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179.sh
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#! /bin/sh
# This is a shell archive, meaning:
# 1. Remove everything above the #! /bin/sh line.
# 2. Save the resulting text in a file.
# 3. Execute the file with /bin/sh (not csh) to create the files:
# Fortran/
# Fortran/Sp/
# Fortran/Sp/Drivers/
# Fortran/Sp/Drivers/Makefile
# Fortran/Sp/Drivers/driver.f
# Fortran/Sp/Drivers/res
# Fortran/Sp/Src/
# Fortran/Sp/Src/src.f
# This archive created: Wed Jan 18 20:30:22 2006
export PATH; PATH=/bin:$PATH
if test ! -d 'Fortran'
then
mkdir 'Fortran'
fi
cd 'Fortran'
if test ! -d 'Sp'
then
mkdir 'Sp'
fi
cd 'Sp'
if test ! -d 'Drivers'
then
mkdir 'Drivers'
fi
cd 'Drivers'
if test -f 'Makefile'
then
echo shar: will not over-write existing file "'Makefile'"
else
cat << "SHAR_EOF" > 'Makefile'
all: Res
src.o: src.f
$(F77) $(F77OPTS) -c src.f
driver.o: driver.f
$(F77) $(F77OPTS) -c driver.f
DRIVERS= driver
RESULTS= Res
Objs1= driver.o src.o
driver: $(Objs1)
$(F77) $(F77OPTS) -o driver $(Objs1) $(SRCLIBS)
Res: driver
./driver >Res
diffres:Res res
echo "Differences in results from driver"
$(DIFF) Res res
clean:
rm -rf *.o $(DRIVERS) $(CLEANUP) $(RESULTS)
SHAR_EOF
fi # end of overwriting check
if test -f 'driver.f'
then
echo shar: will not over-write existing file "'driver.f'"
else
cat << "SHAR_EOF" > 'driver.f'
program main
c***********************************************************************
c
cc TOMS179_PRB tests TOMS179.
c
c Modified:
c
c 03 January 2006
c
c Author:
c
c John Burkardt
c
implicit none
write ( *, '(a)' ) ' '
write ( *, '(a)' ) 'TOMS179_PRB'
write ( *, '(a)' ) ' Test TOMS algorithm 179, to evaluate'
write ( *, '(a)' ) ' the modified Beta function.'
call test01
call test02
write ( *, '(a)' ) ' '
write ( *, '(a)' ) 'TOMS179_PRB'
write ( *, '(a)' ) ' Normal end of execution.'
stop
end
subroutine test01
c***********************************************************************
c
cc TEST01 tests DLGAMA.
c
c Modified:
c
c 03 January 2006
c
c Author:
c
c John Burkardt
c
implicit none
double precision dlgama
double precision fx
double precision fx2
integer n_data
double precision x
write ( *, '(a)' ) ' '
write ( *, '(a)' ) 'TEST01'
write ( *, '(a)' ) ' Test DLGAMA, which estimates the logarithm'
write ( *, '(a)' ) ' of the Gamma function.'
write ( *, '(a)' ) ' '
write ( *, '(a)' )
& ' X Exact Value Computed'
write ( *, '(a)' ) ' '
n_data = 0
10 continue
call gamma_log_values ( n_data, x, fx )
if ( n_data <= 0 ) then
go to 20
end if
fx2 = dlgama ( x )
write ( *, '(2x,f8.4,2x,g16.8,2x,g16.8)' ) x, fx, fx2
go to 10
20 continue
return
end
subroutine test02
c***********************************************************************
c
cc TEST02 tests MDBETA.
c
c Modified:
c
c 03 January 2006
c
c Author:
c
c John Burkardt
c
implicit none
double precision fx
double precision fx2
integer ier
integer n_data
double precision p
double precision prob
double precision q
double precision x
write ( *, '(a)' ) ' '
write ( *, '(a)' ) 'TEST02'
write ( *, '(a)' ) ' Test MDBETA, which estimates the value of'
write ( *, '(a)' ) ' the modified Beta function.'
