lecture 10 thm 5
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@ -154,7 +154,8 @@ However, Fourier analysis is not only useful for continuous probability density
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Let $\phi$ be the characteristic function of $\bP \in M_1(\lambda)$.
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Let $\phi$ be the characteristic function of $\bP \in M_1(\lambda)$.
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Then
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Then
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\begin{enumerate}[(a)]
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\begin{enumerate}[(a)]
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\item $\phi(0) = 1$, $|\phi(t)| \le 1$ and $\phi(\cdot )$ is continuous.
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\item $\phi(0) = 1$, $|\phi(t)| \le 1$, $\phi(-t) = \overline{\phi(t)}$
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and $\phi(\cdot )$ is continuous.
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\item $\phi$ is a \vocab{positive definite function},
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\item $\phi$ is a \vocab{positive definite function},
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i.e.~
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i.e.~
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\[\forall t_1,\ldots, t_n \in \R, (c_1,\ldots,c_n) \in \C^n ~ \sum_{j,k = 1}^n c_j \overline{c_k} \phi(t_j - t_k) \ge 0
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\[\forall t_1,\ldots, t_n \in \R, (c_1,\ldots,c_n) \in \C^n ~ \sum_{j,k = 1}^n c_j \overline{c_k} \phi(t_j - t_k) \ge 0
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