[172] | 1 | \hypertarget{classmgamma}{ |
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[30] | 2 | \section{mgamma Class Reference} |
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| 3 | \label{classmgamma}\index{mgamma@{mgamma}} |
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[172] | 4 | } |
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[30] | 5 | Gamma random walk. |
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| 6 | |
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| 7 | |
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| 8 | {\tt \#include $<$libEF.h$>$} |
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| 9 | |
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[33] | 10 | Inheritance diagram for mgamma:\nopagebreak |
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| 11 | \begin{figure}[H] |
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| 12 | \begin{center} |
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| 13 | \leavevmode |
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[91] | 14 | \includegraphics[width=58pt]{classmgamma__inherit__graph} |
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[33] | 15 | \end{center} |
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| 16 | \end{figure} |
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[30] | 17 | Collaboration diagram for mgamma:\nopagebreak |
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| 18 | \begin{figure}[H] |
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| 19 | \begin{center} |
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| 20 | \leavevmode |
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[91] | 21 | \includegraphics[width=76pt]{classmgamma__coll__graph} |
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[30] | 22 | \end{center} |
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| 23 | \end{figure} |
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| 24 | \subsection*{Public Member Functions} |
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| 25 | \begin{CompactItemize} |
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| 26 | \item |
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[172] | 27 | \hypertarget{classmgamma_af43e61b86900c0398d5c0ffc83b94e6}{ |
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| 28 | \hyperlink{classmgamma_af43e61b86900c0398d5c0ffc83b94e6}{mgamma} (const \hyperlink{classRV}{RV} \&\hyperlink{classmpdf_f6687c07ff07d47812dd565368ca59eb}{rv}, const \hyperlink{classRV}{RV} \&\hyperlink{classmpdf_acb7dda792b3cd5576f39fa3129abbab}{rvc})} |
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| 29 | \label{classmgamma_af43e61b86900c0398d5c0ffc83b94e6} |
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[30] | 30 | |
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| 31 | \begin{CompactList}\small\item\em Constructor. \item\end{CompactList}\item |
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[172] | 32 | \hypertarget{classmgamma_a9d646cf758a70126dde7c48790b6e94}{ |
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| 33 | void \hyperlink{classmgamma_a9d646cf758a70126dde7c48790b6e94}{set\_\-parameters} (double \hyperlink{classmgamma_43f733cce0245a52363d566099add687}{k})} |
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| 34 | \label{classmgamma_a9d646cf758a70126dde7c48790b6e94} |
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[30] | 35 | |
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[33] | 36 | \begin{CompactList}\small\item\em Set value of {\tt k}. \item\end{CompactList}\item |
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[172] | 37 | \hypertarget{classmgamma_a61094c9f7a2d64ea77b130cbc031f97}{ |
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| 38 | void \hyperlink{classmgamma_a61094c9f7a2d64ea77b130cbc031f97}{condition} (const vec \&val)} |
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| 39 | \label{classmgamma_a61094c9f7a2d64ea77b130cbc031f97} |
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[30] | 40 | |
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[172] | 41 | \begin{CompactList}\small\item\em Update {\tt ep} so that it represents this \hyperlink{classmpdf}{mpdf} conditioned on {\tt rvc} = cond. \item\end{CompactList}\item |
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| 42 | virtual vec \hyperlink{classmpdf_3f172b79ec4a5ebc87898a5381141f1b}{samplecond} (const vec \&cond, double \&ll) |
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| 43 | \begin{CompactList}\small\item\em Returns the required moment of the \hyperlink{classepdf}{epdf}. \item\end{CompactList}\item |
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| 44 | virtual mat \hyperlink{classmpdf_0e37163660f93df2a4d723cedb1da89c}{samplecond} (const vec \&cond, vec \&ll, int N) |
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[162] | 45 | \begin{CompactList}\small\item\em Returns. \item\end{CompactList}\item |
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[172] | 46 | \hypertarget{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}{ |
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| 47 | virtual double \hyperlink{classmpdf_80b738ece5bd4f8c4edaee4b38906f91}{evalcond} (const vec \&dt, const vec \&cond)} |
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| 48 | \label{classmpdf_80b738ece5bd4f8c4edaee4b38906f91} |
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[30] | 49 | |
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[172] | 50 | \begin{CompactList}\small\item\em Shortcut for conditioning and evaluation of the internal \hyperlink{classepdf}{epdf}. In some cases, this operation can be implemented efficiently. \item\end{CompactList}\item |
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| 51 | \hypertarget{classmpdf_ec9c850305984582548e8deb64f0ffe8}{ |