write ( *, '(a)' ) ' '
write ( *, '(a)' )
& ' X P Q Exact Value Computed'
write ( *, '(a)' ) ' '
n_data = 0
10 continue
call beta_cdf_values ( n_data, p, q, x, fx )
if ( n_data <= 0 ) then
go to 20
end if
call mdbeta ( x, p, q, prob, ier )
write ( *, '(2x,f8.4,2x,f8.4,2x,f8.4,2x,g16.8,2x,g16.8)' )
& x, p, q, fx, prob
go to 10
20 continue
return
end
function dlgama ( x )
c*******************************************************************************
c
cc DLGAMA calculates the natural logarithm of GAMMA ( X ).
c
c Discussion:
c
c Computation is based on an algorithm outlined in references 1 and 2.
c The program uses rational functions that theoretically approximate
c LOG(GAMMA(X)) to at least 18 significant decimal digits. The
c approximation for 12 < X is from Hart et al, while approximations
c for X < 12.0D+00 are similar to those in Cody and Hillstrom,
c but are unpublished.
c
c The accuracy achieved depends on the arithmetic system, the compiler,
c intrinsic functions, and proper selection of the machine dependent
c constants.
c
c Modified:
c
c 03 January 2006
c
c Author:
c
c W. J. Cody and L. Stoltz
c Argonne National Laboratory
c
c Reference:
c
c W. J. Cody and Kenneth Hillstrom,
c Chebyshev Approximations for the Natural Logarithm of the Gamma Function,
c Mathematics of Computation,
c Volume 21, 1967, pages 198-203.
c
c Kenneth Hillstrom,
c ANL/AMD Program ANLC366S, DGAMMA/DLGAMA,
c May 1969.
c
c Hart, Cheney, Lawson, Maehly, Mesztenyi, Rice, Thacher, Witzgall,
c Computer Approximations,
c Wiley, 1968.
c
c Parameters:
c
c Input, double precision X, the argument of the Gamma function.
c X must be positive.
c
c Output, double precision DLGAMA, the logarithm of the Gamma
c function of X.
c
c Local Parameters:
c
c Local, double precision BETA, the radix for the floating-point
c representation.
c
c Local, integer MAXEXP, the smallest positive power of BETA that overflows.
c
c Local, double precision XBIG, the largest argument for which
c LN(GAMMA(X)) is representable in the machine, the solution to the equation
c LN(GAMMA(XBIG)) = BETA**MAXEXP.
c
c Local, double precision FRTBIG, a rough estimate of the fourth root
c of XBIG.
c
c Approximate values for some important machines are:
c
c BETA MAXEXP XBIG FRTBIG
c
c CRAY-1 (S.P.) 2 8191 9.62D+2461 3.13D+615
c Cyber 180/855 (S.P.) 2 1070 1.72D+319 6.44D+79
c IEEE (IBM/XT) (S.P.) 2 128 4.08D+36 1.42D+9
c IEEE (IBM/XT) (D.P.) 2 1024 2.55D+305 2.25D+76
c IBM 3033 (D.P.) 16 63 4.29D+73 2.56D+18
c VAX D-Format (D.P.) 2 127 2.05D+36 1.20D+9
c VAX G-Format (D.P.) 2 1023 1.28D+305 1.89D+76
c
implicit none
double precision c(7)
double precision corr
double precision d1
double precision d2
double precision d4
double precision dlgama
integer i
double precision frtbig
double precision p1(8)
double precision p2(8)
double precision p4(8)
double precision pnt68
double precision q1(8)
double precision q2(8)
double precision q4(8)
double precision res
double precision sqrtpi
double precision x
double precision xbig
double precision xden
double precision xeps
double precision xm1
double precision xm2
double precision xm4
double precision xnum
double precision xsq
data c /
& -1.910444077728D-03,
& 8.4171387781295D-04,
& -5.952379913043012D-04,
& 7.93650793500350248D-04,
& -2.777777777777681622553D-03,
& 8.333333333333333331554247D-02,
& 5.7083835261D-03 /
data d1 / -5.772156649015328605195174D-01 /
data d2 / 4.227843350984671393993777D-01 /
