If FX(x) takes the form given by Equation (7.93), we have
or
Now, consider FYn(y) defined by Equation (7.89). In view of Equation (7.93),
it takes the form
In the above, we have introduced into the equation the factor exp [g(un)]/n,
which is unity, as shown by Equation (7.97).
Since un is the mode or the ‘most likely’ value of Yn, function g(y) in
Equation (7.98) can be expanded in powers of (y un) in the form
where n dg(y)/ dy is evaluated at y un. It is positive, as g(y) is an increasing
function of y. Retaining only up to the linear term in Equation (7.99) and
substituting it into Equation (7.98), we obtain
in which n and un are functions only of n and not of y. Using the id entity
for any real c, Equation (7.100) tends, as n , to
which was to be proved. In arriving at Equation (7.101), we have assumed that
as n , FYn (y) converges to FY (y) as Yn converges to Y in some probabilistic
sense.
Some Important Continuous Distributions 229
1 expg
un 1
1
n
;
expg
un
n
1 : 7 : 97
FYn
yf 1 expg
ygn
1
expg
unexpg
y
n
n
1
expfg
yg
ung
n
n
:
7 : 98
g
yg
un (^) n
yun;
7 : 99
FYn
y 1
exp (^) n
yun
n
n
;
7 : 100
lim
n!1
1
c
n
n
exp
c;
!1
FY
yexpfexp
yug;
7 : 101