function pdf = point_distance_1d_pdf ( x, a, b ) %*****************************************************************************80 % %% POINT_DISTANCE_1D_PDF evaluates the point distance PDF in 1D. % % Discussion: % % It is assumed that a set of points has been generated in 1D % according to a Poisson process. The number of points in a region % of size LENGTH is a Poisson variate with mean value B * LENGTH. % % For a point chosen at random, we may now find the nearest % Poisson point, the second nearest and so on. We are interested % in the PDF that governs the expected behavior of the distances % of rank A = 1, 2, 3, ... with Poisson density B. % % Note that this PDF is a form of the Gamma PDF.??? % % Formula: % % PDF(X)(A,B) = B^A * X^( A - 1 ) * EXP ( - B * X ) / ( A - 1 )! % % Licensing: % % This code is distributed under the GNU LGPL license. % % Modified: % % 22 November 2004 % % Author: % % John Burkardt % % Parameters: % % Input, real X, the argument of the PDF. % 0.0 <= X. % % Input, integer A, indicates the degree of nearness of the point. % A = 1 means the nearest point, A = 2 the second nearest, and so on. % 0 < A. % % Input, real B, the point density. 0.0 < B. % % Output, real PDF, the value of the PDF. % if ( a < 1 ) fprintf ( 1, '\n' ); fprintf ( 1, 'POINT_DISTANCE_1D_PDF - Fatal error!\n' ); fprintf ( 1, ' Input parameter A < 1.\n' ); error ( 'POINT_DISTANCE_1D_PDF - Fatal error!' ); end if ( b <= 0.0 ) fprintf ( 1, '\n' ); fprintf ( 1, 'POINT_DISTANCE_1D_PDF - Fatal error!\n' ); fprintf ( 1, ' Input parameter B <= 0.0.\n' ); error ( 'POINT_DISTANCE_1D_PDF - Fatal error!' ); end if ( x < 0.0 ) pdf = 0.0; else pdf = b ^ a * x ^ ( a - 1 ) * exp ( - b * x ) / r8_factorial ( a - 1 ); end return end