data d4 / 1.791759469228055000094023D+00 /
data frtbig / 1.42D+09 /
data p1 /
& 4.945235359296727046734888D+00,
& 2.018112620856775083915565D+02,
& 2.290838373831346393026739D+03,
& 1.131967205903380828685045D+04,
& 2.855724635671635335736389D+04,
& 3.848496228443793359990269D+04,
& 2.637748787624195437963534D+04,
& 7.225813979700288197698961D+03 /
data p2 /
& 4.974607845568932035012064D+00,
& 5.424138599891070494101986D+02,
& 1.550693864978364947665077D+04,
& 1.847932904445632425417223D+05,
& 1.088204769468828767498470D+06,
& 3.338152967987029735917223D+06,
& 5.106661678927352456275255D+06,
& 3.074109054850539556250927D+06 /
data p4 /
& 1.474502166059939948905062D+04,
& 2.426813369486704502836312D+06,
& 1.214755574045093227939592D+08,
& 2.663432449630976949898078D+09,
& 2.940378956634553899906876D+10,
& 1.702665737765398868392998D+11,
& 4.926125793377430887588120D+11,
& 5.606251856223951465078242D+11 /
data pnt68 / 0.6796875D+00 /
data q1 /
& 6.748212550303777196073036D+01,
& 1.113332393857199323513008D+03,
& 7.738757056935398733233834D+03,
& 2.763987074403340708898585D+04,
& 5.499310206226157329794414D+04,
& 6.161122180066002127833352D+04,
& 3.635127591501940507276287D+04,
& 8.785536302431013170870835D+03 /
data q2 /
& 1.830328399370592604055942D+02,
& 7.765049321445005871323047D+03,
& 1.331903827966074194402448D+05,
& 1.136705821321969608938755D+06,
& 5.267964117437946917577538D+06,
& 1.346701454311101692290052D+07,
& 1.782736530353274213975932D+07,
& 9.533095591844353613395747D+06 /
data q4 /
& 2.690530175870899333379843D+03,
& 6.393885654300092398984238D+05,
& 4.135599930241388052042842D+07,
& 1.120872109616147941376570D+09,
& 1.488613728678813811542398D+10,
& 1.016803586272438228077304D+11,
& 3.417476345507377132798597D+11,
& 4.463158187419713286462081D+11 /
data sqrtpi / 0.9189385332046727417803297D+00 /
data xbig / 4.08D+36 /
data xeps / 2.23D-16 /
c
c Return immediately if the argument is out of range.
c
if ( x <= 0.0D+00 .or. xbig < x ) then
dlgama = log ( xbig )
return
end if
if ( x <= xeps ) then
res = -log ( x )
else if ( x <= 1.5D+00 ) then
if ( x < pnt68 ) then
corr = - log ( x )
xm1 = x
else
corr = 0.0D+00
xm1 = ( x - 0.5D+00 ) - 0.5D+00
end if
if ( x <= 0.5D+00 .or. pnt68 <= x ) then
xden = 1.0D+00
xnum = 0.0D+00
do i = 1, 8
xnum = xnum * xm1 + p1(i)
xden = xden * xm1 + q1(i)
end do
res = corr + ( xm1 * ( d1 + xm1 * ( xnum / xden ) ) )
else
xm2 = ( x - 0.5D+00 ) - 0.5D+00
xden = 1.0D+00
xnum = 0.0D+00
do i = 1, 8
xnum = xnum * xm2 + p2(i)
xden = xden * xm2 + q2(i)
end do
res = corr + xm2 * ( d2 + xm2 * ( xnum / xden ) )
end if
else if ( x <= 4.0D+00 ) then
xm2 = x - 2.0D+00
xden = 1.0D+00
xnum = 0.0D+00
do i = 1, 8
xnum = xnum * xm2 + p2(i)
xden = xden * xm2 + q2(i)
end do
res = xm2 * ( d2 + xm2 * ( xnum / xden ) )
else if ( x <= 12.0D+00 ) then
xm4 = x - 4.0D+00
xden = - 1.0D+00
xnum = 0.0D+00
do i = 1, 8
xnum = xnum * xm4 + p4(i)
xden = xden * xm4 + q4(i)
end do
res = d4 + xm4 * ( xnum / xden )
else
res = 0.0D+00
if ( x <= frtbig ) then
res = c(7)
xsq = x * x
do i = 1, 6
res = res / xsq + c(i)
end do
end if
res = res / x
corr = log ( x )
res = res + sqrtpi - 0.5D+00 * corr
res = res + x * ( corr - 1.0D+00 )
end if
dlgama = res
return
end
subroutine gamma_log_values ( n_data, x, fx )
c*******************************************************************************
c
cc GAMMA_LOG_VALUES returns some values of the Log Gamma function.
