsheet, said spreadsheet being stored in a memory of the computer system, each set of data items having been generated in a time sequence such that each data item corresponds to a unique time in the time sequence, said time sequence being specific to each set of data items, for each time sequence each data item consisting of one data value or a pair of data values, the data items for each time in the time sequence appearing one-at-a-time in only one cell structure C of the spreadsheet in accordance with the time sequence, the one cell structure C consisting of a single cell or both a first cell and a second cell corresponding respectively to the one data value or the pair of data values, each iteration of each loop comprising: 
     receiving a command to update the at least one statistical parameter for a set S of the at least one set, said command identifying the cell structure C pertaining to the set S, said cell structure C comprising a latest data item of the set S, said spreadsheet not comprising any other data item of the set S, said latest data item corresponding to a latest time in the time sequence of the set S; 
     responsive to said command, updating the at least one statistical parameter for the set S based on the latest data item in the cell structure C to generate an updated at least one statistical parameter value for the set S; and 
     storing each updated statistical parameter value for the set S in a parameter field of the spreadsheet assigned to each statistical parameter. 
     The present invention provides a computer system comprising a processor and a memory, a spreadsheet being stored in the memory, said spreadsheet having a computer program coded therein, said computer program comprising instructions that when executed by the processor perform a method for computing at least one statistical parameter for at least one set of data items, each set of data items having been generated in a time sequence such that each data item corresponds to a unique time in the time sequence, said time sequence being specific to each set of data items, for each time sequence each data item consisting of one data value or a pair of data values, the data items for each time in the time sequence appearing one-at-a-time in only one cell structure C of the spreadsheet in accordance with the time sequence, the one cell structure C consisting of a single cell or both a first cell and a second cell corresponding respectively to the one data value or the pair of data values, said method comprising performing a loop having a plurality of iterations for each set of data items, each iteration of each loop comprising: 
     receiving a command to update the at least one statistical parameter for a set S of the at least one set, said command identifying the cell structure C pertaining to the set S, said cell structure C comprising a latest data item of the set S, said spreadsheet not comprising any other data item of the set S, said latest data item corresponding to a latest time in the time sequence of the set S; 
     responsive to said command, updating the at least one statistical parameter for the set S based on the latest data item in the cell structure C to generate an updated at least one statistical parameter value for the set S; and 
     storing each updated statistical parameter value for the set S in a parameter field of the spreadsheet assigned to each statistical parameter. 
     The present invention provides a computer program comprising instructions that when executed by a processor of a computer system perform a method for computing at least one statistical parameter for at least one set of data items, said computer program being coded within a spreadsheet, said spreadsheet being stored in a memory of the computer system, each set of data items having been generated in a time sequence such that each data item corresponds to a unique time in the time sequence, said time sequence being specific to each set of data items, for each time sequence each data item consisting of one data value or a pair of data values, the data items for each time in the time sequence appearing one-at-a-time in only one cell structure C of the spreadsheet in accordance with the time sequence, the one cell structure C consisting of a single cell or both a first cell and a second cell corresponding respectively to the one data value or the pair of data values, said method comprising performing a loop having a plurality of iterations for each set of data items, each iteration of each loop comprising: 
     receiving a command to update the at least one statistical parameter for a set S of the at least one set, said command identifying the cell structure C pertaining to the set S, said cell structure C comprising a latest data item of the set S, said spreadsheet not comprising any other data item of the set S, said latest data item corresponding to a latest time in the time sequence of the set S; 
     responsive to said command, updating the at least one statistical parameter for the set S based on the latest data item in the cell structure C to generate an updated at least one statistical parameter value for the set S; and 
     storing each updated statistical parameter value for the set S in a parameter field of the spreadsheet assigned to each statistical parameter. 
     From a memory consumption and computing power consumption standpoint, the present invention is much more efficient than conventional means available in electronic spreadsheet environments. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The present invention will best be understood by reference to the following detailed description of an illustrative detailed embodiment when read in conjunction with the accompanying drawings. 
         FIG. 1A  is a block diagram of a computer system in which the present invention can be embodied. 
