In this section we prove the equivalence of the statements in theorem 3A by showing that each implies its successor. For ease of writing, on occasion we write \(F_{n}(\cdot)\) for \(F_{Z_{n}}(\cdot), \phi_{n}(\cdot)\) for \(\phi_{Z_{n}}(\cdot), F(\cdot)\) for \(F_{Z}(\cdot)\) , and \(\phi(\cdot)\) for \(\phi_{Z}(\cdot)\) .

It is immediate that (i) implies (ii), since the function \(g(z)=e^{i u z}\) is a bounded continuous function of \(z\) .

To prove that (ii) implies (iii), we make use of the basic formula (3.6) of Chapter 9 . For any \(d>0\) define the function \(g_{d}(\cdot)\) for any real number \(z\) by \begin{align} g_{d}(z) & = \begin{cases} 1, & \text{if } a \leq z \leq b \\ 1 - \left(\frac{a - z}{d}\right), & \text{if } a - d \leq z \leq a \\ 1 - \left(\frac{z - b}{d}\right), & \text{if } b \leq z \leq b + d \\ 0, & \text{otherwise.} \end{cases} \end{align} 

The function \(g_{d}(\cdot)\) is continuous and integrable. Its Fourier transform \(\gamma_{d}(\cdot)\) is given for any \(u\) by \[\gamma_{d}(u)=\frac{1}{2 \pi} \int_{-\infty}^{\infty} e^{-i u z} g_{d}(z) d z=\frac{1}{2 \pi i u} \int_{-\infty}^{\infty} e^{-i u z} g_{d}^{\prime}(z) d z, \tag{5.1}\] Therefore, \begin{align} \gamma_{d}(u) & =\frac{1}{2 \pi i u d}\left(\int_{a-d}^{a} e^{-i u z}-\int_{b}^{b+d} e^{-i u z}\right) \tag{5.2} \\[3mm] & =\frac{1}{2 \pi u^{2} d}\left(e^{-i u a}-e^{-i u(a-d)}-e^{-i u(b+d)}+e^{-i u b}\right). \end{align} 

Thus we see that the Fourier transform \(\gamma_{d}(\cdot)\) is integrable. Consequently, from (3.6), of Chapter 9 we have. \[\int_{-\infty}^{\infty} g_{d}(z) d F_{Z_{n}}(z)-\int_{-\infty}^{\infty} g_{d}(z) d F_{Z}(z)=\int_{-\infty}^{\infty} d u \gamma_{d}(u)\left[\phi_{Z_{n}}(u)-\phi_{Z}(u)\right]. \tag{5.3}\] 

By letting \(n\) tend to \(\infty\) in (5.3) and using the hypothesis of statement (ii), we obtain for any \(d>0\) , as \(n\) tends to \(\infty\) , \[\int_{-\infty}^{\infty} g_{d}(z) d F_{Z_{n}}(z) \rightarrow \int_{-\infty}^{\infty} g_{d}(z) d F_{Z}(z). \tag{5.4}\] Next, define the function \(g_{d}^{*}(\cdot)\) for any \(z\) by \begin{align} g_{d}^{*}(z) & = \begin{cases} 1, & \text{if } a + d \leq z \leq b - d \\ \frac{z - a}{d}, & \text{if } a \leq z \leq a + d \\ \frac{b - z}{d}, & \text{if } b - d \leq z \leq b \\ 0, & \text{otherwise.} \end{cases} \end{align} 

By the foregoing argument, one may prove that (5.4) holds for \(g_{d}^{*}(\cdot)\) . Now, the expectations of the functions \(g_{d}(\cdot)\) and \(g_{d}^{*}(\cdot)\) clearly straddle the quantity \(F_{Z_{n}}(b)-F_{Z_{n}}(a)\) : \[\int_{-\infty}^{\infty} g_{a}^{*}(z) d F_{Z_{n}}(z) \leq F_{Z_{n}}(b)-F_{Z_{n}}(a) \leq \int_{-\infty}^{\infty} g_{d}(z) d F_{Z_{n}}(z) . \tag{5.5}\] From (5.5), letting \(n\) tend to \(\infty\) , we obtain \begin{align} \int_{-\infty}^{\infty} g_{d}^{*}(z) d F_{Z}(z) & \leq \liminf_{n} F_{Z_{n}}(b)-F_{Z_{n}}(a) \tag{5.6} \\ & \leq \limsup_{n} F_{Z_{n}}(b)-F_{Z_{n}}(a) \\ & \leq \int_{-\infty}^{\infty} g_{d}(z) d F_{Z}(z). \end{align} 