c
c Discussion:
c
c In Mathematica, the function can be evaluated by:
c
c Log[Gamma[x]]
c
c Modified:
c
c 03 January 2006
c
c Author:
c
c John Burkardt
c
c Reference:
c
c Milton Abramowitz and Irene Stegun,
c Handbook of Mathematical Functions,
c US Department of Commerce, 1964.
c
c Stephen Wolfram,
c The Mathematica Book,
c Fourth Edition,
c Wolfram Media / Cambridge University Press, 1999.
c
c Parameters:
c
c Input/output, integer N_DATA. The user sets N_DATA to 0 before the
c first call. On each call, the routine increments N_DATA by 1, and
c returns the corresponding data; when there is no more data, the
c output value of N_DATA will be 0 again.
c
c Output, double precision X, the argument of the function.
c
c Output, double precision FX, the value of the function.
c
implicit none
integer n_max
parameter ( n_max = 20 )
double precision fx
double precision fx_vec(n_max)
integer n_data
double precision x
double precision x_vec(n_max)
save fx_vec
save x_vec
data fx_vec /
& 0.1524063822430784D+01, 0.7966778177017837D+00,
& 0.3982338580692348D+00, 0.1520596783998375D+00,
& 0.0000000000000000D+00, -0.4987244125983972D-01,
& -0.8537409000331584D-01, -0.1081748095078604D+00,
& -0.1196129141723712D+00, -0.1207822376352452D+00,
& -0.1125917656967557D+00, -0.9580769740706586D-01,
& -0.7108387291437216D-01, -0.3898427592308333D-01,
& 0.00000000000000000D+00, 0.69314718055994530D+00,
& 0.17917594692280550D+01, 0.12801827480081469D+02,
& 0.39339884187199494D+02, 0.71257038967168009D+02 /
data x_vec /
& 0.20D+00, 0.40D+00, 0.60D+00, 0.80D+00,
& 1.00D+00, 1.10D+00, 1.20D+00, 1.30D+00,
& 1.40D+00, 1.50D+00, 1.60D+00, 1.70D+00,
& 1.80D+00, 1.90D+00, 2.00D+00, 3.00D+00,
& 4.00D+00, 10.00D+00, 20.00D+00, 30.00D+00 /
if ( n_data < 0 ) then
n_data = 0
end if
n_data = n_data + 1
if ( n_max < n_data ) then
n_data = 0
x = 0.0D+00
fx = 0.0D+00
else
x = x_vec(n_data)
fx = fx_vec(n_data)
end if
return
end
subroutine beta_cdf_values ( n_data, a, b, x, fx )
c*******************************************************************************
c
cc BETA_CDF_VALUES returns some values of the Beta CDF.
c
c Discussion:
c
c The incomplete Beta function may be written
c
c BETA_INC(A,B,X) = Integral (0 to X) T**(A-1) * (1-T)**(B-1) dT
c / Integral (0 to 1) T**(A-1) * (1-T)**(B-1) dT
c
c Thus,
c
c BETA_INC(A,B,0.0) = 0.0
c BETA_INC(A,B,1.0) = 1.0
c
c The incomplete Beta function is also sometimes called the
c "modified" Beta function, or the "normalized" Beta function
c or the Beta CDF (cumulative density function.
c
c In Mathematica, the function can be evaluated by:
c
c BETA[X,A,B] / BETA[A,B]
c
c The function can also be evaluated by using the Statistics package:
c
c Needs["Statistics`ContinuousDistributions`"]
c dist = BetaDistribution [ a, b ]
c CDF [ dist, x ]
c
c Modified:
c
c 04 January 2006
c
c Author:
c
c John Burkardt
c
c Reference:
c
c Milton Abramowitz and Irene Stegun,
c Handbook of Mathematical Functions,
c US Department of Commerce, 1964.
