tplt(3f) - [M_datapac:LINE_PLOT] generates a Student's T probability
plot (with integer degrees of freedom parameter value NU).
SUBROUTINE TPLT(X,N,Nu)
REAL(kind=wp),intent(in) :: X(:)
INTEGER,intent(in) :: N
INTEGER,intent(in) :: Nu
TPLT(3f) generates a Student's T probability plot (with integer
degrees of freedom parameter value = NU).
The prototype Student's T distribution used herein is defined for all
X, and its probability density function is given in the references
below.
As used herein, a probability plot for a distribution is a plot
of the ordered observations versus the order statistic medians for
that distribution.
The Student's T probability plot is useful in graphically testing
the composite (that is, location and scale parameters need not be
specified) hypothesis that the underlying distribution from which
the data have been randomly drawn is the Student's T distribution
with degrees of freedom parameter value = NU.
If the hypothesis is true, the probability plot should be near-linear.
A measure of such linearity is given by the calculated probability
plot correlation coefficient.
X The vector of (unsorted or sorted) observations.
N The integer number of observations in the vector X.
The maximum allowable value of N for this subroutine is 7500.
NU The integer number of degrees of freedom.
NU should be positive.
A one-page Student's T probability plot.
Sample program:
program demo_tplt
use M_datapac, only : tplt
implicit none
! call tplt(x,y)
end program demo_tplt
Results:
The original DATAPAC library was written by James Filliben of the
Statistical Engineering Division, National Institute of Standards
and Technology.
John Urban, 2022.05.31
CC0-1.0
Type | Intent | Optional | Attributes | Name | ||
---|---|---|---|---|---|---|
real(kind=wp), | intent(in) | :: | X(:) | |||
integer, | intent(in) | :: | N | |||
integer, | intent(in) | :: | Nu |
Type | Attributes | Name | Initial | |||
---|---|---|---|---|---|---|
real | :: | WS(15000) |
SUBROUTINE TPLT(X,N,Nu) REAL(kind=wp),intent(in) :: X(:) INTEGER,intent(in) :: N INTEGER,intent(in) :: Nu REAL(kind=wp) :: W(7500), Y(7500) REAL(kind=wp) :: an, cc, hold, pp0025, pp025, pp975, pp9975, q, sum1, sum2, sum3, tau, wbar, WS, ybar, yint, yslope INTEGER :: i, iupper COMMON /BLOCK2_real64/ WS(15000) EQUIVALENCE (Y(1),WS(1)) EQUIVALENCE (W(1),WS(7501)) ! iupper = 7500 ! ! CHECK THE INPUT ARGUMENTS FOR ERRORS ! IF ( N<1 .OR. N>iupper ) THEN WRITE (G_IO,99001) iupper 99001 FORMAT ( & & ' ***** FATAL ERROR--THE SECOND INPUT ARGUMENT TO TPLT(3f) IS OUTSIDE THE ALLOWABLE (1,',I0,') INTERVAL *****') WRITE (G_IO,99007) N RETURN ELSEIF ( N==1 ) THEN WRITE (G_IO,99002) 99002 FORMAT (' ***** NON-FATAL DIAGNOSTIC--THE SECOND INPUT ARGUMENT TO TPLT(3f) HAS THE VALUE 1 *****') RETURN ELSE IF ( Nu<=0 ) THEN WRITE (G_IO,99003) 99003 FORMAT (' ***** FATAL ERROR--THE THIRD INPUT ARGUMENT TO TPLT(3f) IS NON-POSITIVE *****') WRITE (G_IO,99007) Nu RETURN ELSE hold = X(1) DO i = 2 , N IF ( X(i)/=hold ) GOTO 50 ENDDO WRITE (G_IO,99004) hold 99004 FORMAT (' ',& &'***** NON-FATAL DIAGNOSTIC--THE FIRST INPUT ARGUMENT (A VECTOR) TO TPLT(3f) HAS ALL ELEMENTS = ',E15.8,' *****') RETURN ENDIF ! !-----START POINT----------------------------------------------------- ! 50 continue an = N ! ! SORT THE DATA ! CALL SORT(X,N,Y) ! ! GENERATE UNIFORM ORDER STATISTIC MEDIANS ! CALL UNIMED(N,W) ! ! COMPUTE STUDENT'S T DISTRIBUTION ORDER STATISTIC MEDIANS ! DO i = 1 , N CALL TPPF(W(i),Nu,W(i)) ENDDO ! ! PLOT THE ORDERED OBSERVATIONS VERSUS ORDER STATISTICS MEDIANS. ! COMPUTE THE TAIL LENGTH MEASURE OF THE DISTRIBUTION. ! WRITE OUT THE TAIL LENGTH MEASURE OF THE DISTRIBUTION ! AND THE SAMPLE SIZE. ! CALL PLOT(Y,W,N) q = .9975_wp CALL TPPF(q,Nu,pp9975) q = .0025_wp CALL TPPF(q,Nu,pp0025) q = .975_wp CALL TPPF(q,Nu,pp975) q = .025_wp CALL TPPF(q,Nu,pp025) tau = (pp9975-pp0025)/(pp975-pp025) WRITE (G_IO,99005) Nu , tau , N ! 99005 FORMAT (' STUDENT''S T PROBABILITY PLOT WITH DEGREES OF FREEDOM = '& & ,I0,1X,'(TAU = ',E15.8,')',11X,'THE SAMPLE SIZE N = ',I0) ! ! COMPUTE THE PROBABILITY PLOT CORRELATION COEFFICIENT. ! COMPUTE LOCATION AND SCALE ESTIMATES ! FROM THE INTERCEPT AND SLOPE OF THE PROBABILITY PLOT. ! THEN WRITE THEM OUT. ! sum1 = 0.0_wp sum2 = 0.0_wp DO i = 1 , N sum1 = sum1 + Y(i) sum2 = sum2 + W(i) ENDDO ybar = sum1/an wbar = sum2/an sum1 = 0.0_wp sum2 = 0.0_wp sum3 = 0.0_wp DO i = 1 , N sum1 = sum1 + (Y(i)-ybar)*(Y(i)-ybar) sum2 = sum2 + (Y(i)-ybar)*(W(i)-wbar) sum3 = sum3 + (W(i)-wbar)*(W(i)-wbar) ENDDO cc = sum2/SQRT(sum3*sum1) yslope = sum2/sum3 yint = ybar - yslope*wbar WRITE (G_IO,99006) cc , yint , yslope 99006 FORMAT (' PROBABILITY PLOT CORRELATION COEFFICIENT = ',F8.5,& & 5X,'ESTIMATED INTERCEPT = ',E15.8,3X, & & 'ESTIMATED SLOPE = ',E15.8) ENDIF 99007 FORMAT (' ***** THE VALUE OF THE ARGUMENT IS ',I0,' *****') ! END SUBROUTINE TPLT