Now, let \(d\) tend to 0 in (5.6); since \begin{align} 0 \leq F_{Z}(b)-F_{Z}(a)&-\int_{-\infty}^{\infty} g_{d}^{*}(z) d F_{Z}(z) \leq F_{Z}(a+d) \\[3mm] &\qquad-F_{Z}(a)+F_{Z}(b)-F_{Z}(b-d) \rightarrow 0, \tag{5.7} \\[3mm] 0 \leq \int_{-\infty}^{\infty} g_{d}(z) d F_{Z}(z)&-\left[F_{Z}(b)-F_{Z}(a)\right] \leq F_{Z}(a) \\[3mm] &\quad -F_{Z}(a-d)+F_{Z}(b+d)-F_{Z}(b) \rightarrow 0. \end{align} as \(d\) tends to 0, it follows that (3.4) holds. Note that (5.7) would not hold if we did not require \(a\) and \(b\) to be points at which \(F_{Z}(\cdot)\) is continuous.

We next prove that (iii) implies (iv). Let \(M\) be a positive number such that \(F(\cdot)\) is continuous at \(M\) and at \(-M\) . Then, for any real number \(a\) \begin{align} \left|F_{n}(a)-F(a)\right| \leq \mid F_{n}(a)-F_{n}(-M)-F(a) & +F(-M) \mid \tag{5.8} \\ & +F_{n}(-M)+F(-M). \end{align} Since statement (iii) holds, it follows that if \(a\) is a continuity point of \(F(\cdot)\) \[\limsup_{n} |F_n(a) - F(a)| \leq F(-M) + \limsup_{n} F_n(-M). \tag{5.9}\] Now, also by (iii), since \(F_{n}(M)-F_{n}(-M)\) tends to \(F(M)-F(-M)\) , \begin{align} \limsup_{n} F_{n}(-M) & \leq \limsup_{n} \left(1 - F_{n}(M) + F_{n}(-M)\right) \\[2mm] & \leq 1 - F(M) + F(-M). \tag{5.10} \end{align} Consequently, \[\limsup_{n} \left|F_{n}(a)-F(a)\right| \leq 2 F(-M)+1-F(M), \tag{5.11}\] which tends to \(0\) , as one lets \(M\) tend to \(\infty\) . The proof that (iii) implies (iv) is complete.

We next prove that (iv) implies (i). We first note that a function \(g(\cdot)\) , continuous on a closed interval, is uniformly continuous there; that is, for every positive number \(\epsilon\) there is a positive number, derioted by \(d(\epsilon)\) , such that \(\left|g\left(z_{1}\right)-g\left(z_{2}\right)\right| \leq \epsilon\) for any two points \(z_{1}\) and \(z_{2}\) in the interval satisfying. \(\left|z_{1}-z_{2}\right| \leq d(\epsilon)\) . Choose \(M\) so that \(F(\cdot)\) is continuous at \(M\) and \(-M\) . On the closed interval \([-M, M], g(\cdot)\) is continuous. Fix \(\epsilon>0\) , and let \(d(\epsilon)\) be defined as in the foregoing sentence. We may then choose \((K+1)\) real numbers \(a_{0}, a_{1}, \ldots, a_{K}\) having these properties: (i) \(-M=a_{0}, (ii) \(a_{k}-a_{k-1} \leq d(\epsilon)\) for \(k=1,2, \ldots, K\) , (iii) for \(k=1,2, \ldots, K, F(\cdot)\) is continuous at \(a_{k}\) . Then define a function \(g(\cdot ; \epsilon, M)\) : \begin{align} g(x ; \epsilon, M) & = \begin{cases} 0, & \text{if } |x| > M \\ g(a_{k}), & \text{if } a_{k-1} < x \leq a_{k}, \quad \text{for some } k = 1, 2, \ldots, K, \\ g(-M), & \text{if } x = -M. \end{cases} \end{align} It is clear that for \(|x| \leq M\) \[\quad|g(x)-g(x ; \epsilon, M)| \leq \epsilon. \tag{5.13}\] Now \[\left|\int_{-\infty}^{\infty} g(x) d F_{n}(x)-\int_{-\infty}^{\infty} g(x) d F(x)\right| \leq\left|I_{n}\right|+\left|J_{n}\right|+|I|, \tag{5.14}\] where \begin{align} I_{n} & =\int_{-\infty}^{\infty}[g(x)-g(x ; \epsilon, M)] d F_{n}(x) \\ I & =\int_{-\infty}^{\infty}[g(x)-g(x ; \epsilon, M)] d F(x) \\ J_{n} & =\int_{-\infty}^{\infty} g(x ; \epsilon, M) d F_{n}(x)-\int_{-\infty}^{\infty} g(x ; \epsilon, M) d F(x) \end{align} 

