Concentration inequality applied for robust estimation of the mean












2














Problem: (Page 19 in "Vershynin, Roman (2018). High-Dimensional Probability. Cambridge University Press. ISBN 9781108415194.")




Suppose we want to estimate the mean µ of a random variable $X$ from a
sample $X_1 , dots , X_N$ drawn independently from the distribution
of $X$. We want an $varepsilon$-accurate estimate, i.e. one that
falls in the interval $(mu − varepsilon, mu + varepsilon)$.



Show that a sample of size $N = O( log (delta^{−1} ), sigma^2 / varepsilon^2 )$ is sufficient to compute an $varepsilon$-accurate
estimate with probability at least $1 −delta$.



Hint: Use the median of $O(log(delta^{−1}))$ weak estimates.




It is easy to use Chebyshev's inequality to find a weak estimate of $N = O( sigma^2 / (delta varepsilon^2) )$.



However, I do not how to find inequality about their median. The wikipedia of median (https://en.wikipedia.org/wiki/Median#The_sample_median) says sample median asymptotically normal but this does not give a bound for specific $N$. Any suggestion is welcome.










share|cite|improve this question





























    2














    Problem: (Page 19 in "Vershynin, Roman (2018). High-Dimensional Probability. Cambridge University Press. ISBN 9781108415194.")




    Suppose we want to estimate the mean µ of a random variable $X$ from a
    sample $X_1 , dots , X_N$ drawn independently from the distribution
    of $X$. We want an $varepsilon$-accurate estimate, i.e. one that
    falls in the interval $(mu − varepsilon, mu + varepsilon)$.



    Show that a sample of size $N = O( log (delta^{−1} ), sigma^2 / varepsilon^2 )$ is sufficient to compute an $varepsilon$-accurate
    estimate with probability at least $1 −delta$.



    Hint: Use the median of $O(log(delta^{−1}))$ weak estimates.




    It is easy to use Chebyshev's inequality to find a weak estimate of $N = O( sigma^2 / (delta varepsilon^2) )$.



    However, I do not how to find inequality about their median. The wikipedia of median (https://en.wikipedia.org/wiki/Median#The_sample_median) says sample median asymptotically normal but this does not give a bound for specific $N$. Any suggestion is welcome.










    share|cite|improve this question



























      2












      2








      2


      1





      Problem: (Page 19 in "Vershynin, Roman (2018). High-Dimensional Probability. Cambridge University Press. ISBN 9781108415194.")




      Suppose we want to estimate the mean µ of a random variable $X$ from a
      sample $X_1 , dots , X_N$ drawn independently from the distribution
      of $X$. We want an $varepsilon$-accurate estimate, i.e. one that
      falls in the interval $(mu − varepsilon, mu + varepsilon)$.



      Show that a sample of size $N = O( log (delta^{−1} ), sigma^2 / varepsilon^2 )$ is sufficient to compute an $varepsilon$-accurate
      estimate with probability at least $1 −delta$.



      Hint: Use the median of $O(log(delta^{−1}))$ weak estimates.




      It is easy to use Chebyshev's inequality to find a weak estimate of $N = O( sigma^2 / (delta varepsilon^2) )$.



      However, I do not how to find inequality about their median. The wikipedia of median (https://en.wikipedia.org/wiki/Median#The_sample_median) says sample median asymptotically normal but this does not give a bound for specific $N$. Any suggestion is welcome.










      share|cite|improve this question















      Problem: (Page 19 in "Vershynin, Roman (2018). High-Dimensional Probability. Cambridge University Press. ISBN 9781108415194.")




      Suppose we want to estimate the mean µ of a random variable $X$ from a
      sample $X_1 , dots , X_N$ drawn independently from the distribution
      of $X$. We want an $varepsilon$-accurate estimate, i.e. one that
      falls in the interval $(mu − varepsilon, mu + varepsilon)$.



      Show that a sample of size $N = O( log (delta^{−1} ), sigma^2 / varepsilon^2 )$ is sufficient to compute an $varepsilon$-accurate
      estimate with probability at least $1 −delta$.



