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STATS.PRG
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*-------------------------------------------------------------------------------
*-- Program...: STATS.PRG
*-- Programmer: Ken Mayer (CIS: 71333,1030) and Jay Parsons (CIS: 70160,340)
*-- Date......: 06/25/1992
*-- Notes.....: Statistical Functions -- see README.TXT to include this
*-- library file in your system.
*-------------------------------------------------------------------------------
FUNCTION Samplevar
*-------------------------------------------------------------------------------
*-- Programmer..: Jay Parsons (CIS: 70160,340)
*-- Date........: 4/13/1992
*-- Notes.......: Finds sample variance of specified field of the current
*-- : database, using CALCULATE command.
*-- : The CALCULATE command calculates the population variance,
*-- : which is smaller by a factor of (n-1)/n.
*-- :
*-- Written for.: dBASE IV Version 1.5
*-- Rev. History: Original function 1990.
*-- : Modified to take optional parameter, 4/13/1992
*-- Calls : None
*-- Called by...: Any
*-- Usage.......: Samplevar( <cField> [, <cClause> ] )
*-- Example.....: ? Samplevar( "Balance", ".FOR..NOT. isblank( Balance )" )
*-- Returns : a numeric or float value, the sample variance, or .F. if
*-- : it cannot be calculated.
*-- : If any of the numeric items are floats, the result will be.
*-- Parameters..: cField, name of a numeric field of the current database
*-- : for which to calculate the sample variance
*-- : cClause, optional, a FOR, WHILE, TO, etc. clause
*-------------------------------------------------------------------------------
PARAMETERS cField, cCondition
PRIVATE fVar, nCount, cCond
IF pcount() = 2
cCond = " "+ cCondition
ELSE
cCond = ""
ENDIF
CALCULATE VAR( &cField ), CNT() TO fVar, nCount &cCond
RETURN iif( nCount > 1, fVar * nCount / ( nCount - 1 ), .F. )
*-- Eof: Samplevar()
FUNCTION Stny
*-------------------------------------------------------------------------------
*-- Programmer..: Jay Parsons (CIS: 70160,340)
*-- Date........: 11/13/1990
*-- Notes.......: Returns value of the standard normal distribution function
*-- : given a number of standard deviations from the mean.
*-- : This function is not useful alone. The standard normal
*-- : distribution function is the familiar bell-shaped curve
*-- : scaled so its mean is at 0, each standard deviation is 1
*-- : and the total area under the curve is 1. The function
*-- : Stnarea calls on this function to calculate the approximate
*-- : area (a fraction equal to percent of the total) under the
*-- : part of the curve lying betwen the mean and the given
*-- : number of standard deviations.
*-- :
*-- Written for.: dBASE IV
*-- Rev. History: None
*-- Calls : None
*-- Called by...: Any
*-- Usage.......: Stny( <nDevs> )
*-- Example.....: ? Stny( 1 )
*-- Returns : numeric value of the function.
*-- Parameters..: nDevs, standard deviations from the mean
*-------------------------------------------------------------------------------
PARAMETERS nDevs
RETURN exp( -nDevs * nDevs / 2 ) / sqrt( 2 * pi() )
*-- EoF: Stny()
FUNCTION Stnarea
*-------------------------------------------------------------------------------
*-- Programmer..: Jay Parsons (CIS: 70160,340)
*-- Date........: 11/13/1990
*-- Notes.......: Area of the standard normal distribution function between
*-- : mean and given number of standard deviations from the mean.
*-- :
*-- : What's it about? Well, College Board scores (originally)
*-- : were based on a normal distribution with a mean of 500 and
*-- : 100 points per standard deviation. Knowing that a 650
*-- : score is 1.5 standard deviations from the 500 mean, we
*-- : can calculate Stnarea( 1.5 ) as .4332. This tells us that
*-- : 43.32% of the scores lie between 650 and 500. Since 50%
*-- : lie below 500, a score of 650 beats 93.32% of the scores.