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| 52 | \hyperlink{classRV}{RV} \hyperlink{classmpdf_ec9c850305984582548e8deb64f0ffe8}{\_\-rvc} ()} |
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| 53 | \label{classmpdf_ec9c850305984582548e8deb64f0ffe8} |
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[30] | 54 | |
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[33] | 55 | \begin{CompactList}\small\item\em access function \item\end{CompactList}\item |
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[172] | 56 | \hypertarget{classmpdf_1e71ad4c66d5884c82d4a3b06b42fe32}{ |
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| 57 | \hyperlink{classRV}{RV} \hyperlink{classmpdf_1e71ad4c66d5884c82d4a3b06b42fe32}{\_\-rv} ()} |
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| 58 | \label{classmpdf_1e71ad4c66d5884c82d4a3b06b42fe32} |
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[162] | 59 | |
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| 60 | \begin{CompactList}\small\item\em access function \item\end{CompactList}\item |
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[172] | 61 | \hypertarget{classmpdf_e17780ee5b2cfe05922a6c56af1462f8}{ |
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| 62 | \hyperlink{classepdf}{epdf} \& \hyperlink{classmpdf_e17780ee5b2cfe05922a6c56af1462f8}{\_\-epdf} ()} |
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| 63 | \label{classmpdf_e17780ee5b2cfe05922a6c56af1462f8} |
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[33] | 64 | |
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| 65 | \begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize} |
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| 66 | \subsection*{Protected Attributes} |
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| 67 | \begin{CompactItemize} |
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| 68 | \item |
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[172] | 69 | \hypertarget{classmgamma_612dbf35c770a780027619aaac2c443e}{ |
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| 70 | \hyperlink{classegamma}{egamma} \hyperlink{classmgamma_612dbf35c770a780027619aaac2c443e}{epdf}} |
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| 71 | \label{classmgamma_612dbf35c770a780027619aaac2c443e} |
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[79] | 72 | |
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[172] | 73 | \begin{CompactList}\small\item\em Internal \hyperlink{classepdf}{epdf} that arise by conditioning on {\tt rvc}. \item\end{CompactList}\item |
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| 74 | \hypertarget{classmgamma_43f733cce0245a52363d566099add687}{ |
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| 75 | double \hyperlink{classmgamma_43f733cce0245a52363d566099add687}{k}} |
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| 76 | \label{classmgamma_43f733cce0245a52363d566099add687} |
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[79] | 77 | |
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[91] | 78 | \begin{CompactList}\small\item\em Constant $k$. \item\end{CompactList}\item |
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[172] | 79 | \hypertarget{classmgamma_5e90652837448bcc29707e7412f99691}{ |
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| 80 | vec $\ast$ \hyperlink{classmgamma_5e90652837448bcc29707e7412f99691}{\_\-beta}} |
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| 81 | \label{classmgamma_5e90652837448bcc29707e7412f99691} |
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[79] | 82 | |
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| 83 | \begin{CompactList}\small\item\em cache of epdf.beta \item\end{CompactList}\item |
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[172] | 84 | \hypertarget{classmpdf_f6687c07ff07d47812dd565368ca59eb}{ |
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| 85 | \hyperlink{classRV}{RV} \hyperlink{classmpdf_f6687c07ff07d47812dd565368ca59eb}{rv}} |
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| 86 | \label{classmpdf_f6687c07ff07d47812dd565368ca59eb} |
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[33] | 87 | |
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| 88 | \begin{CompactList}\small\item\em modeled random variable \item\end{CompactList}\item |
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[172] | 89 | \hypertarget{classmpdf_acb7dda792b3cd5576f39fa3129abbab}{ |
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| 90 | \hyperlink{classRV}{RV} \hyperlink{classmpdf_acb7dda792b3cd5576f39fa3129abbab}{rvc}} |
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| 91 | \label{classmpdf_acb7dda792b3cd5576f39fa3129abbab} |
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[33] | 92 | |
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| 93 | \begin{CompactList}\small\item\em random variable in condition \item\end{CompactList}\item |
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[172] | 94 | \hypertarget{classmpdf_7aa894208a32f3487827df6d5054424c}{ |
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| 95 | \hyperlink{classepdf}{epdf} $\ast$ \hyperlink{classmpdf_7aa894208a32f3487827df6d5054424c}{ep}} |
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| 96 | \label{classmpdf_7aa894208a32f3487827df6d5054424c} |
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[33] | 97 | |
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[172] | 98 | \begin{CompactList}\small\item\em pointer to internal \hyperlink{classepdf}{epdf} \item\end{CompactList}\end{CompactItemize} |
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[33] | 99 | |
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| 100 | |
