/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Q 11E The definition of the conditiona... [FREE SOLUTION] | 91影视

91影视

The definition of the conditional p.d.f. of X given\({\bf{Y = y}}\)is arbitrary if\({{\bf{f}}_{\bf{2}}}\left( {\bf{y}} \right){\bf{ = 0}}\). The reason that this causes no serious problem is that it is highly unlikely that we will observe Y close to a value\({{\bf{y}}_{\bf{0}}}\)such that\({{\bf{f}}_{\bf{2}}}\left( {{{\bf{y}}_{\bf{0}}}} \right){\bf{ = 0}}\). To be more precise, let\({{\bf{f}}_{\bf{2}}}\left( {{{\bf{y}}_{\bf{0}}}} \right){\bf{ = 0}}\), and let\({{\bf{A}}_{\bf{0}}}{\bf{ = }}\left( {{{\bf{y}}_{\bf{0}}}{\bf{ - }} \in {\bf{,}}{{\bf{y}}_{\bf{0}}}{\bf{ + }} \in } \right)\). Also, let\({{\bf{y}}_{\bf{1}}}\)be such that\({{\bf{f}}_{\bf{2}}}\left( {{{\bf{y}}_{\bf{1}}}} \right){\bf{ > 0}}\), and let\({{\bf{A}}_{\bf{1}}}{\bf{ = }}\left( {{{\bf{y}}_{\bf{1}}}{\bf{ - }} \in {\bf{,}}{{\bf{y}}_{\bf{1}}}{\bf{ + }} \in } \right)\). Assume that\({{\bf{f}}_{\bf{2}}}\)is continuous at both\({{\bf{y}}_{\bf{0}}}\)and\({{\bf{y}}_{\bf{1}}}\).

Show that

\(\mathop {{\bf{lim}}}\limits_{ \in \to {\bf{0}}} \,\frac{{{\bf{Pr}}\left( {{\bf{Y}} \in {{\bf{A}}_{\bf{0}}}} \right)}}{{{\bf{Pr}}\left( {{\bf{Y}} \in {{\bf{A}}_{\bf{1}}}} \right)}}{\bf{ = 0}}{\bf{.}}\)

That is, the probability that Y is close to\({{\bf{y}}_{\bf{0}}}\)is much smaller than the probability that Y is close to\({{\bf{y}}_{\bf{1}}}\).

Short Answer

Expert verified

\(\mathop {\lim }\limits_{ \in \to 0} \frac{{\Pr \left( {Y \in {A_i}} \right)}}{{\Pr \left( {Y \in {A_1}} \right)}} = 0\)

Step by step solution

01

Given information

The conditional p.d.f. of X given\(Y = y\)is arbitrary if\({f_2}\left( y \right) = 0\)

Y is close to\({y_0}\)such that\({f_2}\left( {{y_0}} \right) = 0\).

And let,

\({A_0} = \left( {{y_0} - \in ,{y_0} + \in } \right)\)

And\({y_1}\)is such that,\({f_2}\left( {{y_1}} \right) > 0\), and\({A_1} = \left( {{y_1} - \in ,{y_1} + \in } \right)\)

\({f_2}\) is continuous at both \({y_0}\) and \({y_1}\)

02

Necessary calculation

Let, \({F_2}\) be the c.d.f. of Y.

Since\({f_2}\)is continuous at both\({y_0}\,and\,{y_1}\), we can write, for\(i = 0,1\)

\(\begin{align}\Pr \left( {Y \in {A_i}} \right) &= {F_2}\left( {{y_i} - \in } \right) - {F_2}\left( {{y_i} - \in } \right)\\ &= 2 \in {f_2}\left( {{{\left( {{y_i}} \right)}^\prime }} \right),\end{align}\)

Where,\({y_i}^\prime \)is within\( \in \)of\({y_i}\).

This last equation follows from the mean value theorem of calculus.