*-- :
*-- : The polynomial approximation used by this function is said
*-- : to be accurate to .00001, 1/1000 of one percent. Remember
*-- : to SET DECIMALS appropriately to view results.
*-- :
*-- Written for.: dBASE IV
*-- Rev. History: None
*-- Calls : Stny() Function in STATS.PRG
*-- Called by...: Any
*-- Usage.......: Stnarea( <nDevs> )
*-- Example.....: ? Stnarea( 1.5 )
*-- Returns : % of area between deviations given and the mean, 0<=a<.5.
*-- Parameters..: nDevs, standard deviations from the mean
*-------------------------------------------------------------------------------
PARAMETERS nDevs
PRIVATE nX, nV
nX = abs( nDevs )
nV = 1 / ( 1 + .33267 * nX )
RETURN .5 - Stny( nX ) * ( .4361836 * nV - .1201676 * nV * nV ;
+ .937298 * nV * nV * nV )
*-- EoF: Stnarea()
FUNCTION Stnz
*-------------------------------------------------------------------------------
*-- Programmer..: Jay Parsons (CIS: 70160,340)
*-- Date........: 11/13/1990
*-- Notes.......: A lookup table to find the values of "z", standard
*-- : deviations, corresponding to the most common areas inside a
*-- : given number of tails of the normal distribution function.
*-- :
*-- : Used in testing confidence intervals. If a sample of
*-- : light bulbs from a shipment shows an average life of 1150
*-- : hours, and the criterion for rejection of the shipment is
*-- : 95% confidence that the average life of all bulbs is less
*-- : than (a single tail) 1200 hours, the value 1.64485 returned
*-- : by this function is necessary to determine whether to
*-- : reject the shipment or not.
*-- :
*-- : Values of "z" that are not found in the table can be found
*-- : using Stndevs, below, but it is slow.
*-- :
*-- Written for.: dBASE IV
*-- Rev. History: None
*-- Calls : None
*-- Called by...: Any
*-- Usage.......: Stnz( <nProb>, <nTails> )
*-- Example.....: ? Stnz( .95, 1 )
*-- Returns : z, number of standard deviations from mean inside which
*-- : ( or to the side of which includes the mean, if one tail)
*-- : the given percentage of area will fall.
*-- : Returns -1 if no entry in table.
*-- Parameters..: nConf, confidence desired, 0 < nConf < 1
*-- : nTails, 1 or 2 = number of tails of curve of interest
*-------------------------------------------------------------------------------
PARAMETERS nConf, nTails
IF nTails # 1 .AND. nTails # 2
RETURN -1
ENDIF
DO CASE
CASE nConf = .95
RETURN iif( nTails = 1, 1.64485, 1.96010 )
CASE nConf = .99
RETURN iif( nTails = 1, 2.32676, 2.57648 )
CASE nConf = .995
RETURN iif( nTails = 1, 2.57648, 2.80794 )
CASE nConf = .999
RETURN iif( nTails = 1, 3.09147, 3.29202 )
OTHERWISE
RETURN -1
ENDCASE
*-- EoF: Stnz()
FUNCTION Stndiff
*-------------------------------------------------------------------------------
*-- Programmer..: Jay Parsons (CIS: 70160,340)
*-- Date........: 4/13/1992
*-- Notes.......: Determines whether hypothesis that sample of a given mean
*-- is different from expected mean is justified.
*--
*-- If nPopstd, the standard deviation of the population, is
*-- not known and nSample, the sample size, is greater than
*-- 30, the sample standard deviation may be used for nPopstd.
*--
*-- This function assumes the population is large relative to
*-- the sample or that the sampling is with replacement. If
*-- neither is true, the right side of the expression in the
*-- later return line should be multiplied by:
*-- sqrt( ( nPop - nSample ) / ( nPop - 1 ) )
*-- where nPop is the size of the population.
*--
*-- Do not use this with small samples, less than 20, because
*-- the standard normal distribution is not sufficiently
*-- accurate as an approximation of the distribution of sample
*-- means in such a case. See "Student's T-distribution" in a
*-- statistics text.