      Hint: Use the median of $O(log(delta^{−1}))$ weak estimates.




      It is easy to use Chebyshev's inequality to find a weak estimate of $N = O( sigma^2 / (delta varepsilon^2) )$.



      However, I do not how to find inequality about their median. The wikipedia of median (https://en.wikipedia.org/wiki/Median#The_sample_median) says sample median asymptotically normal but this does not give a bound for specific $N$. Any suggestion is welcome.







      probability statistics median






      share|cite|improve this question















      share|cite|improve this question













      share|cite|improve this question




      share|cite|improve this question








      edited 2 days ago

























      asked Nov 15 '18 at 17:02









      Rikeijin

      949




      949






















          0






          active

          oldest

          votes











          Your Answer





          StackExchange.ifUsing("editor", function () {
          return StackExchange.using("mathjaxEditing", function () {
          StackExchange.MarkdownEditor.creationCallbacks.add(function (editor, postfix) {
          StackExchange.mathjaxEditing.prepareWmdForMathJax(editor, postfix, [["$", "$"], ["\\(","\\)"]]);
          });
          });
          }, "mathjax-editing");

          StackExchange.ready(function() {
          var channelOptions = {
          tags: "".split(" "),
          id: "69"
          };
          initTagRenderer("".split(" "), "".split(" "), channelOptions);

          StackExchange.using("externalEditor", function() {
          // Have to fire editor after snippets, if snippets enabled
          if (StackExchange.settings.snippets.snippetsEnabled) {
          StackExchange.using("snippets", function() {
          createEditor();
          });
          }
          else {
          createEditor();
          }
          });

          function createEditor() {
          StackExchange.prepareEditor({
          heartbeatType: 'answer',
          autoActivateHeartbeat: false,
          convertImagesToLinks: true,
          noModals: true,
          showLowRepImageUploadWarning: true,
          reputationToPostImages: 10,
          bindNavPrevention: true,
          postfix: "",
          imageUploader: {
          brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
          contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
          allowUrls: true
          },
          noCode: true, onDemand: true,
          discardSelector: ".discard-answer"
          ,immediatelyShowMarkdownHelp:true
          });


          }
          });














          draft saved

          draft discarded


















          StackExchange.ready(
          function () {
          StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f2999970%2fconcentration-inequality-applied-for-robust-estimation-of-the-mean%23new-answer', 'question_page');
          }
          );

          Post as a guest















          Required, but never shown

























          0






          active

          oldest

          votes








          0






          active

          oldest

          votes









          active

          oldest

          votes






          active

          oldest

          votes
















          draft saved

          draft discarded




















































          Thanks for contributing an answer to Mathematics Stack Exchange!


          • Please be sure to answer the question. Provide details and share your research!

          But avoid



          • Asking for help, clarification, or responding to other answers.

          • Making statements based on opinion; back them up with references or personal experience.


          Use MathJax to format equations. MathJax reference.


          To learn more, see our tips on writing great answers.





          Some of your past answers have not been well-received, and you're in danger of being blocked from answering.


          Please pay close attention to the following guidance:


          • Please be sure to answer the question. Provide details and share your research!

          But avoid



          • Asking for help, clarification, or responding to other answers.

          • Making statements based on opinion; back them up with references or personal experience.


          To learn more, see our tips on writing great answers.




          draft saved


          draft discarded














          StackExchange.ready(
          function () {
          StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f2999970%2fconcentration-inequality-applied-for-robust-estimation-of-the-mean%23new-answer', 'question_page');
          }
          );

          Post as a guest















          Required, but never shown





















































          Required, but never shown














          Required, but never shown












          Required, but never shown







          Required, but never shown

































          Required, but never shown














          Required, but never shown












          Required, but never shown







          Required, but never shown







          Popular posts from this blog

          1300-talet

          1300-talet

          Has there ever been an instance of an active nuclear power plant within or near a war zone?