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Headings-> Derivatives Taylor Coefficients Recursion

@(@\newcommand{\W}[1]{ \; #1 \; } \newcommand{\R}[1]{ {\rm #1} } \newcommand{\B}[1]{ {\bf #1} } \newcommand{\D}[2]{ \frac{\partial #1}{\partial #2} } \newcommand{\DD}[3]{ \frac{\partial^2 #1}{\partial #2 \partial #3} } \newcommand{\Dpow}[2]{ \frac{\partial^{#1}}{\partial {#2}^{#1}} } \newcommand{\dpow}[2]{ \frac{ {\rm d}^{#1}}{{\rm d}\, {#2}^{#1}} }@)@ This is cppad-20221105 documentation. Here is a link to its current documentation . Logarithm Function Forward Mode Theory
Derivatives
If @(@ F(x) @)@ is @(@ \R{log} (x) @)@ or @(@ \R{log1p} (x) @)@ the corresponding derivative satisfies the equation @[@ ( \bar{b} + x ) * F^{(1)} (x) - 0 * F (x) = 1 @]@ where @[@ \bar{b} = \left\{ \begin{array}{ll} 0 & \R{if} \; F(x) = \R{log}(x) \\ 1 & \R{if} \; F(x) = \R{log1p}(x) \end{array} \right. @]@ In the standard math function differential equation , @(@ A(x) = 0 @)@, @(@ B(x) = \bar{b} + x @)@, and @(@ D(x) = 1 @)@. We use @(@ a @)@, @(@ b @)@, @(@ d @)@, and @(@ z @)@ to denote the Taylor coefficients for @(@ A [ X (t) ] @)@, @(@ B [ X (t) ] @)@, @(@ D [ X (t) ] @)@, and @(@ F [ X(t) ] @)@ respectively.

Taylor Coefficients Recursion
For orders @(@ j = 0 , 1, \ldots @)@, @[@ \begin{array}{rcl} z^{(0)} & = & F ( x^{(0)} ) \\ e^{(j)} & = & d^{(j)} + \sum_{k=0}^{j} a^{(j-k)} * z^{(k)} \\ & = & \left\{ \begin{array}{ll} 1 & {\rm if} \; j = 0 \\ 0 & {\rm otherwise} \end{array} \right. \\ z^{(j+1)} & = & \frac{1}{j+1} \frac{1}{ b^{(0)} } \left( \sum_{k=1}^{j+1} k x^{(k)} e^{(j+1-k)} - \sum_{k=1}^j k z^{(k)} b^{(j+1-k)} \right) \\ & = & \frac{1}{j+1} \frac{1}{ \bar{b} + x^{(0)} } \left( (j+1) x^{(j+1) } - \sum_{k=1}^j k z^{(k)} x^{(j+1-k)} \right) \end{array} @]@

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