*--
*-- Written for.: dBASE IV Version 1.5
*-- Rev. History: None.
*-- Calls : Stnz() Function in STATS.PRG
*-- Called by...: Any
*-- Usage.......: Stndiff( <nConf>, <nTails>, <nSample>, <nSampmean>, ;
*-- : <nPopmean>, <nPopstd> )
*-- Example.....: ? Stndiff( .95, 1, 30, 1150, 1200, 20 )
*-- Returns : .T. if hypothesis of difference is justified to degree of
*-- : confidence specified, or .F. Returns -1 if confidence is
*-- : not one for which z can be looked up in Stnz(). If you
*-- : need other confidence levels, run Stndevs() to find the
*-- : z values for them and add them to the Stnz() table.
*-- Parameters..: nConf, confidence desired, 0 < nConf < 1
*-- : nTails, 1 or 2 = number of tails of curve of interest
*-- : nSample, number of items in the sample
*-- : nSampmean, mean of the sample
*-- : nPopmean, mean of the population ( test standard mean )
*-- : nPopstd, standard deviation of population
*-------------------------------------------------------------------------------
PARAMETERS nConf, nTails, nSample, nSampmean, ;
nPopmean, nPopstd
PRIVATE nStd
nStd = Stnz( nConf, nTails )
IF nStd = -1
RETURN nStd
ELSE
RETURN abs( nSampmean - nPopmean ) ;
> nStd * nPopstd / sqrt( nSample )
ENDIF
*-- EoF: Stndiff()
FUNCTION Stndevs
*-------------------------------------------------------------------------------
*-- Programmer..: Jay Parsons (CIS: 70160,340)
*-- Date........: 4/13/1992
*-- Notes.......: Calculates "z", standard deviations, corresponding to any
*-- : area of standard normal curve between mean and the desired
*-- : z. Much slower than Stnz().
*-- Written for.: dBASE IV Version 1.5
*-- Rev. History: Original function 1990.
*-- : Conformed to Zeroin() 4/13/1992.
*-- Calls : Zeroin() Function in STATS.PRG
*-- Called by...: Any
*-- Usage.......: Stndevs( <nArea> )
*-- Example.....: ? Stndevs( .96 )
*-- Returns : z, number of standard deviations from mean, or a negative
*-- : number indicating failure to find a root..
*-- Parameters..: nArea, area "left" of point of interest, .5 < nArea < 1
*-------------------------------------------------------------------------------
PARAMETERS nArea
PRIVATE nTest, nFlag
IF nArea > .99999 .OR. nArea < .5
RETURN -1
ENDIF
nFlag = 0
nTest = Zeroin( "Tstnarea", 0, 4.2, float(1/100000), 100, nFlag, nArea )
RETURN iif( nFlag < 3, nTest, -nFlag )
*-- EoF: Stndevs()
FUNCTION Tstnarea
*-------------------------------------------------------------------------------
*-- Programmer..: Jay Parsons (CIS: 70160,340)
*-- Date........: 11/13/1990
*-- Notes.......: Translation function to convert area to left of point
*-- : under standard normal curve to 0 for Zeroin().
*-- Written for.: dBASE IV
*-- Rev. History: None
*-- Calls : Stnarea() Function in STATS.PRG
*-- Called by...: Any
*-- Usage.......: Tstnarea( <nDevs>, <nArea> )
*-- Example.....: ? Tstnarea( 1.6,.96 )
*-- Returns : positive or negative number corresponding to direction to
*-- : root where nArea = Stnarea
*-- Parameters..: nDevs, trial number of standard deviations
*-- : nArea, area for which deviations are to be found
*-------------------------------------------------------------------------------
PARAMETERS nDevs, nArea
RETURN Stnarea( nDevs ) +.5 - nArea
*-- EoF: Tstnarea()
FUNCTION Zeroin
*-------------------------------------------------------------------------------
*-- Programmer..: Tony Lima (CIS: 72331,3724) and Jay Parsons (CIS: 70160,340)
*-- Date........: 04/13/1992
*-- Notes.......: Finds a zero of a continuous function.
