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Merge pull request #66 from StatProofBook/master
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D/cf.md

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in: "Wikipedia, the free encyclopedia"
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pages: "retrieved on 2021-09-22"
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url: "https://en.wikipedia.org/wiki/Characteristic_function_(probability_theory)#Definition"
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- authors: "Taboga, Marco"
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year: 2017
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title: "Joint characteristic function"
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in: "Lectures on probability and mathematical statistics"
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pages: "retrieved on 2021-10-07"
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url: "https://www.statlect.com/fundamentals-of-probability/joint-characteristic-function"
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def_id: "D159"
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shortcut: "cf"

D/mgf.md

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in: "Wikipedia, the free encyclopedia"
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pages: "retrieved on 2020-01-22"
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url: "https://en.wikipedia.org/wiki/Moment-generating_function#Definition"
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- authors: "Taboga, Marco"
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year: 2017
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title: "Joint moment generating function"
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in: "Lectures on probability and mathematical statistics"
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pages: "retrieved on 2021-10-07"
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url: "https://www.statlect.com/fundamentals-of-probability/joint-moment-generating-function"
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def_id: "D2"
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shortcut: "mgf"

I/Proof_by_Author.md

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---
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### JoramSoch (250 proofs)
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### JoramSoch (252 proofs)
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- [(Non-)Multiplicativity of the expected value](/P/mean-mult)
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- [Accuracy and complexity for the univariate Gaussian](/P/ug-anc)
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- [Accuracy and complexity for the univariate Gaussian with known variance](/P/ugkv-anc)
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- [Addition law of probability](/P/prob-add)
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- [Addition of the differential entropy upon multiplication with a constant](/P/dent-add)
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- [Addition of the differential entropy upon multiplication with invertible matrix](/P/dent-addvec)
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- [Additivity of the Kullback-Leibler divergence for independent distributions](/P/kl-add)
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- [Additivity of the variance for independent random variables](/P/var-add)
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- [Bayes' rule](/P/bayes-rule)
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- [Monotonicity of probability](/P/prob-mon)
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- [Monotonicity of the expected value](/P/mean-mono)
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- [Necessary and sufficient condition for independence of multivariate normal random variables](/P/mvn-ind)
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- [Non-invariance of the differential entropy under change of variables](/P/dent-noninv)
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- [Non-negativity of the Kullback-Leibler divergence](/P/kl-nonneg)
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- [Non-negativity of the Kullback-Leibler divergence](/P/kl-nonneg2)
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- [Non-negativity of the Shannon entropy](/P/ent-nonneg)

I/Proof_by_Number.md

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| P258 | pdf-sumind | [Probability density function of a sum of independent discrete random variables](/P/pdf-sumind) | JoramSoch | 2021-08-30 |
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| P259 | cf-fct | [Characteristic function of a function of a random variable](/P/cf-fct) | JoramSoch | 2021-09-22 |
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| P260 | mgf-fct | [Moment-generating function of a function of a random variable](/P/mgf-fct) | JoramSoch | 2021-09-22 |
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| P261 | dent-addvec | [Addition of the differential entropy upon multiplication with invertible matrix](/P/dent-addvec) | JoramSoch | 2021-10-07 |
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| P262 | dent-noninv | [Non-invariance of the differential entropy under change of variables](/P/dent-noninv) | JoramSoch | 2021-10-07 |

I/Proof_by_Topic.md

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- [Accuracy and complexity for the univariate Gaussian with known variance](/P/ugkv-anc)
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- [Addition law of probability](/P/prob-add)
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- [Addition of the differential entropy upon multiplication with a constant](/P/dent-add)
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- [Addition of the differential entropy upon multiplication with invertible matrix](/P/dent-addvec)
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- [Additivity of the Kullback-Leibler divergence for independent distributions](/P/kl-add)
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- [Additivity of the variance for independent random variables](/P/var-add)
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### N
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- [Necessary and sufficient condition for independence of multivariate normal random variables](/P/mvn-ind)
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- [Non-invariance of the differential entropy under change of variables](/P/dent-noninv)
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- [Non-negativity of the Kullback-Leibler divergence](/P/kl-nonneg)
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- [Non-negativity of the Kullback-Leibler divergence](/P/kl-nonneg2)
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- [Non-negativity of the Shannon entropy](/P/ent-nonneg)

P/dent-addvec.md

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\end{split}
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$$
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Using the differential $\mathrm{d}(Ax) = \left|A\right| \mathrm{d}x$, this becomes
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Using the differential $\mathrm{d}(Ax) = \lvert A \rvert \mathrm{d}x$, this becomes
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$$ \label{eq:Y-dent-s3}
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\begin{split}

P/dent-noninv.md

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\end{split}
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$$
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Using the relations $y = f(x) \Rightarrow \mathrm{d}y = \left| J_f(x) \right| \, \mathrm{d}x$ and $\left|A\right|\left|B\right| = \left|AB\right|$, this becomes
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Using the relations $y = f(x) \Rightarrow \mathrm{d}y = \lvert J_f(x) \rvert \, \mathrm{d}x$ and $\lvert A \rvert \lvert B \rvert = \lvert AB \rvert$, this becomes
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$$ \label{eq:Y-dent-s3}
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\begin{split}
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\end{split}
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$$
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Finally, employing [the fact](/D/pdf) that $\int_{\mathcal{X}} f_X(x) \, \mathrm{d}x = 1$ and the determinant property $\left|A^{-1}\right| = 1/\left|A\right|$, we can derive the [differential entropy](/D/dent) of $Y$ as
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Finally, employing [the fact](/D/pdf) that $\int_{\mathcal{X}} f_X(x) \, \mathrm{d}x = 1$ and the determinant property $\lvert A^{-1} \rvert = 1/\lvert A \rvert$, we can derive the [differential entropy](/D/dent) of $Y$ as
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$$ \label{eq:Y-dent-s4}
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\begin{split}

P/pdf-invfct.md

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A(y) = \left\lbrace x \in \mathbb{R}^n: g_j(x) \leq y_j \; \text{for all} \; j = 1, \ldots, n \right\rbrace
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$$
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and $g_j(X)$ is the function which returns the $j$-th element of $Y$, given a vector $x$.
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and $g_j(X)$ is the function which returns the $j$-th element of $Y$, given a vector $X$.
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<br>
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2) Next, we substitute $x = g^{-1}(y)$ into the integral which gives us

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