Lower Lebesgue integral for ℝ≥0∞
-valued functions #
We define the lower Lebesgue integral of an ℝ≥0∞
-valued function.
Notation #
We introduce the following notation for the lower Lebesgue integral of a function f : α → ℝ≥0∞
.
∫⁻ x, f x ∂μ
: integral of a functionf : α → ℝ≥0∞
with respect to a measureμ
;∫⁻ x, f x
: integral of a functionf : α → ℝ≥0∞
with respect to the canonical measurevolume
onα
;∫⁻ x in s, f x ∂μ
: integral of a functionf : α → ℝ≥0∞
over a sets
with respect to a measureμ
, defined as∫⁻ x, f x ∂(μ.restrict s)
;∫⁻ x in s, f x
: integral of a functionf : α → ℝ≥0∞
over a sets
with respect to the canonical measurevolume
, defined as∫⁻ x, f x ∂(volume.restrict s)
.
The lower Lebesgue integral of a function f
with respect to a measure μ
.
Equations
Instances For
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will not be parsed correctly,
and needs parentheses. We do not set the binding power of r
to 0
, because then
∫⁻ x, f x = 0
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The lower Lebesgue integral of a function f
with respect to a measure μ
.
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The lower Lebesgue integral of a function f
with respect to a measure μ
.
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The lower Lebesgue integral of a function f
with respect to a measure μ
.
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Instances For
The lower Lebesgue integral of a function f
with respect to a measure μ
.
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Alias of MeasureTheory.setLIntegral_const
.
Alias of MeasureTheory.setLIntegral_one
.
Alias of MeasureTheory.setLIntegral_const_lt_top
.
For any function f : α → ℝ≥0∞
, there exists a measurable function g ≤ f
with the same
integral.
∫⁻ a in s, f a ∂μ
is defined as the supremum of integrals of simple functions
φ : α →ₛ ℝ≥0∞
such that φ ≤ f
. This lemma says that it suffices to take
functions φ : α →ₛ ℝ≥0
.
Lebesgue integral over a set is monotone in function.
This version assumes that the upper estimate is an a.e. measurable function
and the estimate holds a.e. on the set.
See also setLIntegral_mono_ae'
for a version that assumes measurability of the set
but assumes no regularity of either function.
Alias of MeasureTheory.setLIntegral_mono_ae
.
Lebesgue integral over a set is monotone in function.
This version assumes that the upper estimate is an a.e. measurable function
and the estimate holds a.e. on the set.
See also setLIntegral_mono_ae'
for a version that assumes measurability of the set
but assumes no regularity of either function.
Alias of MeasureTheory.setLIntegral_mono
.
Alias of MeasureTheory.setLIntegral_mono_ae'
.
Alias of MeasureTheory.setLIntegral_mono'
.
Alias of MeasureTheory.setLIntegral_le_lintegral
.
Alias of MeasureTheory.setLIntegral_congr
.
Alias of MeasureTheory.setLIntegral_congr_fun
.
Monotone convergence theorem -- sometimes called Beppo-Levi convergence.
See lintegral_iSup_directed
for a more general form.
Monotone convergence theorem -- sometimes called Beppo-Levi convergence. Version with ae_measurable functions.
Monotone convergence theorem expressed with limits
If f
has finite integral, then ∫⁻ x in s, f x ∂μ
is absolutely continuous in s
: it tends
to zero as μ s
tends to zero. This lemma states this fact in terms of ε
and δ
.
Alias of MeasureTheory.exists_pos_setLIntegral_lt_of_measure_lt
.
If f
has finite integral, then ∫⁻ x in s, f x ∂μ
is absolutely continuous in s
: it tends
to zero as μ s
tends to zero. This lemma states this fact in terms of ε
and δ
.
If f
has finite integral, then ∫⁻ x in s, f x ∂μ
is absolutely continuous in s
: it tends
to zero as μ s
tends to zero.
Alias of MeasureTheory.tendsto_setLIntegral_zero
.
If f
has finite integral, then ∫⁻ x in s, f x ∂μ
is absolutely continuous in s
: it tends
to zero as μ s
tends to zero.
The sum of the lower Lebesgue integrals of two functions is less than or equal to the integral of their sum. The other inequality needs one of these functions to be (a.e.-)measurable.
If f g : α → ℝ≥0∞
are two functions and one of them is (a.e.) measurable, then the Lebesgue
integral of f + g
equals the sum of integrals. This lemma assumes that f
is integrable, see also
MeasureTheory.lintegral_add_right
and primed versions of these lemmas.
If f g : α → ℝ≥0∞
are two functions and one of them is (a.e.) measurable, then the Lebesgue
integral of f + g
equals the sum of integrals. This lemma assumes that g
is integrable, see also
MeasureTheory.lintegral_add_left
and primed versions of these lemmas.
Alias of MeasureTheory.setLIntegral_smul_measure
.
Alias of MeasureTheory.setLIntegral_empty
.
Alias of MeasureTheory.setLIntegral_univ
.
Alias of MeasureTheory.setLIntegral_measure_zero
.
Alias of MeasureTheory.setLIntegral_eq_const
.
A version of Markov's inequality for two functions. It doesn't follow from the standard
Markov's inequality because we only assume measurability of g
, not f
.
Markov's inequality also known as Chebyshev's first inequality.
Markov's inequality also known as Chebyshev's first inequality. For a version assuming
AEMeasurable
, see mul_meas_ge_le_lintegral₀
.