*-- : In substance, what this function does is close in on a
*-- : solution to a function that cannot otherwise be solved.
*-- : Assuming Y = f(X), if Y1 and Y2, the values of the function
*-- : for X1 and X2, have different signs, there must be at least
*-- : one value of X between X1 and X2 for which Y = 0, if the
*-- : function is continuous. This function closes in on such a
*-- : value of X by a trial-and-error process.
*-- :
*-- : This function is very slow, so a maximum number of iterations
*-- : is passed as a parameter. If the number of iterations is
*-- : exceeded, the function will fail to find a root. If this
*-- : occurs, pick different original "X" values, increase the
*-- : number of iterations or increase the errors allowed. Once
*-- : an approximate root is found, you can use values of X close
*-- : on either side and reduce the error allowed to find an
*-- : improved solution. Also, of course, the signs of Y must be
*-- : different for the starting X values for the function to
*-- : proceed at all.
*-- :
*-- : NOTE ESPECIALLY - There is NO guarantee that a root returned
*-- : by this function is the only one, or the most meaningful.
*-- : It depends on the function that this function calls, but if
*-- : that function has several roots, any of them may be returned.
*-- : This can easily happen with such called functions as net
*-- : present value where the cash flows alternate from positive
*-- : to negative and back, and in many other "real life" cases.
*-- : See the discussion of @IRR in the documentation of a good
*-- : spreadsheet program such as Quattro Pro for further
*-- : information.
*-- :
*-- : The method used by this function is a "secant and bisect"
*-- : search. The "secant" is the line connecting two X,Y
*-- : points on a graph using standard Cartesian coordinates.
*-- : Where the secant crosses the X axis is the best guess for
*-- : the value of X that will have Y = 0, and will be correct
*-- : if the function is linear between the two points. The
*-- : basic strategy is to calculate Y at that value of X, then
*-- : keep the new X and that one of the old X values that had
*-- : a Y-value of opposite sign, and reiterate to close in.
*-- :
*-- : If the function is a simple curve with most of the change
*-- : in Y close to one of the X-values, as often occurs if the
*-- : initial values of X are poorly chosen, repeated secants
*-- : will do little to find a Y-value close to zero and will
*-- : reduce the difference in X-values only slightly. In this
*-- : case the function shifts to choosing the new X halfway
*-- : between the old ones, bisecting the difference and always
*-- : reducing the bracket by half, for a while.
*-- :
*-- : While this function finds a "zero", it may be used to
*-- : find an X corresponding to any other value of Y. Suppose
*-- : the function of X is FUNCTION Blackbox( X ) and it is
*-- : desired to find a value of X for which f(X) = 7. The trick
*-- : is to interpose a function between Zeroin() and Blackbox()
*-- : that will return a 0 to Zeroin() whenever Blackbox() returns
*-- : 7. By calling that function, Zeroin() finds a value of
*-- : X for which Blackbox( X ) = 7, as required:
*-- : Result = Zeroin( "Temp", <other parameters omitted> )
*-- :
*-- : FUNCTION Temp
*-- : parameters nQ
*-- : RETURN Blackbox( nQ ) - 7
*-- :
*-- Written for.: dBASE IV Version 1.5
*-- Rev. History: Original function 1990.
*-- : Modified to take optional parameters, 4/13/1992
*-- Calls : The function whose name is first parameter.
*-- : NPV() Function in FINANCE.PRG
*-- Called by...: Any
*-- Usage.......: Zeroin( <cFunction>, <fX1>, <fX2>, <fAbserror>, ;
*-- : <nMaxiter>, <n_Flag> ;
*-- : [, xPass1 [, xPass2 [, xPass3 ] ] ] )
*-- Example.....: ? Zeroin( "Npv", 0, 200, .000001, 200, n_Flag, 11 )
*-- Returns : a float value representing a root, if n_Flag < 3.
*-- Parameters..: cFunction, the name of the function to solve for a root.
*-- fX1, one of the X-values between which the root is sought.