Let \(C\) be an upper bound for \(g(\cdot)\) ; that is, \(|g(x)| \leq C\) for all \(x\) . Then \[\left|J_{n}\right| \leq C \sum_{k=1}^{K}\left[\left|F_{n}\left(a_{k}\right)-F\left(a_{k}\right)\right|+\mid F_{n}\left(a_{k-1}\right)-F\left(a_{k-1}\right)|\right]. \tag{5.15}\] 

Next, we may write \(I_{n}\) as a sum of two integrals, one over the range \(|x| \leq M\) and the other over the range \(|x|>M\) . In view of (5.13), we then have \[\left|I_{n}\right| \leq \epsilon+C\left[1-F_{n}(M)+F_{n}(-M)\right].\] Similarly \[|I| \leq \epsilon+C[1-F(M)+F(-M)].\] In view of (5.14), (5.15), and the two preceding inequalities, it follows that \[\limsup_{n} \left|\int_{-\infty}^{\infty} g(x) \, dF_{n}(x) - \int_{-\infty}^{\infty} g(x) \, dF(x)\right| \tag{5.16}\] \[\leq 2 \epsilon+2 C[1-F(M)+F(-M)].\] 

Letting first \(\epsilon\) tend to 0 and then \(M\) tend to \(\infty\) , it follows that (5.13) will hold. The proof that (iv) implies (i) is complete.

The reader may easily verify that (v) is equivalent to the preceding statements.

Theoretical exercises

5.1.Convergence of the means of random variables convergent in distribution. If \(Z_{n}\) converges in distribution to \(Z\) , show that for \(M>0\) such that \(F_{Z}(\cdot)\) is continuous at \(\pm M\) , as \(n\) tends to \(\infty\) .

\[\int_{-M}^{M} z d F_{Z_{n}}(z) \rightarrow \int_{-M}^{M} z d F_{Z}(z).\] 

From this it does not follow that \(E\left[Z_{n}\right]\) converges to \(E[Z]\) .

Hint: Let \(F_{Z_{n}}(z)=0,1-(1 / n), 1\) , depending on whether \(z<0,0 \leq z; then \(E\left[Z_{n}\right]=1\) does not tend to \(E[Z]=0\) . But if \(Z_{n}\) converges in distribution to \(Z\) and, in addition, \(E\left[Z_{n}\right]\) exists for all \(n\) and

\[\lim _{M \rightarrow \infty} \limsup _{n \rightarrow \infty} \int_{|z| \geq M}|z| d F_{Z_{n}}(z)=0, \tag{5.17}\] 

then \(E\left[Z_{n}\right]\) converges to \(E[Z]\) .

5.2 . On uniform convergence of distribution functions. Let \(\left\{Z_{n}\right\}\) be a sequence of random variables converging in distribution to the random variable \(Z\) , so that, for each real number \(z, \displaystyle\lim_{n} F_{Z_{n}}(z)=F_{Z}(z)\) . Show that if \(Z\) is a continuous random variable, so that \(F_{Z}(\cdot)\) has no points of discontinuity, then the distribution functions converge uniformly; more precisely

\[\lim _{n \rightarrow \infty} \underset{-\infty

Hint: To any \(\epsilon>0\) , choose points \(-\infty=z_{0}, so that \(F_{Z}\left(z_{j}\right)-F_{Z}\left(z_{j-1}\right)<\epsilon\) for \(j=1,2, \ldots, K\) . Verify that

\[\underset{-\infty