joint cumulative distribution function proof












0












$begingroup$


Let $X=(X_1,..,X_n)$ be a density random vector.



Then for all $1 le k le n$: $$f_{X_k}(x_k)=int_{-infty}^{infty}dx_1···int_{-infty}^{infty}dx_{k-1}int_{-infty}^{infty}dx_{k+1}···int_{-infty}^{infty}dx_n f_X(x_1,..,x_n)$$



Proof:



$$P(X_kin A)=P(Xinmathbb{R}^{k-1}times A times mathbb{R}^{n-k})=$$$$int_{mathbb{R}}dx_1···int_{mathbb{R}}dx_{k-1}int_{A}dx_kint_{mathbb{R}}dx_{k+1}int_{mathbb{R}}dx_{n}f_X(x_1,..,x_n)=$$$$int_{A}dx_kf_{X_k}(x_k)$$



I don't understand the last two equalities, is it by definition that $P(X_1le x_1, ...,X_n le x_n)=int_{-infty}^{x_1}ds_1···int_{-infty}^{x_n}ds_nf_X(s_1,..,s_n)$ ?



And how to explain the last equality ?










share|cite|improve this question











$endgroup$

















    0












    $begingroup$


    Let $X=(X_1,..,X_n)$ be a density random vector.



    Then for all $1 le k le n$: $$f_{X_k}(x_k)=int_{-infty}^{infty}dx_1···int_{-infty}^{infty}dx_{k-1}int_{-infty}^{infty}dx_{k+1}···int_{-infty}^{infty}dx_n f_X(x_1,..,x_n)$$



    Proof:



    $$P(X_kin A)=P(Xinmathbb{R}^{k-1}times A times mathbb{R}^{n-k})=$$$$int_{mathbb{R}}dx_1···int_{mathbb{R}}dx_{k-1}int_{A}dx_kint_{mathbb{R}}dx_{k+1}int_{mathbb{R}}dx_{n}f_X(x_1,..,x_n)=$$$$int_{A}dx_kf_{X_k}(x_k)$$



    I don't understand the last two equalities, is it by definition that $P(X_1le x_1, ...,X_n le x_n)=int_{-infty}^{x_1}ds_1···int_{-infty}^{x_n}ds_nf_X(s_1,..,s_n)$ ?



    And how to explain the last equality ?










    share|cite|improve this question











    $endgroup$















      0












      0








      0





      $begingroup$


      Let $X=(X_1,..,X_n)$ be a density random vector.



      Then for all $1 le k le n$: $$f_{X_k}(x_k)=int_{-infty}^{infty}dx_1···int_{-infty}^{infty}dx_{k-1}int_{-infty}^{infty}dx_{k+1}···int_{-infty}^{infty}dx_n f_X(x_1,..,x_n)$$



      Proof:



      $$P(X_kin A)=P(Xinmathbb{R}^{k-1}times A times mathbb{R}^{n-k})=$$$$int_{mathbb{R}}dx_1···int_{mathbb{R}}dx_{k-1}int_{A}dx_kint_{mathbb{R}}dx_{k+1}int_{mathbb{R}}dx_{n}f_X(x_1,..,x_n)=$$$$int_{A}dx_kf_{X_k}(x_k)$$



      I don't understand the last two equalities, is it by definition that $P(X_1le x_1, ...,X_n le x_n)=int_{-infty}^{x_1}ds_1···int_{-infty}^{x_n}ds_nf_X(s_1,..,s_n)$ ?



      And how to explain the last equality ?










      share|cite|improve this question











      $endgroup$




      Let $X=(X_1,..,X_n)$ be a density random vector.