c
c Karl Pearson,
c Tables of the Incomplete Beta Function,
c Cambridge University Press, 1968.
c
c Stephen Wolfram,
c The Mathematica Book,
c Fourth Edition,
c Wolfram Media / Cambridge University Press, 1999.
c
c Parameters:
c
c Input/output, integer N_DATA. The user sets N_DATA to 0 before the
c first call. On each call, the routine increments N_DATA by 1, and
c returns the corresponding data; when there is no more data, the
c output value of N_DATA will be 0 again.
c
c Output, double precision A, B, the parameters of the function.
c
c Output, double precision X, the argument of the function.
c
c Output, double precision FX, the value of the function.
c
implicit none
integer n_max, i
parameter ( n_max = 42 )
double precision a
double precision a_vec(n_max)
double precision b
double precision b_vec(n_max)
double precision fx
double precision fx_vec(n_max)
integer n_data
double precision x
double precision x_vec(n_max)
save a_vec
save b_vec
save fx_vec
save x_vec
data a_vec / 0.5D+00, 0.5D+00, 0.5D+00, 1.0D+00,
& 1.0D+00, 1.0D+00, 1.0D+00, 1.0D+00, 2.0D+00,
& 2.0D+00, 2.0D+00, 2.0D+00, 2.0D+00, 2.0D+00,
& 2.0D+00, 2.0D+00, 2.0D+00, 5.5D+00, 10.0D+00,
& 10.0D+00, 10.0D+00, 10.0D+00, 20.0D+00, 20.0D+00,
& 20.0D+00, 20.0D+00, 20.0D+00, 30.0D+00, 30.0D+00,
& 40.0D+00, 0.1D+01, 0.1D+01, 0.1D+01, 0.1D+01,
& 0.1D+01, 0.1D+01, 0.1D+01, 0.1D+01, 0.2D+01,
& 0.3D+01, 0.4D+01, 0.5D+01 /
data b_vec /
& 0.5D+00, 0.5D+00, 0.5D+00, 0.5D+00, 0.5D+00,
& 0.5D+00, 0.5D+00, 1.0D+00, 2.0D+00, 2.0D+00,
& 2.0D+00, 2.0D+00, 2.0D+00, 2.0D+00, 2.0D+00,
& 2.0D+00, 2.0D+00, 5.0D+00, 0.5D+00, 5.0D+00,
& 5.0D+00, 10.0D+00, 5.0D+00, 10.0D+00, 10.0D+00,
& 20.0D+00, 20.0D+00, 10.0D+00, 10.0D+00, 20.0D+00,
& 0.5D+00, 0.5D+00, 0.5D+00, 0.5D+00, 0.2D+01,
& 0.3D+01, 0.4D+01, 0.5D+01, 0.2D+01, 0.2D+01,
& 0.2D+01, 0.2D+01 /
data (fx_vec(i), i=1,20) /
& 0.6376856085851985D-01, 0.2048327646991335D+00,
& 0.1000000000000000D+01, 0.0000000000000000D+00,
& 0.5012562893380045D-02, 0.5131670194948620D-01,
& 0.2928932188134525D+00, 0.5000000000000000D+00,
& 0.2800000000000000D-01, 0.1040000000000000D+00,
& 0.2160000000000000D+00, 0.3520000000000000D+00,
& 0.5000000000000000D+00, 0.6480000000000000D+00,
& 0.7840000000000000D+00, 0.8960000000000000D+00,
& 0.9720000000000000D+00, 0.4361908850559777D+00,
& 0.1516409096347099D+00, 0.8978271484375000D-01/
data (fx_vec(i), i=21,42) /
& 0.1000000000000000D+01, 0.5000000000000000D+00,
& 0.4598773297575791D+00, 0.2146816102371739D+00,
& 0.9507364826957875D+00, 0.5000000000000000D+00,
& 0.8979413687105918D+00, 0.2241297491808366D+00,
& 0.7586405487192086D+00, 0.7001783247477069D+00,
& 0.5131670194948620D-01, 0.1055728090000841D+00,