         FIG. 1B  is a block diagram of a software system including an operating system, an application software, and a user interface for carrying out the present invention. 
         FIG. 1C  illustrates the basic architecture and functionality of a graphical user interface in which the present invention may be embodied. 
         FIG. 2A  shows a spreadsheet notebook interface used in the accordance with the present invention. 
         FIG. 2B  shows the toolbar component of the notebook interface shown in  FIG. 2A . 
         FIGS. 2C and 2D  show page identifiers for rapidly accessing and manipulating individual pages of the notebook interface shown in  FIG. 2A . 
         FIG. 3  illustrates the structure of the “Single Over Time Working Zone” and of the “Double Over Time Working Zone” used in embodiments of the present invention. 
         FIG. 4  is a flow chart illustrating the method for managing over time statistics to take according to the present invention. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     The present invention is directed to a method, system, and computer program for managing and/or computing statistical information based on a set of values taken by a given cell or by a given pair of cells of a spreadsheet. The present invention comprises means for controlling, for a given cell or a given pair of cells, the set of values upon which the statistical computing is performed. 
     When invoked in a first mode called “Reset mode”, the method re-initializes the computing of statistical information, to get rid of any past history. 
     When invoked in a second mode, called “Run mode”, the method computes the statistical information based on the current value of the given cell or of the given pair of cells, and of the past historical values taken during the current “Run mode”. 
     The method according to the present invention, for use in a multi-dimensional spreadsheet comprising a plurality of cells identified by a cell address along each dimension, comprises the steps of: 
     receiving a command for computing statistical data based on successive values of a first cell over a time period, said command comprising: (1) means for identifying said first cell, (2) means for determining the beginning and the end of the time period, and (3) a reference to a statistical function for computing statistical data based on the successive values of said first cell over said time period; and 
     computing statistical data based on the successive values of said first cell over said time period, said computing statistical data comprising the further steps of, each time the value of said first cell is updated: (1) computing said statistical data by means of said statistical function, based on: the current value of said first cell, and the previously computed statistical data based on the successive values taken by the first cell from the beginning of the time period; and (2) storing the computed statistical data in place of the previously computed statistical data. 
     The present invention discloses an Over Time Statistic Manager (OTSM) handling the management and computation of statistical information, based on the values taken either by a single cell, or by a pair of cells. 
     The present invention solves the problem of the related art by recursively evaluating the desired statistical information, only on the base of the last simulation, thus avoiding to keep a high volume array of all simulations results. 
     Hardware 
     As shown in  FIG. 1A , the present invention may be embodied on a computer system  100  comprising a central processor  101 , a main memory  102 , an input/output controller  103 , a keyboard  104 , a pointing device  105  (e.g., mouse, track ball, pen device, or the like), a display device  106 , and a mass storage  107  (e.g., hard disk). Additional input/output devices, such as a printing device  108 , may be included in the system  100  as desired. As illustrated, the various components of the system  100  communicate through a system bus  110  or similar architecture. In an embodiment, the computer system  100  includes an IBM-compatible personal computer, which is available from several vendors (including IBM of Armonk, N.Y.). 
     Illustrated in  FIG. 1B , a computer software system  150  is provided for directing the operation of the computer system  100 . Software system  150 , which is stored in system memory  102  and on disk memory  107 , includes a kernel or operating system  151  and a shell or interface  153 . One or more application programs, such as application software  152 , may be “loaded’ (i.e., transferred from storage  107  into memory  102 ) for execution by the system  100 . The system  100  receives user commands and data through user interface  153 ; these inputs may then be acted upon by the system  100  in accordance with instructions from operating module  151  and/or application module  152 . The interface  153 , which is preferably a graphical user interface (GUI), also serves to display results, whereupon the user may supply additional inputs or terminate the session. In an embodiment, operating system  151  and interface  153  are Microsoft Win95, available from Microsoft Corporation of Redmond, Wash. Application module  152 , on the other hand, includes a spreadsheet notebook of the present invention as described in further detail herein below. 
     Interface 
