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Datei: Levy.thy Sprache: Isabelle

Original von: Isabelle^©

(* Title: HOL/Probability/Levy.thy
 Authors: Jeremy Avigad (CMU)
*)

section \<open>The Levy inversion theorem, and the Levy continuity theorem.\<close>

theory Levy
 imports Characteristic_Functions Helly_Selection Sinc_Integral
begin

subsection \<open>The Levy inversion theorem\<close>

(* Actually, this is not needed for us -- but it is useful for other purposes. (See Billingsley.) *)
lemma Levy_Inversion_aux1:
 fixes a b :: real
 assumes "a \ b"
 shows "((\t. (iexp (-(t * a)) - iexp (-(t * b))) / (\ * t)) \ b - a) (at 0)"
 (is "(?F \ _) (at _)")
proof -
 have 1: "cmod (?F t - (b - a)) \ a^2 / 2 * abs t + b^2 / 2 * abs t" if "t \ 0" for t
 proof -
 have "cmod (?F t - (b - a)) = cmod (
 (iexp (-(t * a)) - (1 + \ * -(t * a))) / (\ * t) -
 (iexp (-(t * b)) - (1 + \ * -(t * b))) / (\ * t))"
 (is "_ = cmod (?one / (\ * t) - ?two / (\ * t))")
 using \<open>t \<noteq> 0\<close> by (intro arg_cong[where f=norm]) (simp add: field_simps)
 also have "\ \ cmod (?one / (\ * t)) + cmod (?two / (\ * t))"
 by (rule norm_triangle_ineq4)
 also have "cmod (?one / (\ * t)) = cmod ?one / abs t"
 by (simp add: norm_divide norm_mult)
 also have "cmod (?two / (\ * t)) = cmod ?two / abs t"
 by (simp add: norm_divide norm_mult)
 also have "cmod ?one / abs t + cmod ?two / abs t \
 ((- (a * t))^2 / 2) / abs t + ((- (b * t))^2 / 2) / abs t"
 apply (rule add_mono)
 apply (rule divide_right_mono)
 using iexp_approx1 [of "-(t * a)" 1] apply (simp add: field_simps eval_nat_numeral)
 apply force
 apply (rule divide_right_mono)
 using iexp_approx1 [of "-(t * b)" 1] apply (simp add: field_simps eval_nat_numeral)
 by force
 also have "\ = a^2 / 2 * abs t + b^2 / 2 * abs t"
 using \<open>t \<noteq> 0\<close> apply (case_tac "t \<ge> 0", simp add: field_simps power2_eq_square)
 using \<open>t \<noteq> 0\<close> by (subst (1 2) abs_of_neg, auto simp add: field_simps power2_eq_square)
 finally show "cmod (?F t - (b - a)) \ a^2 / 2 * abs t + b^2 / 2 * abs t" .
 qed
 show ?thesis
 apply (rule LIM_zero_cancel)
 apply (rule tendsto_norm_zero_cancel)
 apply (rule real_LIM_sandwich_zero [OF _ _ 1])
 apply (auto intro!: tendsto_eq_intros)
 done
qed

lemma Levy_Inversion_aux2:
 fixes a b t :: real
 assumes "a \ b" and "t \ 0"
 shows "cmod ((iexp (t * b) - iexp (t * a)) / (\ * t)) \ b - a" (is "?F \ _")
proof -
 have "?F = cmod (iexp (t * a) * (iexp (t * (b - a)) - 1) / (\ * t))"
 using \<open>t \<noteq> 0\<close> by (intro arg_cong[where f=norm]) (simp add: field_simps exp_diff exp_minus)
 also have "\ = cmod (iexp (t * (b - a)) - 1) / abs t"
 unfolding norm_divide norm_mult norm_exp_i_times using \<open>t \<noteq> 0\<close>
 by (simp add: complex_eq_iff norm_mult)
 also have "\ \ abs (t * (b - a)) / abs t"
 using iexp_approx1 [of "t * (b - a)" 0]
 by (intro divide_right_mono) (auto simp add: field_simps eval_nat_numeral)
 also have "\ = b - a"
 using assms by (auto simp add: abs_mult)
 finally show ?thesis .
qed

