--- a/src/HOL/Probability/Euclidean_Lebesgue.thy Wed Dec 01 18:00:40 2010 +0100
+++ /dev/null Thu Jan 01 00:00:00 1970 +0000
@@ -1,212 +0,0 @@
-theory Euclidean_Lebesgue
- imports Lebesgue_Integration Lebesgue_Measure
-begin
-
-lemma simple_function_has_integral:
- fixes f::"'a::ordered_euclidean_space \<Rightarrow> pinfreal"
- assumes f:"lebesgue.simple_function f"
- and f':"\<forall>x. f x \<noteq> \<omega>"
- and om:"\<forall>x\<in>range f. lmeasure (f -` {x} \<inter> UNIV) = \<omega> \<longrightarrow> x = 0"
- shows "((\<lambda>x. real (f x)) has_integral (real (lebesgue.simple_integral f))) UNIV"
- unfolding lebesgue.simple_integral_def
- apply(subst lebesgue_simple_function_indicator[OF f])
-proof- case goal1
- have *:"\<And>x. \<forall>y\<in>range f. y * indicator (f -` {y}) x \<noteq> \<omega>"
- "\<forall>x\<in>range f. x * lmeasure (f -` {x} \<inter> UNIV) \<noteq> \<omega>"
- using f' om unfolding indicator_def by auto
- show ?case unfolding space_lebesgue_space real_of_pinfreal_setsum'[OF *(1),THEN sym]
- unfolding real_of_pinfreal_setsum'[OF *(2),THEN sym]
- unfolding real_of_pinfreal_setsum space_lebesgue_space
- apply(rule has_integral_setsum)
- proof safe show "finite (range f)" using f by (auto dest: lebesgue.simple_functionD)
- fix y::'a show "((\<lambda>x. real (f y * indicator (f -` {f y}) x)) has_integral
- real (f y * lmeasure (f -` {f y} \<inter> UNIV))) UNIV"
- proof(cases "f y = 0") case False
- have mea:"gmeasurable (f -` {f y})" apply(rule glmeasurable_finite)
- using assms unfolding lebesgue.simple_function_def using False by auto
- have *:"\<And>x. real (indicator (f -` {f y}) x::pinfreal) = (if x \<in> f -` {f y} then 1 else 0)" by auto
- show ?thesis unfolding real_of_pinfreal_mult[THEN sym]
- apply(rule has_integral_cmul[where 'b=real, unfolded real_scaleR_def])
- unfolding Int_UNIV_right lmeasure_gmeasure[OF mea,THEN sym]
- unfolding measure_integral_univ[OF mea] * apply(rule integrable_integral)
- unfolding gmeasurable_integrable[THEN sym] using mea .
- qed auto
- qed qed
-
-lemma (in measure_space) positive_integral_omega:
- assumes "f \<in> borel_measurable M"
- and "positive_integral f \<noteq> \<omega>"
- shows "\<mu> (f -` {\<omega>} \<inter> space M) = 0"
-proof -
- have "\<omega> * \<mu> (f -` {\<omega>} \<inter> space M) = positive_integral (\<lambda>x. \<omega> * indicator (f -` {\<omega>} \<inter> space M) x)"
- using positive_integral_cmult_indicator[OF borel_measurable_vimage, OF assms(1), of \<omega> \<omega>] by simp
- also have "\<dots> \<le> positive_integral f"
- by (auto intro!: positive_integral_mono simp: indicator_def)
- finally show ?thesis
- using assms(2) by (cases ?thesis) auto
-qed
-
-lemma (in measure_space) simple_integral_omega:
- assumes "simple_function f"
- and "simple_integral f \<noteq> \<omega>"
- shows "\<mu> (f -` {\<omega>} \<inter> space M) = 0"
-proof (rule positive_integral_omega)
- show "f \<in> borel_measurable M" using assms by (auto intro: borel_measurable_simple_function)
- show "positive_integral f \<noteq> \<omega>"
- using assms by (simp add: positive_integral_eq_simple_integral)
-qed
-
-lemma bounded_realI: assumes "\<forall>x\<in>s. abs (x::real) \<le> B" shows "bounded s"
- unfolding bounded_def dist_real_def apply(rule_tac x=0 in exI)
- using assms by auto
-
-lemma simple_function_has_integral':
- fixes f::"'a::ordered_euclidean_space \<Rightarrow> pinfreal"
- assumes f:"lebesgue.simple_function f"
- and i: "lebesgue.simple_integral f \<noteq> \<omega>"
- shows "((\<lambda>x. real (f x)) has_integral (real (lebesgue.simple_integral f))) UNIV"
-proof- let ?f = "\<lambda>x. if f x = \<omega> then 0 else f x"
- { fix x have "real (f x) = real (?f x)" by (cases "f x") auto } note * = this
- have **:"{x. f x \<noteq> ?f x} = f -` {\<omega>}" by auto
- have **:"lmeasure {x\<in>space lebesgue_space. f x \<noteq> ?f x} = 0"
- using lebesgue.simple_integral_omega[OF assms] by(auto simp add:**)
- show ?thesis apply(subst lebesgue.simple_integral_cong'[OF f _ **])
- apply(rule lebesgue.simple_function_compose1[OF f])
- unfolding * defer apply(rule simple_function_has_integral)
- proof-
- show "lebesgue.simple_function ?f"
- using lebesgue.simple_function_compose1[OF f] .