      Then for all $1 le k le n$: $$f_{X_k}(x_k)=int_{-infty}^{infty}dx_1···int_{-infty}^{infty}dx_{k-1}int_{-infty}^{infty}dx_{k+1}···int_{-infty}^{infty}dx_n f_X(x_1,..,x_n)$$



      Proof:



      $$P(X_kin A)=P(Xinmathbb{R}^{k-1}times A times mathbb{R}^{n-k})=$$$$int_{mathbb{R}}dx_1···int_{mathbb{R}}dx_{k-1}int_{A}dx_kint_{mathbb{R}}dx_{k+1}int_{mathbb{R}}dx_{n}f_X(x_1,..,x_n)=$$$$int_{A}dx_kf_{X_k}(x_k)$$



      I don't understand the last two equalities, is it by definition that $P(X_1le x_1, ...,X_n le x_n)=int_{-infty}^{x_1}ds_1···int_{-infty}^{x_n}ds_nf_X(s_1,..,s_n)$ ?



      And how to explain the last equality ?







      probability-theory density-function






      share|cite|improve this question















      share|cite|improve this question













      share|cite|improve this question




      share|cite|improve this question








      edited Dec 19 '18 at 10:14









      drhab

      102k545136




      102k545136










      asked Dec 19 '18 at 9:02









      WaspWasp

      112




      112






















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          $begingroup$

          It is by definition that $$P((X_1,dots,X_n)in B)=int;d(x_1,dots,x_n)mathbf1_B(x_1,dots,x_n)f_X(x_1,dots,x_n)$$
          or in slightly different notation:$$P((X_1,dots,X_n)in B)=int_B;d(x_1,dots,x_n)f_X(x_1,dots,x_n)$$





          As a sidenote: personally I dislike this notation and would rather go for $$P((X_1,dots,X_n)in B)=intdotsintmathbf1_B(x_1,dots,x_n)f_X(x_1,dots,x_n);dx_1dots dx_n$$





          In special case $B=A_1timescdotscdotstimes A_n$ this takes the form:$$P(X_1in A_1,dots,X_nin A_n)=int_{A_1};dx_1cdotsint_{A_n};dx_nf_X(x_1,dots,x_n)$$



          Now see what happens if $A_i=(-infty,x_i]$.



          Concerning the second equality note that it is allowed here to change the order of integration.



          So: $$int_{mathbb R}dx_1cdotsint_Adx_kcdotsint_{mathbb R}dx_nf_X(x_1,dots,x_n)=int_{A}dx_kint_{mathbb R}dx_1cdotsint_{mathbb R}dx_nf_X(x_1,dots,x_n)=int_Adx_kf_{X_k}(x_k)$$






          share|cite|improve this answer











          $endgroup$













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            0












            $begingroup$

            It is by definition that $$P((X_1,dots,X_n)in B)=int;d(x_1,dots,x_n)mathbf1_B(x_1,dots,x_n)f_X(x_1,dots,x_n)$$
            or in slightly different notation:$$P((X_1,dots,X_n)in B)=int_B;d(x_1,dots,x_n)f_X(x_1,dots,x_n)$$





            As a sidenote: personally I dislike this notation and would rather go for $$P((X_1,dots,X_n)in B)=intdotsintmathbf1_B(x_1,dots,x_n)f_X(x_1,dots,x_n);dx_1dots dx_n$$





            In special case $B=A_1timescdotscdotstimes A_n$ this takes the form:$$P(X_1in A_1,dots,X_nin A_n)=int_{A_1};dx_1cdotsint_{A_n};dx_nf_X(x_1,dots,x_n)$$



            Now see what happens if $A_i=(-infty,x_i]$.



            Concerning the second equality note that it is allowed here to change the order of integration.



            So: $$int_{mathbb R}dx_1cdotsint_Adx_kcdotsint_{mathbb R}dx_nf_X(x_1,dots,x_n)=int_{A}dx_kint_{mathbb R}dx_1cdotsint_{mathbb R}dx_nf_X(x_1,dots,x_n)=int_Adx_kf_{X_k}(x_k)$$






            share|cite|improve this answer











            $endgroup$


















              0












              $begingroup$

              It is by definition that $$P((X_1,dots,X_n)in B)=int;d(x_1,dots,x_n)mathbf1_B(x_1,dots,x_n)f_X(x_1,dots,x_n)$$
              or in slightly different notation:$$P((X_1,dots,X_n)in B)=int_B;d(x_1,dots,x_n)f_X(x_1,dots,x_n)$$





              As a sidenote: personally I dislike this notation and would rather go for $$P((X_1,dots,X_n)in B)=intdotsintmathbf1_B(x_1,dots,x_n)f_X(x_1,dots,x_n);dx_1dots dx_n$$





              In special case $B=A_1timescdotscdotstimes A_n$ this takes the form:$$P(X_1in A_1,dots,X_nin A_n)=int_{A_1};dx_1cdotsint_{A_n};dx_nf_X(x_1,dots,x_n)$$



              Now see what happens if $A_i=(-infty,x_i]$.