(* TODO: refactor! *)
theorem (in real_distribution) Levy_Inversion:
 fixes a b :: real
 assumes "a \ b"
 defines "\ \ measure M" and "\ \ char M"
 assumes "\ {a} = 0" and "\ {b} = 0"
 shows "(\T. 1 / (2 * pi) * (CLBINT t=-T..T. (iexp (-(t * a)) - iexp (-(t * b))) / (\ * t) * \ t))
 \<longlonglongrightarrow> \<mu> {a<..b}"
 (is "(\T. 1 / (2 * pi) * (CLBINT t=-T..T. ?F t * \ t)) \ of_real (\ {a<..b})")
proof -
 interpret P: pair_sigma_finite lborel M ..
 from bounded_Si obtain B where Bprop: "\T. abs (Si T) \ B" by auto
 from Bprop [of 0] have [simp]: "B \ 0" by auto
 let ?f = "\t x :: real. (iexp (t * (x - a)) - iexp(t * (x - b))) / (\ * t)"
 { fix T :: real
 assume "T \ 0"
 let ?f' = "\(t, x). indicator {-T<..R ?f t x"
 { fix x
 have 1: "complex_interval_lebesgue_integrable lborel u v (\t. ?f t x)" for u v :: real
 using Levy_Inversion_aux2[of "x - b" "x - a"]
 apply (simp add: interval_lebesgue_integrable_def set_integrable_def del: times_divide_eq_left)
 apply (intro integrableI_bounded_set_indicator[where B="b - a"] conjI impI)
 apply (auto intro!: AE_I [of _ _ "{0}"] simp: assms)
 done
 have "(CLBINT t. ?f' (t, x)) = (CLBINT t=-T..T. ?f t x)"
 using \<open>T \<ge> 0\<close> by (simp add: interval_lebesgue_integral_def set_lebesgue_integral_def)
 also have "\ = (CLBINT t=-T..(0 :: real). ?f t x) + (CLBINT t=(0 :: real)..T. ?f t x)"
 (is "_ = _ + ?t")
 using 1 by (intro interval_integral_sum[symmetric]) (simp add: min_absorb1 max_absorb2 \<open>T \<ge> 0\<close>)
 also have "(CLBINT t=-T..(0 :: real). ?f t x) = (CLBINT t=(0::real)..T. ?f (-t) x)"
 by (subst interval_integral_reflect) auto
 also have "\ + ?t = (CLBINT t=(0::real)..T. ?f (-t) x + ?f t x)"
 using 1
 by (intro interval_lebesgue_integral_add(2) [symmetric] interval_integrable_mirror[THEN iffD2]) simp_all
 also have "\ = (CLBINT t=(0::real)..T. ((iexp(t * (x - a)) - iexp (-(t * (x - a)))) -
 (iexp(t * (x - b)) - iexp (-(t * (x - b))))) / (\ * t))"
 using \<open>T \<ge> 0\<close> by (intro interval_integral_cong) (auto simp add: field_split_simps)
 also have "\ = (CLBINT t=(0::real)..T. complex_of_real(
 2 * (sin (t * (x - a)) / t) - 2 * (sin (t * (x - b)) / t)))"
 using \<open>T \<ge> 0\<close>
 apply (intro interval_integral_cong)
 apply (simp add: field_simps cis.ctr Im_divide Re_divide Im_exp Re_exp complex_eq_iff)
 unfolding minus_diff_eq[symmetric, of "y * x" "y * a" for y a] sin_minus cos_minus
 apply (simp add: field_simps power2_eq_square)
 done
 also have "\ = complex_of_real (LBINT t=(0::real)..T.
 2 * (sin (t * (x - a)) / t) - 2 * (sin (t * (x - b)) / t))"
 by (rule interval_lebesgue_integral_of_real)
 also have "\ = complex_of_real (2 * (sgn (x - a) * Si (T * abs (x - a)) -
 sgn (x - b) * Si (T * abs (x - b))))"
 apply (subst interval_lebesgue_integral_diff)
 apply (rule interval_lebesgue_integrable_mult_right, rule integrable_sinc')+
 apply (subst interval_lebesgue_integral_mult_right)+
 apply (simp add: zero_ereal_def[symmetric] LBINT_I0c_sin_scale_divide[OF \<open>T \<ge> 0\<close>])
 done
 finally have "(CLBINT t. ?f' (t, x)) =
 2 * (sgn (x - a) * Si (T * abs (x - a)) - sgn (x - b) * Si (T * abs (x - b)))" .
 } note main_eq = this
 have "(CLBINT t=-T..T. ?F t * \ t) =
 (CLBINT t. (CLINT x | M. ?F t * iexp (t * x) * indicator {-T<..<T} t))"
 using \<open>T \<ge> 0\<close> unfolding \<phi>_def char_def interval_lebesgue_integral_def set_lebesgue_integral_def
 by (auto split: split_indicator intro!: Bochner_Integration.integral_cong)
 also have "\ = (CLBINT t. (CLINT x | M. ?f' (t, x)))"
 by (auto intro!: Bochner_Integration.integral_cong simp: field_simps exp_diff exp_minus split: split_indicator)
 also have "\ = (CLINT x | M. (CLBINT t. ?f' (t, x)))"
 proof (intro P.Fubini_integral [symmetric] integrableI_bounded_set [where B="b - a"])
 show "emeasure (lborel \\<^sub>M M) ({- T<.. space M) < \"
 using \<open>T \<ge> 0\<close>
 by (subst emeasure_pair_measure_Times)
 (auto simp: ennreal_mult_less_top not_less top_unique)
 show "AE x\{- T<.. space M in lborel \\<^sub>M M. cmod (case x of (t, x) \ ?f' (t, x)) \ b - a"
 using Levy_Inversion_aux2[of "x - b" "x - a" for x] \<open>a \<le> b\<close>
 by (intro AE_I [of _ _ "{0} \ UNIV"]) (force simp: emeasure_pair_measure_Times)+
 qed (auto split: split_indicator split_indicator_asm)
 also have "\ = (CLINT x | M. (complex_of_real (2 * (sgn (x - a) *
 Si (T * abs (x - a)) - sgn (x - b) * Si (T * abs (x - b))))))"
 using main_eq by (intro Bochner_Integration.integral_cong, auto)
 also have "\ = complex_of_real (LINT x | M. (2 * (sgn (x - a) *
 Si (T * abs (x - a)) - sgn (x - b) * Si (T * abs (x - b)))))"
 by (rule integral_complex_of_real)
 finally have "(CLBINT t=-T..T. ?F t * \ t) =
 complex_of_real (LINT x | M. (2 * (sgn (x - a) *
 Si (T * abs (x - a)) - sgn (x - b) * Si (T * abs (x - b)))))" .
 } note main_eq2 = this