Markov's inequality, also known as Chebyshev's first inequality.
Weaker version of the monotone convergence theorem
Alias of MeasureTheory.setLIntegral_strict_mono
.
Monotone convergence theorem for nonincreasing sequences of functions
Monotone convergence theorem for nonincreasing sequences of functions
Monotone convergence for an infimum over a directed family and indexed by a countable type
Known as Fatou's lemma, version with AEMeasurable
functions
Known as Fatou's lemma
Dominated convergence theorem for nonnegative functions
Dominated convergence theorem for nonnegative functions which are just almost everywhere measurable.
Dominated convergence theorem for filters with a countable basis
Monotone convergence for a supremum over a directed family and indexed by a countable type
Monotone convergence for a supremum over a directed family and indexed by a countable type.
Alias of MeasureTheory.setLIntegral_max
.
Alias of MeasureTheory.setLIntegral_map
.
If g : α → β
is a measurable embedding and f : β → ℝ≥0∞
is any function (not necessarily
measurable), then ∫⁻ a, f a ∂(map g μ) = ∫⁻ a, f (g a) ∂μ
. Compare with lintegral_map
which
applies to any measurable g : α → β
but requires that f
is measurable as well.
The lintegral
transforms appropriately under a measurable equivalence g : α ≃ᵐ β
.
(Compare lintegral_map
, which applies to a wider class of functions g : α → β
, but requires
measurability of the function being integrated.)
Alias of MeasureTheory.MeasurePreserving.setLIntegral_comp_preimage
.
Alias of MeasureTheory.MeasurePreserving.setLIntegral_comp_preimage_emb
.
Alias of MeasureTheory.MeasurePreserving.setLIntegral_comp_emb
.
If f : α → ℝ≥0∞
has finite integral, then there exists a measurable set s
of finite measure
such that the integral of f
over sᶜ
is less than a given positive number.
Also used to prove an Lᵖ
-norm version in MeasureTheory.Memℒp.exists_snorm_indicator_compl_le
.
For any function f : α → ℝ≥0∞
, there exists a measurable function g ≤ f
with the same
integral over any measurable set.
Alias of MeasureTheory.setLIntegral_subtype
.
Alias of MeasureTheory.setLIntegral_dirac'
.
Alias of MeasureTheory.setLIntegral_dirac
.
Markov's inequality for the counting measure with hypothesis using tsum
in ℝ≥0∞
.
Markov's inequality for counting measure with hypothesis using tsum
in ℝ≥0
.
Lebesgue integral over finite and countable types and sets #
Lebesgue integral of a bounded function over a set of finite measure is finite.
Note that this lemma assumes no regularity of either f
or s
.
Lebesgue integral of a bounded function over a set of finite measure is finite.
Note that this lemma assumes no regularity of either f
or s
.
Alias of MeasureTheory.setLIntegral_lt_top_of_bddAbove
.
Lebesgue integral of a bounded function over a set of finite measure is finite.
Note that this lemma assumes no regularity of either f
or s
.
If a monotone sequence of functions has an upper bound and the sequence of integrals of these functions tends to the integral of the upper bound, then the sequence of functions converges almost everywhere to the upper bound. Auxiliary version assuming moreover that the functions in the sequence are ae measurable.
If a monotone sequence of functions has an upper bound and the sequence of integrals of these functions tends to the integral of the upper bound, then the sequence of functions converges almost everywhere to the upper bound.
If an antitone sequence of functions has a lower bound and the sequence of integrals of these functions tends to the integral of the lower bound, then the sequence of functions converges almost everywhere to the lower bound.
If μ
is an s-finite measure, then for any function f
there exists a measurable function g ≤ f
that has the same Lebesgue integral over every set.
For the integral over the whole space, the statement is true without extra assumptions,
see exists_measurable_le_lintegral_eq
.
See also MeasureTheory.Measure.restrict_toMeasurable_of_sFinite
for a similar result.
In a sigma-finite measure space, there exists an integrable function which is positive everywhere (and with an arbitrarily small integral).
If the Lebesgue integral of a function is bounded by some constant on all sets with finite measure in a sub-σ-algebra and the measure is σ-finite on that sub-σ-algebra, then the integral over the whole space is bounded by that same constant.
Alias of MeasureTheory.lintegral_le_of_forall_fin_meas_trim_le
.
If the Lebesgue integral of a function is bounded by some constant on all sets with finite measure in a sub-σ-algebra and the measure is σ-finite on that sub-σ-algebra, then the integral over the whole space is bounded by that same constant.
Alias of MeasureTheory.lintegral_le_of_forall_fin_meas_trim_le
.
If the Lebesgue integral of a function is bounded by some constant on all sets with finite measure in a sub-σ-algebra and the measure is σ-finite on that sub-σ-algebra, then the integral over the whole space is bounded by that same constant.
If the Lebesgue integral of a function is bounded by some constant on all sets with finite measure and the measure is σ-finite, then the integral over the whole space is bounded by that same constant.
If the indicators of measurable sets Aᵢ
tend pointwise almost everywhere to the indicator
of a measurable set A
and we eventually have Aᵢ ⊆ B
for some set B
of finite measure, then
the measures of Aᵢ
tend to the measure of A
.
If μ
is a finite measure and the indicators of measurable sets Aᵢ
tend pointwise
almost everywhere to the indicator of a measurable set A
, then the measures μ Aᵢ
tend to
the measure μ A
.