& 0.1633399734659245D+00, 0.2254033307585166D+00,
& 0.3600000000000000D+00, 0.4880000000000000D+00,
& 0.5904000000000000D+00, 0.6723200000000000D+00,
& 0.2160000000000000D+00, 0.8370000000000000D-01,
& 0.3078000000000000D-01, 0.1093500000000000D-01 /
data x_vec /
& 0.01D+00, 0.10D+00, 1.00D+00, 0.00D+00, 0.01D+00,
& 0.10D+00, 0.50D+00, 0.50D+00, 0.10D+00, 0.20D+00,
& 0.30D+00, 0.40D+00, 0.50D+00, 0.60D+00, 0.70D+00,
& 0.80D+00, 0.90D+00, 0.50D+00, 0.90D+00, 0.50D+00,
& 1.00D+00, 0.50D+00, 0.80D+00, 0.60D+00, 0.80D+00,
& 0.50D+00, 0.60D+00, 0.70D+00, 0.80D+00, 0.70D+00,
& 0.10D+00, 0.20D+00, 0.30D+00, 0.40D+00, 0.20D+00,
& 0.20D+00, 0.20D+00, 0.20D+00, 0.30D+00, 0.30D+00,
& 0.30D+00, 0.30D+00 /
if ( n_data < 0 ) then
n_data = 0
end if
n_data = n_data + 1
if ( n_max < n_data ) then
n_data = 0
a = 0.0D+00
b = 0.0D+00
x = 0.0D+00
fx = 0.0D+00
else
a = a_vec(n_data)
b = b_vec(n_data)
x = x_vec(n_data)
fx = fx_vec(n_data)
end if
return
end
SHAR_EOF
fi # end of overwriting check
if test -f 'res'
then
echo shar: will not over-write existing file "'res'"
else
cat << "SHAR_EOF" > 'res'
TOMS179_PRB
Test TOMS algorithm 179, to evaluate
the modified Beta function.
TEST01
Test DLGAMA, which estimates the logarithm
of the Gamma function.
X Exact Value Computed
0.2000 1.5240638 1.5240638
0.4000 0.79667782 0.79667782
0.6000 0.39823386 0.39823386
0.8000 0.15205968 0.15205968
1.0000 0.0000000 0.0000000
1.1000 -0.49872441E-01 -0.49872441E-01
1.2000 -0.85374090E-01 -0.85374090E-01
1.3000 -0.10817481 -0.10817481
1.4000 -0.11961291 -0.11961291
1.5000 -0.12078224 -0.12078224
1.6000 -0.11259177 -0.11259177
1.7000 -0.95807697E-01 -0.95807697E-01
1.8000 -0.71083873E-01 -0.71083873E-01
1.9000 -0.38984276E-01 -0.38984276E-01
2.0000 0.0000000 0.0000000
3.0000 0.69314718 0.69314718
4.0000 1.7917595 1.7917595
10.0000 12.801827 12.801827
20.0000 39.339884 39.339884
30.0000 71.257039 71.257039
TEST02
Test MDBETA, which estimates the value of
the modified Beta function.
X P Q Exact Value Computed
0.0100 0.5000 0.5000 0.63768561E-01 0.63768561E-01
0.1000 0.5000 0.5000 0.20483276 0.20483276
1.0000 0.5000 0.5000 1.0000000 1.0000000
0.0000 1.0000 0.5000 0.0000000 0.0000000
0.0100 1.0000 0.5000 0.50125629E-02 0.50125629E-02
0.1000 1.0000 0.5000 0.51316702E-01 0.51316702E-01
0.5000 1.0000 0.5000 0.29289322 0.29289322
0.5000 1.0000 1.0000 0.50000000 0.50000000
0.1000 2.0000 2.0000 0.28000000E-01 0.28000000E-01
0.2000 2.0000 2.0000 0.10400000 0.10400000
0.3000 2.0000 2.0000 0.21600000 0.21600000
0.4000 2.0000 2.0000 0.35200000 0.35200000
0.5000 2.0000 2.0000 0.50000000 0.50000000
0.6000 2.0000 2.0000 0.64800000 0.64800000
0.7000 2.0000 2.0000 0.78400000 0.78400000
0.8000 2.0000 2.0000 0.89600000 0.89600000