     The following description will focus on the embodiments of the present invention, which are embodied in spreadsheet applications operative in the Microsoft Windows environment. The present invention, however, is not limited to any particular application or any particular environment. Instead, those skilled in the art will find that the system and methods of the present invention may be advantageously applied to a variety of system and application software, including database management systems, word processors, and the like. Moreover, the present invention may be embodied on a variety of different platforms, including Macintosh, UNIX, NextStep, and the like. ‘Therefore, the description of the exemplary embodiments which follows is for purposes of illustration and not limitation. 
     Referring now to  FIG. 1C , the system  100  includes a windowing interface or workspace  160 . Window  160  is a rectangular, graphical user interface (GUI) for display on screen  106 ; additional windowing elements may be displayed in various sizes and formats (e.g., tiled or cascaded), as desired. At the top of window  160  is a menu bar  170  with a plurality of user-command choices, each of which may invoke additional submenus and software tools for use with application objects. Window  160  includes a client area  180  for displaying and manipulating screen objects, such as graphic object  181  and text object  182 . In essence, the client area is a workspace or view port for the user to interact with data objects which reside within the computer system  100 . 
     Windowing interface  160  includes a screen cursor or pointer  185  for selecting and otherwise invoking screen objects of interest. In response to user movement signals from the pointing device  105 , the cursor  185  floats (i.e., freely moves) across the screen  106  to a desired screen location. During or after cursor movement, the user may generate user-event signals (e.g., mouse button “clicks” and “drags”) for selecting and manipulating objects, as is known in the art. For example, Window  160  may be closed, resized, or scrolled by “clicking” (selecting) screen components  172 ,  174 / 5 , and  177 / 8 , respectively. 
     In an embodiment, screen cursor  185  is controlled with a mouse device. Single-button, double-button, or triple-button mouse devices are available from a variety of vendors, including Apple Computer of Cupertino, Calif., Microsoft Corporation of Redmond, Wash., and Logitech Corporation of Fremont, Calif., respectively. The screen cursor control device  105  may be a two-button mouse device, including both right and left “mouse buttons.” 
     Programming techniques and operations for mouse devices are well documented in the programming and hardware literature; see e.g.,  Microsoft Mouse Programmer&#39;s Reference , Microsoft Press, 1989. The general construction and operation of a GUI event-driven system, such as Windows, is also known in the art. See, e.g., Petzold, C.,  Programming Windows , Second Edition, Microsoft Press, 1990. The disclosures of each are hereby incorporated by reference. 
     Shown in  FIG. 2A , a spreadsheet notebook interface of the present invention will now be described. The spreadsheet notebook or workbook of the present invention includes a notebook workspace  200  for receiving, processing, and presenting information, including alphanumeric as well as graphic information. Notebook workspace  200  includes a menu bar  210 , a toolbar  220 , a current cell indicator  230 , an input line  231 , a status line  240 , and a notebook window  250 . The menu bar  210  displays and invokes, in response to user inputs, a main level of user commands. Menu  210  also invokes additional pull down menus, as is known in windowing applications. Input line  231  accepts user commands and information for the entry and editing of cell contents, which may include data, formulas, macros, and the like. Indicator  230  displays an address for the current cursor (i.e., active cell) position. At the status line  240 , system  100  displays information about the current state of the workbook. For example, a “READY” indicator means that the system is ready for the user to select another task to be performed. 
     The toolbar  220 , shown in further detail in  FIG. 2B , comprises a row or palette of tools which provide a quick way for the user to choose commonly-used menu commands or properties, In an exemplary embodiment, toolbar  220  includes file manipulation buttons  221 , printing buttons  222 , an undo button  223 , cut, copy, and paste buttons  224 , information pop-up window buttons tool  225 , a range selection button  226 , a style copy button  227 , a column resizing button  228 , and a sum button  229 . The functions of these buttons are suggested by their names. For instance, buttons  224  cut, copy and paste data and objects to and from Windows&#39; clipboard. The same actions are also available as corresponding commands in the Edit menu (available from menu bar  210 ). 
     The notebook, which provides an interface for entering and displaying information of interest, includes a plurality of spreadsheet pages. Each page may include conventional windowing features and operations, such as moving, resizing, and deleting. In an embodiment, the notebook includes 256 spreadsheet pages, all of which are saved as a single disk file on the mass storage  107 . Workspace  200  may display one or more notebooks, each sized and positioned (e.g., tiled, overlapping, and the like) according to user-specified constraints. 
     Each spreadsheet page of a notebook includes a 2-D spread. Page A from the notebook  200 , for example, includes a grid in row and column format, such as row  3  and column F. At each row/column intersection, a box or cell (e.g., cell C 4 ) is provided for entering, processing, and displaying information in a conventional manner. Each cell is addressable, with a selector being provided for indicating a currently active cell (i.e., the cell that is currently selected). 