 have "(\T :: nat. LINT x | M. (2 * (sgn (x - a) *
 Si (T * abs (x - a)) - sgn (x - b) * Si (T * abs (x - b))))) \<longlonglongrightarrow>
 (LINT x | M. 2 * pi * indicator {a<..b} x)"
 proof (rule integral_dominated_convergence [where w="\x. 4 * B"])
 show "integrable M (\x. 4 * B)"
 by (rule integrable_const_bound [of _ "4 * B"]) auto
 next
 let ?S = "\n::nat. \x. sgn (x - a) * Si (n * \x - a\) - sgn (x - b) * Si (n * \x - b\)"
 { fix n x
 have "norm (?S n x) \ norm (sgn (x - a) * Si (n * \x - a\)) + norm (sgn (x - b) * Si (n * \x - b\))"
 by (rule norm_triangle_ineq4)
 also have "\ \ B + B"
 using Bprop by (intro add_mono) (auto simp: abs_mult abs_sgn_eq)
 finally have "norm (2 * ?S n x) \ 4 * B"
 by simp }
 then show "\n. AE x in M. norm (2 * ?S n x) \ 4 * B"
 by auto
 have "AE x in M. x \ a" "AE x in M. x \ b"
 using prob_eq_0[of "{a}"] prob_eq_0[of "{b}"] \<open>\<mu> {a} = 0\<close> \<open>\<mu> {b} = 0\<close> by (auto simp: \<mu>_def)
 then show "AE x in M. (\n. 2 * ?S n x) \ 2 * pi * indicator {a<..b} x"
 proof eventually_elim
 fix x assume x: "x \ a" "x \ b"
 then have "(\n. 2 * (sgn (x - a) * Si (\x - a\ * n) - sgn (x - b) * Si (\x - b\ * n)))
 \<longlonglongrightarrow> 2 * (sgn (x - a) * (pi / 2) - sgn (x - b) * (pi / 2))"
 by (intro tendsto_intros filterlim_compose[OF Si_at_top]
 filterlim_tendsto_pos_mult_at_top[OF tendsto_const] filterlim_real_sequentially)
 auto
 also have "(\n. 2 * (sgn (x - a) * Si (\x - a\ * n) - sgn (x - b) * Si (\x - b\ * n))) = (\n. 2 * ?S n x)"
 by (auto simp: ac_simps)
 also have "2 * (sgn (x - a) * (pi / 2) - sgn (x - b) * (pi / 2)) = 2 * pi * indicator {a<..b} x"
 using x \<open>a \<le> b\<close> by (auto split: split_indicator)
 finally show "(\n. 2 * ?S n x) \ 2 * pi * indicator {a<..b} x" .
 qed
 qed simp_all
 also have "(LINT x | M. 2 * pi * indicator {a<..b} x) = 2 * pi * \ {a<..b}"
 by (simp add: \<mu>_def)
 finally have "(\T. LINT x | M. (2 * (sgn (x - a) *
 Si (T * abs (x - a)) - sgn (x - b) * Si (T * abs (x - b))))) \<longlonglongrightarrow>
 2 * pi * \<mu> {a<..b}" .
 with main_eq2 show ?thesis
 by (auto intro!: tendsto_eq_intros)
qed