0.9000 2.0000 2.0000 0.97200000 0.97200000
0.5000 5.5000 5.0000 0.43619089 0.43619089
0.9000 10.0000 0.5000 0.15164091 0.15164091
0.5000 10.0000 5.0000 0.89782715E-01 0.89782715E-01
1.0000 10.0000 5.0000 1.0000000 1.0000000
0.5000 10.0000 10.0000 0.50000000 0.50000000
0.8000 20.0000 5.0000 0.45987733 0.45987733
0.6000 20.0000 10.0000 0.21468161 0.21468161
0.8000 20.0000 10.0000 0.95073648 0.95073648
0.5000 20.0000 20.0000 0.50000000 0.50000000
0.6000 20.0000 20.0000 0.89794137 0.89794137
0.7000 30.0000 10.0000 0.22412975 0.22412975
0.8000 30.0000 10.0000 0.75864055 0.75864055
0.7000 40.0000 20.0000 0.70017832 0.70017832
0.1000 1.0000 0.5000 0.51316702E-01 0.51316702E-01
0.2000 1.0000 0.5000 0.10557281 0.10557281
0.3000 1.0000 0.5000 0.16333997 0.16333997
0.4000 1.0000 0.5000 0.22540333 0.22540333
0.2000 1.0000 2.0000 0.36000000 0.36000000
0.2000 1.0000 3.0000 0.48800000 0.48800000
0.2000 1.0000 4.0000 0.59040000 0.59040000
0.2000 1.0000 5.0000 0.67232000 0.67232000
0.3000 2.0000 2.0000 0.21600000 0.21600000
0.3000 3.0000 2.0000 0.83700000E-01 0.83700000E-01
0.3000 4.0000 2.0000 0.30780000E-01 0.30780000E-01
0.3000 5.0000 2.0000 0.10935000E-01 0.10935000E-01
TOMS179_PRB
Normal end of execution.
SHAR_EOF
fi # end of overwriting check
cd ..
if test ! -d 'Src'
then
mkdir 'Src'
fi
cd 'Src'
if test -f 'src.f'
then
echo shar: will not over-write existing file "'src.f'"
else
cat << "SHAR_EOF" > 'src.f'
SUBROUTINE MDBETA ( X, P, Q, PROB, IER )
C FUNCTION - INCOMPLETE BETA PROBABILITY DISTRIBUTION FUNCTION
C
C USAGE - CALL MDBETA ( X, P, Q, PROB, IER )
C
C PARAMETERS
C
C X - VALUE TO WHICH FUNCTION IS TO BE INTEGRATED. X
C MUST BE IN THE RANGE [0,1] INCLUSIVE.
C P - INPUT (1ST) PARAMETER. MUST BE GREATER THAN 0.0.
C Q - INPUT (2ND) PARAMETER. MUST BE GREATER THAN 0.0.
C PROB - OUTPUT PROBABILITY THAT A RANDOM VARIABLE FROM A
C BETA DISTRIBUTION HAVING PARAMETERS P AND Q
C WILL BE LESS THAN OR EQUAL TO X.
C IER - ERROR PARAMETER.
C IER = 0 INDICATES A NORMAL EXIT.
C IER = 1 INDICATES THAT X IS NOT IN THE RANGE [0,1] INCLUSIVE.
C IER = 2 INDICATES THAT P AND/OR Q IS LESS THAN OR EQUAL TO 0.
C
IMPLICIT NONE
DOUBLE PRECISION ALEPS
DOUBLE PRECISION C
DOUBLE PRECISION CNT
DOUBLE PRECISION D4
DOUBLE PRECISION DLGAMA
DOUBLE PRECISION DP
DOUBLE PRECISION DQ
DOUBLE PRECISION EPS
DOUBLE PRECISION EPS1
DOUBLE PRECISION FINSUM
INTEGER IB
INTEGER IER
DOUBLE PRECISION INFSUM
INTEGER INT
DOUBLE PRECISION P
DOUBLE PRECISION P1
DOUBLE PRECISION PQ
DOUBLE PRECISION PROB
DOUBLE PRECISION PS
DOUBLE PRECISION PX
DOUBLE PRECISION Q
DOUBLE PRECISION TEMP
DOUBLE PRECISION WH
DOUBLE PRECISION X
DOUBLE PRECISION XB
DOUBLE PRECISION Y
C DOUBLE PRECISION FUNCTION DLGAMA.