     As shown in  FIGS. 2C and 2D , individual notebook pages are identified by page identifiers  260   a  and  260   b , respectively, which may be located along one edge of a notebook. In an embodiment, each page identifier is in the form of a tab member (e.g., members  261   a ,  262   a ,  263   a ) situated along a top edge of the notebook. Each tab member may include representative indicia, such as textual or graphic labels, including user selected titles representing the contents of a corresponding page. In  FIG. 2C , the tab members  260  are set to their respective default names. For example, the first three tab members (members  261   a ,  262   a ,  263   a ) are respectively set to A, B, and C. Tab members are typically given descriptive names provided by the user. As shown in  FIG. 2D , for example, the first three tab members have now been set to “Contents” (tab member  261   b ), “Summary” (tab member  262   b ), and “Jan” (tab member  263   b ). In a similar manner, the remaining tabs are set to subsequent months of the year. In this manner, the user associates the page identifiers with familiar tabs from an ordinary paper notebook. Thus, the user already knows how to select a page or spread of interest: simply select the tab corresponding to the page (as one would do when selecting a page from a paper notebook). 
     In addition to aiding in the selection of an appropriate page of information, the user-customizable page identifiers serve to aid in the entry of spreadsheet formulas. For example, when entering a formula referring to cells on another page, the user may simply use the descriptive page name in the formula itself (as described herein below), thus making it easier for the user to understand the relationship of the cell(s) or information being referenced. 
     A general description of the features and operation of the spreadsheet notebook interface may be found in Quattro Pro for Windows ( Getting Started, User&#39;s Guide and Building Spreadsheet Applications ), available from Borland International. 
     Management Over Time Statistics 
     In contrast with just-described conventional tools, the present invention provides a more powerful, less resource-demanding approach for managing and computing statistical data based on the set or sequence of values taken by a given cell or a pair of cells. The method according to the present invention comprises the following five steps: 
     The first step is building a model of the desired process, based on formulas and functions used in selected cells or ranges of cells. Such a model may be fed by input cells which can correspond to random number generators (also available as standard built-in functions). 
     The second step is identifying the one or plurality of cells of interest, referred to as “Output Cells” (OC), which deserve a statistical analysis. For instance it may be desired to compute, for the sequence of simulations, the standard deviation of a cell OC 1 , the standard deviation of a cell OC 2 , and the covariance between the cells OC 1  and OC 2 . 
     The third step is initializing selected cells with a new set of functions, Over Time Statistical Functions (OTSF), computing the desired statistical information. Such functions are easy to master as being direct derivatives of the conventional statistical functions. If the invocation of a conventional statistical function is “@FCT(argument_list)”, then the invocation of the corresponding OTS function is “@OTFCT(Reset, argument_list)”, where the additional argument “Reset” points to a Boolean cell playing the role of a function reset. In the example herein: (1) a first cell will be filled with the formula “@OTSTD(Reset, OC1)”; (2) a second cell will be filled with the formula “@OTSTD(Reset, OC2)”; and (3) a third cell will be filled with the formula “@OTCOV(Reset, OC1, OC2)”. The value of the cell “Reset” is set to FALSE, in order to prevent the re-initialization of the history (see next step). 
     The fourth step is entering a loop for running a sequence of simulations according to the modeled processes. Each simulation corresponds to an iteration of the loop. Such a loop can easily be implemented by simple macros. Each iteration of the loop includes: (1) feeding the model with a new set of input cells (e.g., by forcing a spreadsheet recalculation if input cells contains random number generators); and (2) checking for the end of the loop and resume the loop if its end is not reached. It is noted that this loop is much simpler to write than the one of the conventional scenario, which requires managing an array of simulation results. 
     In the fifth step, should the user want to run another set of simulations, then the user should first set the value of the cell named “Reset” equal to TRUE, and then set the value of the cell named “Reset” equal to FALSE. 
     With this scenario, no simulation table is created and managed. Therefore much less computing resources are required, and the associated capacity constraints are removed. Furthermore the loop of the fourth step above is quite simple, typically of the form: For I=1 to N; Application.recalc; EndFor. 
     The Over Time Statistic Manager (OTSM) is the entity managing the Over Time Statistical Functions. In an embodiment of the present invention assuming a Lotus 123 environment, the following OTSF are considered:
         @OTMAX(reset, cell 1 ): for computing the maximum value taken over time by cell 1 ,   @OTMIN(reset, cell 1 ): for computing the minimum value taken over time by cell 1 ,   @OTAVG(reset, cell 1 ): for computing the average value taken over time by cell 1 ,   @OTSTD(reset, cell 1 ): for computing the standard deviation of the values taken over time by cell 1 ,   @OTCOV(reset, cell 1 , cell 2 ): for computing the covariance between the values taken over time by cell 1  and cell 2 ,   @OTCORREL(reset, cell 1 , cell 2 ): for computing the correlation between the values taken over time by cell 1  and cell 2 ,
 