theorem Levy_uniqueness:
 fixes M1 M2 :: "real measure"
 assumes "real_distribution M1" "real_distribution M2" and
 "char M1 = char M2"
 shows "M1 = M2"
proof -
 interpret M1: real_distribution M1 by (rule assms)
 interpret M2: real_distribution M2 by (rule assms)
 have "countable ({x. measure M1 {x} \ 0} \ {x. measure M2 {x} \ 0})"
 by (intro countable_Un M2.countable_support M1.countable_support)
 then have count: "countable {x. measure M1 {x} \ 0 \ measure M2 {x} \ 0}"
 by (simp add: Un_def)

 have "cdf M1 = cdf M2"
 proof (rule ext)
 fix x
 let ?D = "\x. \cdf M1 x - cdf M2 x\"

 { fix \<epsilon> :: real
 assume "\ > 0"
 have "(?D \ 0) at_bot"
 using M1.cdf_lim_at_bot M2.cdf_lim_at_bot by (intro tendsto_eq_intros) auto
 then have "eventually (\y. ?D y < \ / 2 \ y \ x) at_bot"
 using \<open>\<epsilon> > 0\<close> by (simp only: tendsto_iff dist_real_def diff_0_right eventually_conj eventually_le_at_bot abs_idempotent)
 then obtain M where "\y. y \ M \ ?D y < \ / 2" "M \ x"
 unfolding eventually_at_bot_linorder by auto
 with open_minus_countable[OF count, of "{..< M}"] obtain a where
 "measure M1 {a} = 0" "measure M2 {a} = 0" "a < M" "a \ x" and 1: "?D a < \ / 2"
 by auto

 have "(?D \ ?D x) (at_right x)"
 using M1.cdf_is_right_cont [of x] M2.cdf_is_right_cont [of x]
 by (intro tendsto_intros) (auto simp add: continuous_within)
 then have "eventually (\y. \?D y - ?D x\ < \ / 2) (at_right x)"
 using \<open>\<epsilon> > 0\<close> by (simp only: tendsto_iff dist_real_def eventually_conj eventually_at_right_less)
 then obtain N where "N > x" "\y. x < y \ y < N \ \?D y - ?D x\ < \ / 2"
 by (auto simp add: eventually_at_right[OF less_add_one])
 with open_minus_countable[OF count, of "{x <..< N}"] obtain b where "x < b" "b < N"
 "measure M1 {b} = 0" "measure M2 {b} = 0" and 2: "\?D b - ?D x\ < \ / 2"
 by (auto simp: abs_minus_commute)
 from \<open>a \<le> x\<close> \<open>x < b\<close> have "a < b" "a \<le> b" by auto

 from \<open>char M1 = char M2\<close>
 M1.Levy_Inversion [OF \<open>a \<le> b\<close> \<open>measure M1 {a} = 0\<close> \<open>measure M1 {b} = 0\<close>]
 M2.Levy_Inversion [OF \<open>a \<le> b\<close> \<open>measure M2 {a} = 0\<close> \<open>measure M2 {b} = 0\<close>]
 have "complex_of_real (measure M1 {a<..b}) = complex_of_real (measure M2 {a<..b})"
 by (intro LIMSEQ_unique) auto
 then have "?D a = ?D b"
 unfolding of_real_eq_iff M1.cdf_diff_eq [OF \<open>a < b\<close>, symmetric] M2.cdf_diff_eq [OF \<open>a < b\<close>, symmetric] by simp
 then have "?D x = \(?D b - ?D x) - ?D a\"
 by simp
 also have "\ \ \?D b - ?D x\ + \?D a\"
 by (rule abs_triangle_ineq4)
 also have "\ \ \ / 2 + \ / 2"
 using 1 2 by (intro add_mono) auto
 finally have "?D x \ \" by simp }
 then show "cdf M1 x = cdf M2 x"
 by (metis abs_le_zero_iff dense_ge eq_iff_diff_eq_0)
 qed
 thus ?thesis
 by (rule cdf_unique [OF \<open>real_distribution M1\<close> \<open>real_distribution M2\<close>])
qed

