Abstract
Asymptotic properties of the sequences
(a)
{
P
j
}
j
=
1
∞
$\{P^{j}\}_{j=1}^{\infty}$
and
(b)
{
j
−
1
∑
i
=
0
j
−
1
P
i
}
j
=
1
∞
$\{ j^{-1} \sum _{i=0}^{j-1} P^{i}\}_{j=1}^{\infty}$
are studied for g ∈ G = {f ∈ L
1(I) : f ≥ 0 and ‖f ‖ = 1}, where P : L
1(I) → L
1(I) is a Markov operator defined by
P
f
:=
∫
P
y
f
d
p
(
y
)
$Pf:= \int P_{y}f\, dp(y) $
for f ∈ L
1; {Py
}
y∈Y
is the family of the Frobenius-Perron operators associated with a family {φy
}
y∈Y
of nonsingular Markov maps defined on a subset I ⊆ ℝ
d
; and the index y runs over a probability space (Y, Σ(Y), p). Asymptotic properties of the sequences (a) and (b), of the Markov operator P, are closely connected with the asymptotic properties of the sequence of random vectors
x
j
=
φ
ξ
j
(
x
j
−
1
)
$x_{j}=\varphi_{\xi_{j}}(x_{j-1})$
for j = 1,2, . . .,where
{
ξ
j
}
j
=
1
∞
$\{\xi_{j}\}_{j=1}^{\infty}$
is a sequence of Y-valued independent random elements with common probability distribution p.
An operator-theoretic analogue of Rényi’s Condition is introduced for the family {Py
}
y∈Y
of the Frobenius-Perron operators. It is proved that under some additional assumptions this condition implies the L
1- convergence of the sequences (a) and (b) to a unique g
0 ∈ G. The general result is applied to some families {φy
}
y∈Y
of smooth Markov maps in ℝ
d
.
The space $D$ in several variables: random variables and higher moments