C MACHINE PRECISION.
DATA EPS / 2.2D-16 /
C SMALLEST POSITIVE NUMBER REPRESENTABLE.
DATA EPS1 / 1.D-78 /
C NATURAL LOG OF EPS1.
DATA ALEPS / -179.6016D0 /
C CHECK RANGES OF THE ARGUMENTS.
Y = X
IF ( ( X .LE. 1.D0 ) .AND. ( X .GE. 0.D0 ) ) GO TO 10
IER = 1
GO TO 140
10 IF ( ( P .GT. 0.D0 ) .AND. ( Q .GT. 0.D0 ) ) GO TO 20
IER = 2
GO TO 140
20 IER = 0
IF ( X .GT. 0.5D0 ) GO TO 30
INT = 0
GO TO 40
C SWITCH ARGUMENT FOR MORE EFFICIENT USE OF POWER SERIES.
30 INT = 1
TEMP = P
P = Q
Q = TEMP
Y = 1.D0 - Y
40 IF ( X .NE. 0.D0 .AND. X .NE. 1.D0 ) GO TO 60
C SPECIAL CASE: X IS 0 OR 1.
50 PROB = 0.D0
GO TO 130
60 IB = Q
TEMP = IB
PS = Q - DBLE ( IB )
IF ( Q .EQ. TEMP ) PS = 1.D0
DP = P
DQ = Q
PX = DP * DLOG ( Y )
PQ = DLGAMA ( DP + DQ )
P1 = DLGAMA ( DP )
C = DLGAMA ( DQ )
D4 = DLOG ( DP )
C DLGAMA IS A FUNCTION WHICH CALCULATES THE DOUBLE
C PRECISION LOG GAMMA FUNCTION.
XB = PX + DLGAMA ( PS + DP ) - DLGAMA ( PS ) - D4 - P1
C SCALING
IB = XB / ALEPS
INFSUM = 0.D0
C FIRST TERM OF A DECREASING SERIES WILL UNDERFLOW.
IF ( IB .NE. 0 ) GO TO 90
INFSUM = DEXP ( XB )
CNT = INFSUM * DP
C CNT WILL EQUAL DEXP ( TEMP ) * ( 1.D0 - PS ) * I * P * Y**I / FACTORIAL ( I ).
WH = 0.0D0
80 WH = WH + 1.D0
CNT = CNT * ( WH - PS ) * Y / WH
XB = CNT / ( DP + WH )
INFSUM = INFSUM + XB
IF ( XB / EPS .GT. INFSUM ) GO TO 80
C DLGAMA IS A FUNCTION WHICH CALCULATES THE DOUBLE
C PRECISION LOG GAMMA FUNCTION.
90 FINSUM = 0.D0
IF ( DQ .LE. 1.D0 ) GO TO 120
XB = PX + DQ * DLOG ( 1.D0 - Y ) + PQ - P1 - DLOG ( DQ ) - C
C SCALING
IB = XB / ALEPS
IF ( IB .LT. 0 ) IB = 0
C = 1.D0 / ( 1.D0 - Y )
CNT = DEXP ( XB - FLOAT ( IB ) * ALEPS )
PS = DQ
WH = DQ
100 WH = WH - 1.D0
IF ( WH .LE. 0.0D0 ) GO TO 120
PX = ( PS * C ) / ( DP + WH )
IF ( PX .GT. 1.0D0 ) GO TO 105
IF ( CNT / EPS .LE. FINSUM .OR. CNT .LE. EPS1 / PX ) GO TO 120
105 CNT = CNT * PX
IF ( CNT .LE. 1.D0 ) GO TO 110
C RESCALE
IB = IB - 1
CNT = CNT * EPS1
110 PS = WH
IF ( IB .EQ. 0 ) FINSUM = FINSUM + CNT
GO TO 100
120 PROB = FINSUM + INFSUM
130 IF ( INT .EQ. 0 ) GO TO 140
PROB = 1.D0 - PROB
TEMP = P
P = Q
Q = TEMP
140 RETURN
END
SHAR_EOF
fi # end of overwriting check
cd ..
cd ..
cd ..
# End of shell archive
exit 0