subsection \<open>The Levy continuity theorem\<close>

theorem levy_continuity1:
 fixes M :: "nat \ real measure" and M' :: "real measure"
 assumes "\n. real_distribution (M n)" "real_distribution M'" "weak_conv_m M M'"
 shows "(\n. char (M n) t) \ char M' t"
 unfolding char_def using assms by (rule weak_conv_imp_integral_bdd_continuous_conv) auto

theorem levy_continuity:
 fixes M :: "nat \ real measure" and M' :: "real measure"
 assumes real_distr_M : "\n. real_distribution (M n)"
 and real_distr_M': "real_distribution M'"
 and char_conv: "\t. (\n. char (M n) t) \ char M' t"
 shows "weak_conv_m M M'"
proof -
 interpret Mn: real_distribution "M n" for n by fact
 interpret M': real_distribution M' by fact

 have *: "\u x. u > 0 \ x \ 0 \ (CLBINT t:{-u..u}. 1 - iexp (t * x)) =
 2 * (u - sin (u * x) / x)"
 proof -
 fix u :: real and x :: real
 assume "u > 0" and "x \ 0"
 hence "(CLBINT t:{-u..u}. 1 - iexp (t * x)) = (CLBINT t=-u..u. 1 - iexp (t * x))"
 by (subst interval_integral_Icc, auto)
 also have "\ = (CLBINT t=-u..0. 1 - iexp (t * x)) + (CLBINT t=0..u. 1 - iexp (t * x))"
 using \<open>u > 0\<close>
 apply (subst interval_integral_sum)
 apply (simp add: min_absorb1 min_absorb2 max_absorb1 max_absorb2)
 apply (rule interval_integrable_isCont)
 apply auto
 done
 also have "\ = (CLBINT t=ereal 0..u. 1 - iexp (t * -x)) + (CLBINT t=ereal 0..u. 1 - iexp (t * x))"
 apply (subgoal_tac "0 = ereal 0", erule ssubst)
 by (subst interval_integral_reflect, auto)
 also have "\ = (LBINT t=ereal 0..u. 2 - 2 * cos (t * x))"
 apply (subst interval_lebesgue_integral_add (2) [symmetric])
 apply ((rule interval_integrable_isCont, auto)+) [2]
 unfolding exp_Euler cos_of_real
 apply (simp add: of_real_mult interval_lebesgue_integral_of_real[symmetric])
 done
 also have "\ = 2 * u - 2 * sin (u * x) / x"
 by (subst interval_lebesgue_integral_diff)
 (auto intro!: interval_integrable_isCont
 simp: interval_lebesgue_integral_of_real integral_cos [OF \<open>x \<noteq> 0\<close>] mult.commute[of _ x])
 finally show "(CLBINT t:{-u..u}. 1 - iexp (t * x)) = 2 * (u - sin (u * x) / x)"
 by (simp add: field_simps)
 qed
 have main_bound: "\u n. u > 0 \ Re (CLBINT t:{-u..u}. 1 - char (M n) t) \
 u * measure (M n) {x. abs x \<ge> 2 / u}"
 proof -
 fix u :: real and n
 assume "u > 0"
 interpret P: pair_sigma_finite "M n" lborel ..
 (* TODO: put this in the real_distribution locale as a simp rule? *)
 have Mn1 [simp]: "measure (M n) UNIV = 1" by (metis Mn.prob_space Mn.space_eq_univ)
 (* TODO: make this automatic somehow? *)
 have Mn2 [simp]: "\x. complex_integrable (M n) (\t. exp (\ * complex_of_real (x * t)))"
 by (rule Mn.integrable_const_bound [where B = 1], auto)
 have Mn3: "set_integrable (M n \\<^sub>M lborel) (UNIV \ {- u..u}) (\a. 1 - exp (\ * complex_of_real (snd a * fst a)))"