- show "\<forall>x. ?f x \<noteq> \<omega>" by auto
- show "\<forall>x\<in>range ?f. lmeasure (?f -` {x} \<inter> UNIV) = \<omega> \<longrightarrow> x = 0"
- proof (safe, simp, safe, rule ccontr)
- fix y assume "f y \<noteq> \<omega>" "f y \<noteq> 0"
- hence "(\<lambda>x. if f x = \<omega> then 0 else f x) -` {if f y = \<omega> then 0 else f y} = f -` {f y}"
- by (auto split: split_if_asm)
- moreover assume "lmeasure ((\<lambda>x. if f x = \<omega> then 0 else f x) -` {if f y = \<omega> then 0 else f y}) = \<omega>"
- ultimately have "lmeasure (f -` {f y}) = \<omega>" by simp
- moreover
- have "f y * lmeasure (f -` {f y}) \<noteq> \<omega>" using i f
- unfolding lebesgue.simple_integral_def setsum_\<omega> lebesgue.simple_function_def
- by auto
- ultimately have "f y = 0" by (auto split: split_if_asm)
- then show False using `f y \<noteq> 0` by simp
- qed
- qed
-qed
-
-lemma (in measure_space) positive_integral_monotone_convergence:
- fixes f::"nat \<Rightarrow> 'a \<Rightarrow> pinfreal"
- assumes i: "\<And>i. f i \<in> borel_measurable M" and mono: "\<And>x. mono (\<lambda>n. f n x)"
- and lim: "\<And>x. (\<lambda>i. f i x) ----> u x"
- shows "u \<in> borel_measurable M"
- and "(\<lambda>i. positive_integral (f i)) ----> positive_integral u" (is ?ilim)
-proof -
- from positive_integral_isoton[unfolded isoton_fun_expand isoton_iff_Lim_mono, of f u]
- show ?ilim using mono lim i by auto
- have "(SUP i. f i) = u" using mono lim SUP_Lim_pinfreal
- unfolding fun_eq_iff SUPR_fun_expand mono_def by auto
- moreover have "(SUP i. f i) \<in> borel_measurable M"
- using i by (rule borel_measurable_SUP)
- ultimately show "u \<in> borel_measurable M" by simp
-qed
-
-lemma positive_integral_has_integral:
- fixes f::"'a::ordered_euclidean_space => pinfreal"
- assumes f:"f \<in> borel_measurable lebesgue_space"
- and int_om:"lebesgue.positive_integral f \<noteq> \<omega>"
- and f_om:"\<forall>x. f x \<noteq> \<omega>" (* TODO: remove this *)
- shows "((\<lambda>x. real (f x)) has_integral (real (lebesgue.positive_integral f))) UNIV"
-proof- let ?i = "lebesgue.positive_integral f"
- from lebesgue.borel_measurable_implies_simple_function_sequence[OF f]
- guess u .. note conjunctD2[OF this,rule_format] note u = conjunctD2[OF this(1)] this(2)
- let ?u = "\<lambda>i x. real (u i x)" and ?f = "\<lambda>x. real (f x)"
- have u_simple:"\<And>k. lebesgue.simple_integral (u k) = lebesgue.positive_integral (u k)"
- apply(subst lebesgue.positive_integral_eq_simple_integral[THEN sym,OF u(1)]) ..