*-- fX2, the second of these values.
*-- Note: These MUST be chosen so the f( X ) values for the two
*-- of them have opposite signs (they must bracket the result).
*-- fAbserror, the absolute error allowed in the result.
*-- nMaxiter, the maximum number of times to iterate.
*-- n_Flag, an integer to signal success ( < 3 ) or failure.
*-- xPass1 . . . 3, arguments to be passed through to cFunction.
*-- The parameter "n_Flag" should be passed as a variable so it
*-- may be accessed on return. The limit of 9 literal parameters
*-- may require passing others as variables. The "xPass"
*-- parameters are optional and the fact there are three of them
*-- is arbitrary; they exist to hold whatever parameters may be
*-- needed by the function cFunction being called aside from
*-- the value of X for which it is being evaluated. Add more
*-- and change the 3 "&cFunc." lines below if you need more.
*-- Side effects: Uses and alters a global numeric variable, here called
*-- "n_Flag", to report error conditions resulting in value
*-- returned being meaningless. Possible n_Flag values are:
*-- 1 success - root found within error allowed
*-- 2 success - root was found exactly
*-- 3 error - function value not converging
*-- 4 error - original values do not bracket a root
*-- 5 error - maximum iterations exceeded
*-------------------------------------------------------------------------------
parameters cFunc, fNearx, fFarx, fAbserr, nMaxiter, ;
n_Flag, xPass1, xPass2, xPass3
private nSplits, fBracket, fFary, fNeary, nIters
private fMaxabs, fOldx, fOldy, fDiffx, fAbsdiff, fSecant
store 0 to nSplits, nIters
fBracket = abs ( fNearx - fFarx )
fFary = &cFunc.( fFarx, xPass1, xPass2, xPass3 )
fNeary = &cFunc.( fNearx, xPass1, xPass2, xPass3 )
if sign( fNeary ) = sign( fFary )
n_Flag = 4
return float(0)
endif
fMaxabs = max( abs( fNeary ), abs( fFary ) )
n_Flag = 0
* Main iteration loop
do while .t.
if abs( fFary ) < abs( fNeary )
* Interchange fNearx and fFarx so that
* fNearx is closer to a solution--
* abs( fNeary ) <= abs( fFary )
fOldx = fNearx
fOldy = fNeary
fNearx = fFarx
fNeary = fFary
fFarx = fOldx
fFary = fOldy
endif
fDiffx = fFarx - fNearx
fAbsdiff = abs( fDiffx )
* Test whether interval is too small to continue
if fAbsdiff <= 2 * fAbserr
if abs( fNeary ) > fMaxabs
* Yes, but we are out of bounds
n_Flag = 3
fNearx = float(0)
else
* Yes, and we have a solution!
n_Flag = 1
endif
exit
endif
* Save the last approximation to x and y
fOldx = fNearx
fOldy = fNeary
* Check if reduction in the size of
* bracketing interval is satisfactory.
* If not, bisect until it is.
nSplits = nSplits + 1
if nSplits >= 4
if 4 * fAbsdiff >= fBracket
fNearx = fNearx + fDiffx / 2
else
nSplits = 0
fBracket = fAbsdiff / 2
* Calculate secant
fSecant = ( fNearx - fFarx ) * fNeary ;
/ ( fFary - fNeary )
* But not less than error allowed
if abs( fSecant ) < fAbserr
fNearx = fnearx + fAbserr * sign( fDiffx )
else
fNearx = fNearx + fSecant
endif
endif
endif
* Evaluate the function at the new approximation
fNeary = &cFunc.( fNearx, xPass1, xPass2, xPass3 )
* If it's exactly zero, we win! Run with it
if fNeary = 0.00
n_Flag = 2
exit
endif
* Else adjust iteration count and quit if too
* many iterations with no solution
nIters = nIters + 1
if nIters > nMaxiter
n_Flag = 5
fNearx = float( 0 )
exit
endif
* And finally keep as the new fFarx that one
* of the previous approximations, fFarx and
* fOldx, at which the function has a sign opposite
* to that at the new approximation, fNearx.
if sign( fNeary ) = sign( fFary )
fFarx = fOldx
fFary = fOldy
endif
enddo
RETURN fNearx
*-- EoF: Zeroin()
*-------------------------------------------------------------------------------
*-- The functions below are here by courtesy ... (to make life easier on the
*-- poor programmer ...)