 using \<open>0 < u\<close>
 unfolding set_integrable_def
 by (intro integrableI_bounded_set_indicator [where B="2"])
 (auto simp: lborel.emeasure_pair_measure_Times ennreal_mult_less_top not_less top_unique
 split: split_indicator
 intro!: order_trans [OF norm_triangle_ineq4])
 have "(CLBINT t:{-u..u}. 1 - char (M n) t) =
 (CLBINT t:{-u..u}. (CLINT x | M n. 1 - iexp (t * x)))"
 unfolding char_def by (rule set_lebesgue_integral_cong, auto simp del: of_real_mult)
 also have "\ = (CLBINT t. (CLINT x | M n. indicator {-u..u} t *\<^sub>R (1 - iexp (t * x))))"
 unfolding set_lebesgue_integral_def
 by (rule Bochner_Integration.integral_cong) (auto split: split_indicator)
 also have "\ = (CLINT x | M n. (CLBINT t:{-u..u}. 1 - iexp (t * x)))"
 using Mn3 by (subst P.Fubini_integral) (auto simp: indicator_times split_beta' set_integrable_def set_lebesgue_integral_def)
 also have "\ = (CLINT x | M n. (if x = 0 then 0 else 2 * (u - sin (u * x) / x)))"
 using \<open>u > 0\<close> by (intro Bochner_Integration.integral_cong, auto simp add: * simp del: of_real_mult)
 also have "\ = (LINT x | M n. (if x = 0 then 0 else 2 * (u - sin (u * x) / x)))"
 by (rule integral_complex_of_real)
 finally have "Re (CLBINT t:{-u..u}. 1 - char (M n) t) =
 (LINT x | M n. (if x = 0 then 0 else 2 * (u - sin (u * x) / x)))" by simp
 also have "\ \ (LINT x : {x. abs x \ 2 / u} | M n. u)"
 proof -
 have "complex_integrable (M n) (\x. CLBINT t:{-u..u}. 1 - iexp (snd (x, t) * fst (x, t)))"
 using Mn3 unfolding set_integrable_def set_lebesgue_integral_def
 by (intro P.integrable_fst) (simp add: indicator_times split_beta')
 hence "complex_integrable (M n) (\x. if x = 0 then 0 else 2 * (u - sin (u * x) / x))"
 using \<open>u > 0\<close>
 unfolding set_integrable_def
 by (subst integrable_cong) (auto simp add: * simp del: of_real_mult)
 hence **: "integrable (M n) (\x. if x = 0 then 0 else 2 * (u - sin (u * x) / x))"
 unfolding complex_of_real_integrable_eq .
 have "2 * sin x \ x" if "2 \ x" for x :: real
 by (rule order_trans[OF _ \<open>2 \<le> x\<close>]) auto
 moreover have "x \ 2 * sin x" if "x \ - 2" for x :: real
 by (rule order_trans[OF \<open>x \<le> - 2\<close>]) auto
 moreover have "x < 0 \ x \ sin x" for x :: real
 using sin_x_le_x[of "-x"] by simp
 ultimately show ?thesis
 using \<open>u > 0\<close> unfolding set_lebesgue_integral_def
 by (intro integral_mono [OF _ **])
 (auto simp: divide_simps sin_x_le_x mult.commute[of u] mult_neg_pos top_unique less_top[symmetric]
 split: split_indicator)
 qed
 also (xtrans) have "(LINT x : {x. abs x \ 2 / u} | M n. u) = u * measure (M n) {x. abs x \ 2 / u}"
 unfolding set_lebesgue_integral_def
 by (simp add: Mn.emeasure_eq_measure)
 finally show "Re (CLBINT t:{-u..u}. 1 - char (M n) t) \ u * measure (M n) {x. abs x \ 2 / u}" .
 qed

