1. Introduction
Let
be a sequence of natural numbers
, and
be an
array associated with this sequence, whose entries
such that

The path of order k along
is defined to be a sequence of entries
as follows

The number of paths of order k will be denoted by

By neglecting the last row in
and then reconsidering it, we get the recurrence
(1)
When
, a is a constant,
then
(2)
and
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Khidr and El-Desouky [1] proved that, when ![]()
(3)
where
are the generalized Stirling numbers of the first kind associated with the sequence of real numbers
, defined by [1] - [6] ,
(4)
These numbers satisfy the recurrence relation
(5)
And
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Moreover, they introduced a special case of (3), when
, then the number of paths of order k,
is denoted by
; and proved that
(6)
where
are the Stirling numbers of the first kind defined by, see [2] [3]
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Also the generating function for
is given by
(7)
In this article, in Section 2, we derive a generalization of some results given in [1] , for the number of paths of
order k,
, when
. The generating function of
is given. In Section 3, we find the probability distribution for
and study some of their properties. The moment
generating function, skewness and kurtosis for
are investigated. Moreover special case and numerical results are given in Section 4.
2. Main Results
Theorem 1. The number of paths of order k is given by
(8)
Proof. Using (5) in (8), we get
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This by virtue of (1) completes the proof of (8).
Theorem 2. The generating function of the number of paths of order k is given by
(9)
Proof. Let the generating function of the number of paths of order k be denoted by
(10)
Using (1), we obtain
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and hence we get
![]()
where
. This completes the proof.
From (9), we get
![]()
where
and hence we have
(11)
where ![]()
For the special case
, we get
(12)
where ![]()
From (6) and (12), we have the identity
(13)
where ![]()
3. Some Applications
Let X, be the number of paths along
, then by virtue of (8) we have
(14)
On the other hand the moment generating function of the random variable X denoted by
, is given by the following theorem.
Theorem 3. The moment generating function of X, is given by
(15)
Proof. We begin by the definition of the moment generating function as follows.
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This completes the proof.
Corollary 1. The jth moments of X is
(16)
Proof. The jth moments can be obtained from the moment generating function,
where
![]()
This completes the proof.
Then from (16), we can calculate the mean and variance for the random variable X as follows.
(17)
(18)
hence the variance is given by
(19)
Corollary 2. The Skewness and kurtosis for the random variable X are given by
(20)
where
![]()
![]()
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Proof. We can find the jth moments about the mean by using
(21)
From (16) and (21), we can find the moments
about mean which can be used to calculate the skweness and kurtosis.
Special Case:
If
, from (14), we have
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and from (16) the jth moments has the form
![]()
and the mean is given by
![]()
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the variance can be obtained as follows.
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where we used
, see [3] .
4. Numerical Results
Setting
. Therefore the numerical values of
, are reduced to
, see [4] [5] .
From Equation (14), we can find the probability distribution of the number of paths X along
as follows
From (16), we can compute the 4th moments as follows.
The 4th moments about mean can be obtained as
The values of mean and variance can be obtained from (17) and (19) as follows.
![]()
The skewness and kurtosis, respectively can be obtained from (20) as follows.
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