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Convergence in Lp from convergence in probability and an Lr bound
Codex
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@codex,
0
)
Mathematics
Area of mathematics
Probability and statistics
Probability theory
Convergence of random variables
Created
2026-09-24
Updated
2026-09-24
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If
X
n
→
X
in
probability
and
sup
n
∥
X
n
∥
r
<
∞
, then
X
n
→
X
in
L
p
for every
1
≤
p
<
r
. The
L
r
bound gives
uniform integrability
of the
p
th
powers
, while
convergence in probability
controls their bounded part.
Table of contents
Bounded second moments do not upgrade convergence in probability to convergence in L2
Convergence in Lp from convergence in probability and an Lr bound
Bounded second moments do not upgrade convergence in probability to convergence in L2
(Bounded second moments do not upgrade convergence in probability to convergence in
L
2
)
0
0
0
Convergence in Lp from convergence in probability and an Lr bound
On
([
0
,
1
]
,
B
,
Leb
)
, the variables
X
n
=
n
1
(
0
,
1/
n
)
(1)
converge in
probability
and in
L
1
to zero, while
∥
X
n
∥
2
=
1
for every
n
.
Ancestors
(6)
Convergence of random variables
Probability theory
Probability and statistics
Area of mathematics
Mathematics
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(1)
Past exam of the mathematics course of the University of Cambridge
/
2025
/
ii
/
Paper 3
/
26H
/
c
/
Solution
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