 have tight_aux: "\\. \ > 0 \ \a b. a :: real
 assume "\ > 0"
 note M'.isCont_char [of 0]
 hence "\d>0. \t. abs t < d \ cmod (char M' t - 1) < \ / 4"
 apply (subst (asm) continuous_at_eps_delta)
 apply (drule_tac x = "\ / 4" in spec)
 using \<open>\<epsilon> > 0\<close> by (auto simp add: dist_real_def dist_complex_def M'.char_zero)
 then obtain d where "d > 0 \ (\t. (abs t < d \ cmod (char M' t - 1) < \ / 4))" ..
 hence d0: "d > 0" and d1: "\t. abs t < d \ cmod (char M' t - 1) < \ / 4" by auto
 have 1: "\x. cmod (1 - char M' x) \ 2"
 by (rule order_trans [OF norm_triangle_ineq4], auto simp add: M'.cmod_char_le_1)
 then have 2: "\u v. complex_set_integrable lborel {u..v} (\x. 1 - char M' x)"
 unfolding set_integrable_def
 by (intro integrableI_bounded_set_indicator[where B=2]) (auto simp: emeasure_lborel_Icc_eq)
 have 3: "\u v. integrable lborel (\x. indicat_real {u..v} x *\<^sub>R cmod (1 - char M' x))"
 by (intro borel_integrable_compact[OF compact_Icc] continuous_at_imp_continuous_on
 continuous_intros ballI M'.isCont_char continuous_intros)
 have "cmod (CLBINT t:{-d/2..d/2}. 1 - char M' t) \ LBINT t:{-d/2..d/2}. cmod (1 - char M' t)"
 unfolding set_lebesgue_integral_def
 using integral_norm_bound[of _ "\x. indicator {u..v} x *\<^sub>R (1 - char M' x)" for u v] by simp
 also have 4: "\ \ LBINT t:{-d/2..d/2}. \ / 4"
 unfolding set_lebesgue_integral_def
 apply (rule integral_mono [OF 3])
 apply (simp add: emeasure_lborel_Icc_eq)
 apply (case_tac "x \ {-d/2..d/2}")
 apply auto
 apply (subst norm_minus_commute)
 apply (rule less_imp_le)
 apply (rule d1 [simplified])
 using d0 apply auto
 done
 also from d0 4 have "\ = d * \ / 4"
 unfolding set_lebesgue_integral_def by simp
 finally have bound: "cmod (CLBINT t:{-d/2..d/2}. 1 - char M' t) \ d * \ / 4" .
 have "cmod (1 - char (M n) x) \ 2" for n x
 by (rule order_trans [OF norm_triangle_ineq4], auto simp add: Mn.cmod_char_le_1)
 then have "(\n. CLBINT t:{-d/2..d/2}. 1 - char (M n) t) \ (CLBINT t:{-d/2..d/2}. 1 - char M' t)"
 unfolding set_lebesgue_integral_def
 apply (intro integral_dominated_convergence[where w="\x. indicator {-d/2..d/2} x *\<^sub>R 2"])
 apply (auto intro!: char_conv tendsto_intros
 simp: emeasure_lborel_Icc_eq
 split: split_indicator)
 done
 hence "eventually (\n. cmod ((CLBINT t:{-d/2..d/2}. 1 - char (M n) t) -
 (CLBINT t:{-d/2..d/2}. 1 - char M' t)) < d * \ / 4) sequentially"
 using d0 \<open>\<epsilon> > 0\<close> apply (subst (asm) tendsto_iff)
 by (subst (asm) dist_complex_def, drule spec, erule mp, auto)
 hence "\N. \n \ N. cmod ((CLBINT t:{-d/2..d/2}. 1 - char (M n) t) -
 (CLBINT t:{-d/2..d/2}. 1 - char M' t)) < d * \ / 4" by (simp add: eventually_sequentially)
 then guess N ..
 hence N: "\n. n \ N \ cmod ((CLBINT t:{-d/2..d/2}. 1 - char (M n) t) -
 (CLBINT t:{-d/2..d/2}. 1 - char M' t)) < d * \ / 4" by auto
 { fix n
 assume "n \ N"
 have "cmod (CLBINT t:{-d/2..d/2}. 1 - char (M n) t) =
 cmod ((CLBINT t:{-d/2..d/2}. 1 - char (M n) t) - (CLBINT t:{-d/2..d/2}. 1 - char M' t)
 + (CLBINT t:{-d/2..d/2}. 1 - char M' t))" by simp
 also have "\ \ cmod ((CLBINT t:{-d/2..d/2}. 1 - char (M n) t) -
 (CLBINT t:{-d/2..d/2}. 1 - char M' t)) + cmod(CLBINT t:{-d/2..d/2}. 1 - char M' t)"
 by (rule norm_triangle_ineq)
 also have "\ < d * \ / 4 + d * \ / 4"
 by (rule add_less_le_mono [OF N [OF \<open>n \<ge> N\<close>] bound])
 also have "\ = d * \ / 2" by auto
 finally have "cmod (CLBINT t:{-d/2..d/2}. 1 - char (M n) t) < d * \ / 2" .
 hence "d * \ / 2 > Re (CLBINT t:{-d/2..d/2}. 1 - char (M n) t)"
 by (rule order_le_less_trans [OF complex_Re_le_cmod])
 hence "d * \ / 2 > Re (CLBINT t:{-(d/2)..d/2}. 1 - char (M n) t)" (is "_ > ?lhs") by simp
 also have "?lhs \ (d / 2) * measure (M n) {x. abs x \ 2 / (d / 2)}"