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[30] | 101 | \subsection{Detailed Description} |
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| 102 | Gamma random walk. |
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| 103 | |
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[91] | 104 | Mean value, $\mu$, of this density is given by {\tt rvc} . Standard deviation of the random walk is proportional to one $k$-th the mean. This is achieved by setting $\alpha=k$ and $\beta=k/\mu$. |
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[30] | 105 | |
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[33] | 106 | The standard deviation of the walk is then: $\mu/\sqrt(k)$. |
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[30] | 107 | |
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[162] | 108 | \subsection{Member Function Documentation} |
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[172] | 109 | \hypertarget{classmpdf_3f172b79ec4a5ebc87898a5381141f1b}{ |
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[162] | 110 | \index{mgamma@{mgamma}!samplecond@{samplecond}} |
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| 111 | \index{samplecond@{samplecond}!mgamma@{mgamma}} |
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[172] | 112 | \subsubsection[samplecond]{\setlength{\rightskip}{0pt plus 5cm}virtual vec mpdf::samplecond (const vec \& {\em cond}, \/ double \& {\em ll})\hspace{0.3cm}{\tt \mbox{[}inline, virtual, inherited\mbox{]}}}} |
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| 113 | \label{classmpdf_3f172b79ec4a5ebc87898a5381141f1b} |
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[162] | 114 | |
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| 115 | |
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[172] | 116 | Returns the required moment of the \hyperlink{classepdf}{epdf}. |
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[162] | 117 | |
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| 118 | Returns a sample from the density conditioned on {\tt cond}, $x \sim epdf(rv|cond)$. \begin{Desc} |
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| 119 | \item[Parameters:] |
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| 120 | \begin{description} |
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| 121 | \item[{\em cond}]is numeric value of {\tt rv} \item[{\em ll}]is a return value of log-likelihood of the sample. \end{description} |
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| 122 | \end{Desc} |
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| 123 | |
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| 124 | |
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[172] | 125 | Reimplemented in \hyperlink{classmprod_a48887eb8738a9e5550bfc38eb8e9d68}{mprod}. |
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| 126 | |
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[162] | 127 | References mpdf::condition(), mpdf::ep, epdf::evalpdflog(), and epdf::sample(). |
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| 128 | |
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[172] | 129 | Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\hypertarget{classmpdf_0e37163660f93df2a4d723cedb1da89c}{ |
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| 130 | \index{mgamma@{mgamma}!samplecond@{samplecond}} |
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[162] | 131 | \index{samplecond@{samplecond}!mgamma@{mgamma}} |
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[172] | 132 | \subsubsection[samplecond]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond (const vec \& {\em cond}, \/ vec \& {\em ll}, \/ int {\em N})\hspace{0.3cm}{\tt \mbox{[}inline, virtual, inherited\mbox{]}}}} |
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| 133 | \label{classmpdf_0e37163660f93df2a4d723cedb1da89c} |
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[162] | 134 | |
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| 135 | |
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| 136 | Returns. |
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| 137 | |
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| 138 | \begin{Desc} |
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| 139 | \item[Parameters:] |
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| 140 | \begin{description} |
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| 141 | \item[{\em N}]samples from the density conditioned on {\tt cond}, $x \sim epdf(rv|cond)$. \item[{\em cond}]is numeric value of {\tt rv} \item[{\em ll}]is a return value of log-likelihood of the sample. \end{description} |
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| 142 | \end{Desc} |
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| 143 | |
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| 144 | |
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[172] | 145 | Reimplemented in \hyperlink{classmprod_e171c40e210539c2af01d6237785620b}{mprod}. |
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| 146 | |
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[162] | 147 | References mpdf::condition(), RV::count(), mpdf::ep, epdf::evalpdflog(), mpdf::rv, and epdf::sample(). |
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| 148 | |
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[30] | 149 | The documentation for this class was generated from the following files:\begin{CompactItemize} |
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| 150 | \item |
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[172] | 151 | work/git/mixpp/bdm/stat/\hyperlink{libEF_8h}{libEF.h}\item |
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[145] | 152 | work/git/mixpp/bdm/stat/libEF.cpp\end{CompactItemize} |
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