              Concerning the second equality note that it is allowed here to change the order of integration.



              So: $$int_{mathbb R}dx_1cdotsint_Adx_kcdotsint_{mathbb R}dx_nf_X(x_1,dots,x_n)=int_{A}dx_kint_{mathbb R}dx_1cdotsint_{mathbb R}dx_nf_X(x_1,dots,x_n)=int_Adx_kf_{X_k}(x_k)$$






              share|cite|improve this answer











              $endgroup$
















                0












                0








                0





                $begingroup$

                It is by definition that $$P((X_1,dots,X_n)in B)=int;d(x_1,dots,x_n)mathbf1_B(x_1,dots,x_n)f_X(x_1,dots,x_n)$$
                or in slightly different notation:$$P((X_1,dots,X_n)in B)=int_B;d(x_1,dots,x_n)f_X(x_1,dots,x_n)$$





                As a sidenote: personally I dislike this notation and would rather go for $$P((X_1,dots,X_n)in B)=intdotsintmathbf1_B(x_1,dots,x_n)f_X(x_1,dots,x_n);dx_1dots dx_n$$





                In special case $B=A_1timescdotscdotstimes A_n$ this takes the form:$$P(X_1in A_1,dots,X_nin A_n)=int_{A_1};dx_1cdotsint_{A_n};dx_nf_X(x_1,dots,x_n)$$



                Now see what happens if $A_i=(-infty,x_i]$.



                Concerning the second equality note that it is allowed here to change the order of integration.



                So: $$int_{mathbb R}dx_1cdotsint_Adx_kcdotsint_{mathbb R}dx_nf_X(x_1,dots,x_n)=int_{A}dx_kint_{mathbb R}dx_1cdotsint_{mathbb R}dx_nf_X(x_1,dots,x_n)=int_Adx_kf_{X_k}(x_k)$$






                share|cite|improve this answer











                $endgroup$



                It is by definition that $$P((X_1,dots,X_n)in B)=int;d(x_1,dots,x_n)mathbf1_B(x_1,dots,x_n)f_X(x_1,dots,x_n)$$
                or in slightly different notation:$$P((X_1,dots,X_n)in B)=int_B;d(x_1,dots,x_n)f_X(x_1,dots,x_n)$$





                As a sidenote: personally I dislike this notation and would rather go for $$P((X_1,dots,X_n)in B)=intdotsintmathbf1_B(x_1,dots,x_n)f_X(x_1,dots,x_n);dx_1dots dx_n$$





                In special case $B=A_1timescdotscdotstimes A_n$ this takes the form:$$P(X_1in A_1,dots,X_nin A_n)=int_{A_1};dx_1cdotsint_{A_n};dx_nf_X(x_1,dots,x_n)$$



                Now see what happens if $A_i=(-infty,x_i]$.



                Concerning the second equality note that it is allowed here to change the order of integration.



                So: $$int_{mathbb R}dx_1cdotsint_Adx_kcdotsint_{mathbb R}dx_nf_X(x_1,dots,x_n)=int_{A}dx_kint_{mathbb R}dx_1cdotsint_{mathbb R}dx_nf_X(x_1,dots,x_n)=int_Adx_kf_{X_k}(x_k)$$







                share|cite|improve this answer














                share|cite|improve this answer



                share|cite|improve this answer








                edited Dec 19 '18 at 17:32

























                answered Dec 19 '18 at 10:43









                drhabdrhab

                102k545136




                102k545136






























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