 using d0 by (intro main_bound, simp)
 finally (xtrans) have "d * \ / 2 > (d / 2) * measure (M n) {x. abs x \ 2 / (d / 2)}" .
 with d0 \<open>\<epsilon> > 0\<close> have "\<epsilon> > measure (M n) {x. abs x \<ge> 2 / (d / 2)}" by (simp add: field_simps)
 hence "\ > 1 - measure (M n) (UNIV - {x. abs x \ 2 / (d / 2)})"
 apply (subst Mn.borel_UNIV [symmetric])
 by (subst Mn.prob_compl, auto)
 also have "UNIV - {x. abs x \ 2 / (d / 2)} = {x. -(4 / d) < x \ x < (4 / d)}"
 using d0 apply (auto simp add: field_simps)
 (* very annoying -- this should be automatic *)
 apply (case_tac "x \ 0", auto simp add: field_simps)
 apply (subgoal_tac "0 \ x * d", arith, rule mult_nonneg_nonneg, auto)
 apply (case_tac "x \ 0", auto simp add: field_simps)
 apply (subgoal_tac "x * d \ 0", arith)
 apply (rule mult_nonpos_nonneg, auto)
 by (case_tac "x \ 0", auto simp add: field_simps)
 finally have "measure (M n) {x. -(4 / d) < x \ x < (4 / d)} > 1 - \"
 by auto
 } note 6 = this
 { fix n :: nat
 have *: "(UN (k :: nat). {- real k<..real k}) = UNIV"
 by (auto, metis leI le_less_trans less_imp_le minus_less_iff reals_Archimedean2)
 have "(\k. measure (M n) {- real k<..real k}) \
 measure (M n) (UN (k :: nat). {- real k<..real k})"
 by (rule Mn.finite_Lim_measure_incseq, auto simp add: incseq_def)
 hence "(\k. measure (M n) {- real k<..real k}) \ 1"
 using Mn.prob_space unfolding * Mn.borel_UNIV by simp
 hence "eventually (\k. measure (M n) {- real k<..real k} > 1 - \) sequentially"
 apply (elim order_tendstoD (1))
 using \<open>\<epsilon> > 0\<close> by auto
 } note 7 = this
 { fix n :: nat
 have "eventually (\k. \m < n. measure (M m) {- real k<..real k} > 1 - \) sequentially"
 (is "?P n")
 proof (induct n)
 case (Suc n) with 7[of n] show ?case
 by eventually_elim (auto simp add: less_Suc_eq)
 qed simp
 } note 8 = this
 from 8 [of N] have "\K :: nat. \k \ K. \m <
 Sigma_Algebra.measure (M m) {- real k<..real k}"
 by (auto simp add: eventually_sequentially)
 hence "\K :: nat. \m < Sigma_Algebra.measure (M m) {- real K<..real K}" by auto
 then obtain K :: nat where
 "\m < Sigma_Algebra.measure (M m) {- real K<..real K}" ..
 hence K: "\m. m < N \ 1 - \ < Sigma_Algebra.measure (M m) {- real K<..real K}"
 by auto
 let ?K' = "max K (4 / d)"
 have "-?K' < ?K' \ (\n. 1 - \ < measure (M n) {-?K'<..?K'})"
 using d0 apply auto
 apply (rule max.strict_coboundedI2, auto)
 proof -
 fix n
 show " 1 - \ < measure (M n) {- max (real K) (4 / d)<..max (real K) (4 / d)}"
 apply (case_tac "n < N")
 apply (rule order_less_le_trans)
 apply (erule K)
 apply (rule Mn.finite_measure_mono, auto)
 apply (rule order_less_le_trans)
 apply (rule 6, erule leI)
 by (rule Mn.finite_measure_mono, auto)
 qed
 thus "\a b. a < b \ (\n. 1 - \ < measure (M n) {a<..b})" by (intro exI)
 qed
 have tight: "tight M"
 by (auto simp: tight_def intro: assms tight_aux)
 show ?thesis
 proof (rule tight_subseq_weak_converge [OF real_distr_M real_distr_M' tight])
 fix s \<nu>
 assume s: "strict_mono (s :: nat \ nat)"
 assume nu: "weak_conv_m (M \ s) \"
 assume *: "real_distribution \"
 have 2: "\n. real_distribution ((M \ s) n)" unfolding comp_def by (rule assms)
 have 3: "\t. (\n. char ((M \ s) n) t) \ char \ t" by (intro levy_continuity1 [OF 2 * nu])
 have 4: "\t. (\n. char ((M \ s) n) t) = ((\n. char (M n) t) \ s)" by (rule ext, simp)
 have 5: "\t. (\n. char ((M \ s) n) t) \ char M' t"
 by (subst 4, rule LIMSEQ_subseq_LIMSEQ [OF _ s], rule assms)
 hence "char \ = char M'" by (intro ext, intro LIMSEQ_unique [OF 3 5])
 hence "\ = M'" by (rule Levy_uniqueness [OF * \real_distribution M'\])
 thus "weak_conv_m (M \ s) M'"
 by (elim subst) (rule nu)
 qed
qed

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