Characterization of Negative Exponential Distribution through Expectation ()
1. Introduction
Knowing characterizing property may provide unexpectedly accurate information about distributions and one can recognize a class of distributions before any statistical inference is made. This feature of characterization of probability distributions is peculiar to characterizing property and attracted attention of both theoretician and applied workers but there is no general theory of it.
Various approaches were used for characterization of negative exponential distribution. Among many other people, Fisz [1], Tanis [2], Rogers [3] and Fergusion [4] used properties of identical distributions, absolute continuity, constant regression of adjacent order statistics, linear regression of adjacent order statistics of random variables and characterized negative exponential distribution. Using independent and non-degenerate random variables Fergusion ([5,6]) and Crawford [7] characterized negative exponential distribution. Linear regression of two adjacent record values used by Nagaraja ([8,9],) were different from two conditional expectations, conditioned on a non-adjacent order statistics used by Khan [10] to characterize negative exponential distribution.
In this research note section 2 is devoted for characterization based on identity of distribution and equality of expectation function randomly variable for a negative exponential distribution with probability density function (pdf).
(1.1)
where
are known as constants,
is positive absolute continuous function and
is everywhere differentiable function. Since derivative of
is positive, the range is truncated by
from left
.
2. Characterization
Theorem 2.1 Let
be a random variable with distribution function
. Assume that
is continuous on the interval
, where
. Let
and
be two distinct differentiable and intregrable functions of X on the interval
where
and moreover
be non constant. Then
(2.1)
is the necessary and sufficient condition for pdf
of
to be
defined in (1.1).
Proof Given
defined in (1.1), for necessity of (2.1) if
is such that
where
is differentiable function then
(2.2)
Differentiating with respect to
on both sides of (2.2), replacing
for
and simplifying one gets
(2.3)
which establishes necessity of (2.1). Conversely given (2.1), let
be such that
(2.4)
which can be rewritten as
(2.5)
which reduces to
(2.6)
Hence
. (2.7)
Since
is increasing integrable and differentiable function on the interval
with
the following identity holds
. (2.8)
Differentiating
with respect to
and simplifying (2.8) after taking
as one factor, (2.8) reduces to
, (2.9)
where
is a function of
only derived in (2.3) and
is a function of
and
only derived in (2.7).
Since
be increasing integrable and differentiable function on the interval
where
and since
is positive intregrable function on the interval
where
with
and integrating (2.7) over the interval
on both sides, one gets (2.7) as
(2.10)
and
.
Substituting
in
derived in (2.10),
reduces to
defined in (1.1) which establishes sufficiency of (2.1).
Remark 2.1 Using
derived in (2.3), the
given in (1.1) can be determined by
(2.11)
and pdf is given by
(2.12)
where
is decreasing function for
with
such that it satisfies
. (2.13)
Illustrative Example: Using method described in the remark characterization of negative exponential distribution through survival function
is illustrated.






3. Conclusion
To characterize pdf defined in (1.1) one needs any arbitrary non-constant function of
which should only be differentiable and integrable.
NOTES