where:
   “reset” is the name or the address of an individual cell used to reset the computation of statistical information,   “cell1” and “cell2” are the names or addresses of two individual cells whose set or sequence of values is the base for computing statistical information.       

     Other similar OTSF could be defined without departing from the spirit of the present invention. 
     The OTSM takes control each time an OTSF is invoked. The OTSM handles two types of internal tables:
         a Single Over Time Working Zone (SOTWZ) and   a Double Over Time Working Zone (DOTWZ),
 
as described in the following section.
       

     For each pair (reset, cell 1 ) passed as argument of an OTSF is created a SOTWZ  300  the structure of which is described in  FIG. 3 . Thus for a SOTWZ, the set or sequence S of data items being statistically processed consists of one data value (identified by cell 1 ) for each time in the time sequence of data items in the set S. A SOTWZ  300  comprises the following fields:
         a “Ptr” field  301  pointing to the address of the cell “cell1” associated to the SOTWZ  300     an “Index” field  302  counting the number of samples used to compute the output of the OTSF,   “max” field  303  recording the highest value of the cell “cell1” associated to the SOTWZ  300 ,   a “min” field  304  recording the lowest value of the cell “cell1” associated to the SOTWZ  300 ,   an “avg” field  305  recording the average value of the cell “cell1” associated to the SOTWZ  300 ,   a “sqavg” field  306  recording the average of the square value of the cell “cell1” associated to the SOTWZ  300 ,   A “reset” field  307  pointing to the cell “reset” associated to the SOTWZ  300 .       

     For each triple (reset, cell 1 , cell 2 ) passed as argument of an OTSF is created a DOTWZ  310  the structure of which is described in  FIG. 3 . Thus for a DOTWZ, the set or sequence S of data items being statistically processed consists of a pair of data values (identified by cell 1  and cell 2 ) for each time in the time sequence of data items in the set S. A DOTWZ  310  comprises the following fields:
         a “Ptr1” field  311  pointing to the address of the cell “cell1” associated to the DOTWZ  310 ,   a “Ptr2” field  312  pointing to the address of the cell “cell2” associated to the DOTWZ  310 ,   an “Index” field  313  counting the number of samples used to compute the output of the OTSF,   a “reset” field  314  pointing to the cell “reset” associated to the DOTWZ  310 ,   an “avg1” field  315  recording the average value of the cell “cell1” associated to the DOTWZ  310 ,   an “avg2” field  316  recording the average value of the cell “cell2” associated to the DOTWZ  310 ,   a “sqavg1” field  317  recording the average of the square value of the cell “cell1” associated to the DOTWZ  310 ,   a “sqavg2” field  318  recording the average of the square value of the cell “cell2” associated to the DOTWZ  310 ,   a “prod” field  319  recording the average of the product of the values of the cells “cell1” and “cell2” associated to the DOTWZ  310 .       