*-------------------------------------------------------------------------------
FUNCTION Npv
*-------------------------------------------------------------------------------
*-- Programmer..: Tony Lima (CIS: 72331,3724) and Jay Parsons (CIS: 70160,340)
*-- Date........: 03/01/1992
*-- Notes.......: Net present value of array aCashflow[ nPeriods ]
*-- Calculates npv given assumed rate and # periods.
*-- Written for.: dBASE IV, 1.1
*-- Rev. History: None
*-- Calls.......: None
*-- Called by...: Any
*-- Usage.......: NPV(<nRate>,<nPeriods>)
*-- Example.....: ? NPV( .06, 6 )
*-- Returns.....: Float = value of the project at given rate
*-- Parameters..: nRate = Interest Rate
*-- : nPeriods = Number of Periods to calculate for
*-- Other inputs: Requires the array aCashflow[ ] set up before calling.
*-- : Each of its elements [n] holds the cash flow at the
*-- : beginning of period n, with a negative amount indicating
*-- : a cash outflow. Elements of value 0 must be included for
*-- : all periods with no cash flow, and all periods must be of
*-- : equal length.
*-- : If the project is expected to require an immediate outlay
*-- : of $6,000 and to return $2,000 at the end of each of the
*-- : first five years thereafter, the array will be:
*-- : aCashflow[1] = -6000
*-- : aCashflow[2] = 2000
*-- : aCashflow[3] = 2000
*-- : * * *
*-- : aCashflow[6] = 2000
*-- : Rewriting function to have array name passed as a parameter
*-- : is possible, but will slow down execution to an extent that
*-- : will be very noticeable if this function is being repeatedly
*-- : executed, as by Zeroin() to find an Internal Rate of Return.
*-------------------------------------------------------------------------------
parameters nRate, nPeriods
private nDiscount, nFactor, nPeriod, nNpv
nPeriod = 1
nNpv = aCashflow[ 1 ]
nDiscount = float( 1 )
nFactor = 1 / ( 1 + nRate )
do while nPeriod < nPeriods
nPeriod = nPeriod + 1
nDiscount = nDiscount * nFactor
nNpv = nNpv + aCashflow[ nPeriod ] * nDiscount
enddo
RETURN nNpv
*-- EoF: Npv()
FUNCTION ArrayRows
*-------------------------------------------------------------------------------
*-- Programmer..: Jay Parsons (CIS: 70160,340)
*-- Date........: 03/01/1992
*-- Notes.......: Number of Rows in an array
*-- Written for.: dBASE IV, 1.1
*-- Rev. History: None
*-- Calls.......: None
*-- Called by...: Any
*-- Usage.......: ArrayRows("<aArray>")
*-- Example.....: n = ArrayRows("aTest")
*-- Returns.....: numeric
*-- Parameters..: aArray = Name of array
*-------------------------------------------------------------------------------
parameters aArray
private nHi, nLo, nTrial, nDims
nLo = 1
nHi = 1170
if type( "&aArray[ 1, 1 ]" ) = "U"
nDims = 1
else
nDims = 2
endif
do while .T.
nTrial = int( ( nHi + nLo ) / 2 )
if nHi < nLo
exit
endif
if nDims = 1 .and. type( "&aArray[ nTrial ]" ) = "U" .or. ;
nDims = 2 .and. type( "&aArray[ nTrial, 1 ]" ) = "U"
nHi = nTrial - 1
else
nLo = nTrial + 1
endif
enddo
RETURN nTrial
*-- EoF: ArrayRows()
*-------------------------------------------------------------------------------
*-- End of Program: STATS.PRG
*-------------------------------------------------------------------------------