- have int_u_le:"\<And>k. lebesgue.simple_integral (u k) \<le> lebesgue.positive_integral f"
- unfolding u_simple apply(rule lebesgue.positive_integral_mono)
- using isoton_Sup[OF u(3)] unfolding le_fun_def by auto
- have u_int_om:"\<And>i. lebesgue.simple_integral (u i) \<noteq> \<omega>"
- proof- case goal1 thus ?case using int_u_le[of i] int_om by auto qed
-
- note u_int = simple_function_has_integral'[OF u(1) this]
- have "(\<lambda>x. real (f x)) integrable_on UNIV \<and>
- (\<lambda>k. gintegral UNIV (\<lambda>x. real (u k x))) ----> gintegral UNIV (\<lambda>x. real (f x))"
- apply(rule monotone_convergence_increasing) apply(rule,rule,rule u_int)
- proof safe case goal1 show ?case apply(rule real_of_pinfreal_mono) using u(2,3) by auto
- next case goal2 show ?case using u(3) apply(subst lim_Real[THEN sym])
- prefer 3 apply(subst Real_real') defer apply(subst Real_real')
- using isotone_Lim[OF u(3)[unfolded isoton_fun_expand, THEN spec]] using f_om u by auto
- next case goal3
- show ?case apply(rule bounded_realI[where B="real (lebesgue.positive_integral f)"])
- apply safe apply(subst abs_of_nonneg) apply(rule integral_nonneg,rule) apply(rule u_int)
- unfolding integral_unique[OF u_int] defer apply(rule real_of_pinfreal_mono[OF _ int_u_le])
- using u int_om by auto
- qed note int = conjunctD2[OF this]
-
- have "(\<lambda>i. lebesgue.simple_integral (u i)) ----> ?i" unfolding u_simple
- apply(rule lebesgue.positive_integral_monotone_convergence(2))
- apply(rule lebesgue.borel_measurable_simple_function[OF u(1)])
- using isotone_Lim[OF u(3)[unfolded isoton_fun_expand, THEN spec]] by auto
- hence "(\<lambda>i. real (lebesgue.simple_integral (u i))) ----> real ?i" apply-
- apply(subst lim_Real[THEN sym]) prefer 3
- apply(subst Real_real') defer apply(subst Real_real')
- using u f_om int_om u_int_om by auto
- note * = LIMSEQ_unique[OF this int(2)[unfolded integral_unique[OF u_int]]]
- show ?thesis unfolding * by(rule integrable_integral[OF int(1)])
-qed
-
-lemma lebesgue_integral_has_integral:
- fixes f::"'a::ordered_euclidean_space => real"
- assumes f:"lebesgue.integrable f"
- shows "(f has_integral (lebesgue.integral f)) UNIV"
-proof- let ?n = "\<lambda>x. - min (f x) 0" and ?p = "\<lambda>x. max (f x) 0"
- have *:"f = (\<lambda>x. ?p x - ?n x)" apply rule by auto
- note f = lebesgue.integrableD[OF f]
- show ?thesis unfolding lebesgue.integral_def apply(subst *)
- proof(rule has_integral_sub) case goal1
- have *:"\<forall>x. Real (f x) \<noteq> \<omega>" by auto
- note lebesgue.borel_measurable_Real[OF f(1)]
- from positive_integral_has_integral[OF this f(2) *]
- show ?case unfolding real_Real_max .
- next case goal2
- have *:"\<forall>x. Real (- f x) \<noteq> \<omega>" by auto
- note lebesgue.borel_measurable_uminus[OF f(1)]
- note lebesgue.borel_measurable_Real[OF this]
- from positive_integral_has_integral[OF this f(3) *]
- show ?case unfolding real_Real_max minus_min_eq_max by auto
- qed
-qed
-
-lemma lmeasurable_imp_borel[dest]: fixes s::"'a::ordered_euclidean_space set"
- assumes "s \<in> sets borel_space" shows "lmeasurable s"
-proof- let ?S = "range (\<lambda>(a, b). {a .. (b :: 'a\<Colon>ordered_euclidean_space)})"
- have *:"?S \<subseteq> sets lebesgue_space" by auto
- have "s \<in> sigma_sets UNIV ?S" using assms
- unfolding borel_space_eq_atLeastAtMost by (simp add: sigma_def)
- thus ?thesis using lebesgue.sigma_subset[of ?S,unfolded sets_sigma,OF *]
- by auto
-qed
-
-lemma lmeasurable_open[dest]:
- assumes "open s" shows "lmeasurable s"
-proof- have "s \<in> sets borel_space" using assms by auto
- thus ?thesis by auto qed
-
-lemma continuous_on_imp_borel_measurable:
- fixes f::"'a::ordered_euclidean_space \<Rightarrow> 'b::ordered_euclidean_space"
- assumes "continuous_on UNIV f"
- shows "f \<in> borel_measurable lebesgue_space"
- apply(rule lebesgue.borel_measurableI)
- unfolding lebesgue_measurable apply(rule lmeasurable_open)
- using continuous_open_preimage[OF assms] unfolding vimage_def by auto
-
-
-lemma (in measure_space) integral_monotone_convergence_pos':
- assumes i: "\<And>i. integrable (f i)" and mono: "\<And>x. mono (\<lambda>n. f n x)"
- and pos: "\<And>x i. 0 \<le> f i x"
- and lim: "\<And>x. (\<lambda>i. f i x) ----> u x"
- and ilim: "(\<lambda>i. integral (f i)) ----> x"
- shows "integrable u \<and> integral u = x"
- using integral_monotone_convergence_pos[OF assms] by auto
-
-end