So,

\(\frac{{\Pr \left( {Y \in {A_i}} \right)}}{{\Pr \left( {Y \in {A_1}} \right)}} = \frac{{{f_2}\left( {{{\left( {{y_0}} \right)}^\prime }} \right)}}{{{f_2}\left( {{{\left( {{y_1}} \right)}^\prime }} \right)}}\)

Since\({f_2}\)is continuous,

\(\mathop {\lim }\limits_{ \in \to 0} {f_2}\left( {{{\left( {{y_i}} \right)}^\prime }} \right) = {f_2}\left( {{y_i}} \right)\)

So,

\(\begin{align}\mathop {\lim }\limits_{ \in \to 0} \frac{{\Pr \left( {Y \in {A_i}} \right)}}{{\Pr \left( {Y \in {A_1}} \right)}} &= \mathop {\lim }\limits_{ \in \to 0} \frac{{{f_2}\left( {{{\left( {{y_0}} \right)}^\prime }} \right)}}{{{f_2}\left( {{{\left( {{y_1}} \right)}^\prime }} \right)}}\\ &= \frac{{\mathop {\lim }\limits_{ \in \to 0} {f_2}\left( {{{\left( {{y_0}} \right)}^\prime }} \right)}}{{\mathop {\lim }\limits_{ \in \to 0} {f_2}\left( {{{\left( {{y_1}} \right)}^\prime }} \right)}}\\ &= \frac{{{f_2}\left( {{y_0}} \right)}}{{{f_2}\left( {{y_1}} \right)}}\\ &= \frac{0}{{{f_2}\left( {{y_1}} \right)}}\\ &= 0\end{align}\)

Therefore, \(\mathop {\lim }\limits_{ \in \to 0} \frac{{\Pr \left( {Y \in {A_i}} \right)}}{{\Pr \left( {Y \in {A_1}} \right)}} = 0\)

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with 91影视!

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

Suppose that two balanced dice are rolled, and letXdenote the absolute value of the difference between thetwo numbers that appear. Determine and sketch the p.f.ofX.

Let Z be the rate at which customers are served in a queue. Assume that Z has the p.d.f.

\(\begin{aligned}f\left( z \right) &= 2e{}^{ - 2z},z > 0\\ &= 0,otherwise\end{aligned}\)

Find the p.d.f. of the average waiting time T = 1/Z.

Consider the Markov chain in Example 3.10.2 with initial

probability vector \(v = \left( {\frac{1}{2},\frac{1}{2}} \right)\) Where \(p = \left[ {\begin{array}{*{20}{c}}{\frac{1}{3}}&{\frac{2}{3}}\\{\frac{1}{3}}&{\frac{1}{3}}\end{array}} \right]\)

a.Find the probability vector specifying the probabilities

of the states at timen=2.

b.Find the two-step transition matrix

Suppose that the n variables\({{\bf{X}}_{\bf{1}}}{\bf{ \ldots }}{{\bf{X}}_{\bf{n}}}\) form a random sample from the uniform distribution on the interval [0, 1]and that the random variables \({{\bf{Y}}_{\bf{1}}}\;{\bf{and}}\;{{\bf{Y}}_{\bf{n}}}\) are defined as in Eq. (3.9.8). Determine the value of \({\bf{Pr}}\left( {{{\bf{Y}}_{\bf{1}}} \le {\bf{0}}{\bf{.1}}\;{\bf{and}}\;{\bf{Y}}_{\bf{n}}^{} \le {\bf{0}}{\bf{.8}}} \right)\)

Let X be a random vector that is split into three parts,\(X = \left( {Y,Z,W} \right)\)Suppose that X has a continuous joint distribution with p.d.f.\(f\left( {y,z,w} \right)\).Let\({g_1}\left( {y,z|w} \right)\)be the conditional p.d.f. of (Y, Z) given W = w, and let\({g_2}\left( {y|w} \right)\)be the conditional p.d.f. of Y given W = w. Prove that\({g_2}\left( {y|w} \right) = \int {{g_1}\left( {y,z|w} \right)dz} \)

See all solutions

Recommended explanations on Math Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.