     The method for managing OTDF according to the present invention is summarized in the flowchart of  FIG. 4 . This OTSM method can be seen as the processing of an OTSF. 
     The method for managing OTDF according to the present invention is summarized in flowchart  400  of  FIG. 4 . This OTSM method can be seen as the processing of an OTSF. 
       FIG. 4  depicts a loop, wherein each iteration of the loop comprises steps  401 - 410 . The loop splits at step  404  into a first path of steps  405 - 409  (implementing a SOTWZ) and a second path of steps  411 - 415  (implementing a DOTWZ). The first and second paths converge at step  410  which is the last step of the loop. 
     At step  401 , the method is in its default state, waiting for an event to initiate the process. 
     At step  402 , an event is detected, as a result of an invocation of an OTSF. 
     At step  403 , the arguments of the OTSF are retrieved (first argument under the name “reset”, the second argument under the name “cell1”, the third argument, if present, under the name “cell2”). The address or cell name contained in “cell1” (and “cell2” if present) identifies the particular sequence (S) of data items being statistically processed in the current iteration of the loop. 
     A cell structure C stores a data item of the latest data value(s) in the set or sequence S. The cell structure C for storing the latest data value(s) is “cell1” for a SOTWZ. The cell structure C for storing the latest data value(s) is both “cell1” and “cell2” for a DOTWZ. Since the variables “cell1” (and “cell2” if present) are received in each iteration of the loop, different iterations of the loop may pertain to the same or different sequences of data being statistically processed depending on whether the values of “cell1” (and “cell2” if present) are the same or different in the different iterations. 
     For example, consider a first set or sequence (S 1 ) of data items and a second set or sequence (S 2 ) of data items being statistically processed by looping in accordance with  FIG. 4 . After performing a first iteration of the loop for the set S 1  and after performing a first iteration of the loop for the set S 2  a last iteration of the loop for the set S 1  may be performed to end the loop of the set S 1 , and a last iteration of the loop for the set S 2  may be performed to end the loop of the set S 2 . Note that in one embodiment each data item in the set S 1  may consist of one data value (identified by “cell1”) corresponding to an iteration of a SOTWZ implemented in steps  405 - 409 , and each data item in the set S 2  may consist of a pair of data values (identified by “cell1” and “cell2”) corresponding to an iteration of a DOTWZ implemented in steps  411 - 415 . 
     At step  404 , a test is performed to check if a third argument cell 2  was present. If it is the case, then control is given to step  411  for implementing a DOTWZ; otherwise control is given to step  405  for implementing a SOTWZ. 
     At step  405  a test is performed to check if an SOTWZ  300  associated to the cell pair (reset, cell 1 ) is already defined. If it is the case, then control is given to step  407 ; otherwise control is given to step  406 . 
     At step  406 , a new SOTWZ  300  is created and initialized with the following fields:
         the “Ptr” field  301  is initialized with a pointer to the cell cell 1 ,   the “Index” field  302  is initialized with a zero value,   the “max” field  303  is initialized with the value of the cell cell 1 ,   the “min” field  304  is initialized with the value of the cell cell 1 ,   the “avg” field  305  is initialized with the value of the cell cell 1 ,   the “sqavg” field  306  is initialized with the square of the value of the cell cell 1 ,   the “reset” field  307  is initialized with a pointer to the cell “reset”.       

     At step  407 , a test is performed to check if reset is equal to TRUE. If it is the case, then control is given to step  408 ; otherwise control is given to step  409 . 
     At step  408 , the SOTWZ  300  is reset with the following actions on the fields:
         the “Index” field  302  is initialized with a zero value,   the “max” field  303  is initialized with the value of the cell cell 1 ,   the “min” field  304  is initialized with the value of the cell cell 1 ,   the “avg” field  305  is initialized with the value of the cell cell 1 ,   the “sqavg” field  306  is initialized with the square of the value of the cell cell 1 .       

