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18      Modern  Spatiotemporal  Geostatistics —  Chapter 1

        on  a few  choices.  As  a  matter  of  fact,  the  case  of  the  indetermination  thesis
        implies that  one should  use a  more scientifically  sound method  in one's  effort
        to  choose an appropriate  model,  as is suggested by the  following  postulate.
        POSTULATE     1.3:  In  modern  Spatiotemporal  geostatistics,  the  rational
        approach  for  choosing  the  appropriate  model  from  the  data  is by  means
        of a theory  that represents the  physical  knowledge  available  and satisfies
        plausible  logical  principles  of  scientific  reasoning.
            The  meaning of  Postulate  1.3 is that, in addition  to  conforming  to  empiri-
        cal  evidence, there exist  physical knowledge (scientific  theories,  laws, etc.) and
        epistemic  criteria  (explanatory power,  informativeness, etc.) that  are capable
        of  singling out  one model from  a class  of empirically equivalent  models (or, at
        least,  capable of  narrowing the  choices considerably).  In this  sense,  Postulate
        1.3  is closely  related to  the  issue  of  scientific  content  addressed in  the  previ-
        ous  section.  As the  following example demonstrates, instead of fitting various
        mathematical  models  to  the  available data,  one could  fit  the  model  that  is
        justified on the  basis of a physical theory that  produces the specific set of  data.

        EXAMPLE   1.14:  Assume that  a  set of  temporal  burden  data  X(ti),  i  =
        l,...,m  on  a target  human  organ  subjected  to  pollutant  exposure is avail-
        able.  If  the  pure  induction  (theory-free)  approach  is  adopted,  several  valid
        covariance  functions



        could  be fitted  to  the  burden  data  by  means  of  a  conventional  data-fitting
        technique.  The question  then  arises:  Which  model  best describes the  temporal
        burden  correlations?  The  physics of  the  situation  offers  a  realistic  answer  to
        this  question.  The  burden X(t)  on a target  organ due to  exposure obeys the
        stochastic  first-order  kinematics





        where  A is the  transfer  rate  out  of  the  organ determined  from  the  data, U(t)
        is the  uptake  rate  (zero  mean,  white-noise  process with  a unit  variance),  and
        X(0)  — 0  is  the  initial  condition.  On  the  basis  of  the  law  (Eq. 1.3),  the
        theoretical  burden  covariance is given  by




        The  process  of  fitting  the  covariance model  (Eq. 1.4) to  the  burden  data
         has  physical  content,  which  was  not  the  case  with  the  arbitrary  functions
        Cfc(^i) ^2))  k  =  1,2,... of  Equation  1.2 above.
        Other  applications  of  the  important  Postulate  1.3 will  be  discussed  in  the
        following chapters (see e.g..  Chapter  7,  Example 7.5,  p. 143).
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