     At step  409 , the SOTWZ  300  is refreshed with the following actions on the fields:
         the “max” field  303  is set equal to max(max, cell 1 ),   the “min” field  304  is set equal to min(min, cell 1 ),   the “avg” field  305  is set equal to (index*avg+cell 1 )/(index+1),   the “sqavg” field  306  is set equal to (index*sqavg+cell 1 *cell 1 )/(index+1),   the “Index” field  302  is set equal to index+1.       

     At step  410 , the method returns the result of the OTSF function, depending on this function, 
     as listed below: 
     
         
         
           
             @OTMAX(reset,cell 1 )=max; 
             @OTMIN(reset,cell 1 )=min; 
             @OTAVG(reset, cell 1 )=avg 
             @OTSTD(reset, cell 1 )=sqrt(sqavg−avg*avg) 
             @OTCOV(reset, cell 1 , cell 2 )=prod−avg 1 *avg 2   
             @OTCORREL(reset, cell 1 , cell 2 )=(prod−avg 1 *avg 2 )/sqrt(sqavg 1 −avg 1 *avg 1 )/sqrt(sqavg 2 −avg 2 *avg 2 ) 
           
         
       
    
     Then control is returned back to the initial step  401  for handling another OTSF command for initiating execution of another iteration of a loop for a set or sequence of data items. 
     At step  411 , a test is performed to check if an DOTWZ  310  associated with the cell triple (reset, cell 1 , cell 2 ) is already defined. If it is the case, then control is given to step  413 ; otherwise control is given to step  412 . 
     At step  412 , a new DOTWZ  310  is created and initialized with the following fields:
         the “Ptr1” field  311  is initialized with a pointer to the cell cell 1 ,   the “Ptr2” field  312  is initialized with a pointer to the cell cell 2 ,   the “Index” field  313  is initialized with a zero value,   the “reset” field  314  is initialized with a pointer to the cell reset,   the “avg1” field  315  is initialized with the value of the cell cell 1 ,   the “avg2” field  316  is initialized with the value of the cell cell 2 ,   the “sqavg1” field  317  is initialized with the square of the value of the cell cell 1 ,   the “sqavg2” field  318  is initialized with the square of the value of the cell cell 2 , and   the “prod” field  319  is initialized with the product of the values of the cells cell 1  and cell 2 .       

     At step  413 , a test is performed to check if reset is equal to TRUE. If it is the case, then control is given to step  414 , otherwise control is given to step  415 . 
     At step  414 , the DOTWZ  310  is reset with the following actions on the fields:
         the “Index” field  313  is initialized with a zero value,   the “avg1” field  315  is initialized with the value of the cell cell 1 ,   the “avg2” field  316  is initialized with the value of the cell cell 2 ,   the “sqavg1” field  317  is initialized with the square of the value of the cell cell 1 ,   the “sqavg2” field  318  is initialized with the square of the value of the cell cell 2 , and   the “prod” field  319  is initialized with the product of the values of the cells cell 1  and cell 2 .       

     At step  415 , the DOTWZ  310  is refreshed with the following actions on the fields:
         the “avg1” field  315  is set equal to (index*avg 1 +cell 1 )/(index+1),   the “avg2” field  316  is set equal to (index*avg 2 +cell 1 )/(index+1),   the “sqavg1” field  317  is set equal to (index*sqavg 1 +cell 1 *cell 1 )/(index+1),   the “sqavg2” field  318  is set equal to (index*sqavg 2 +cell 2 *cell 2 )/(index+1),   the “prod” field  319  is set equal to (index*prod+cell 1 *cell 2 )/(index+1), and finally   the “Index” field  313  is set equal to index+1.       

     Then control is given to step  410 . 
     What has been described is merely illustrative of the application of the principles of the present invention. Other arrangements and methods can be implemented by those skilled in the art without departing from the spirit and scope of the present invention.