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1\hypertarget{classbdm_1_1migamma__fix}{
2\section{bdm::migamma\_\-fix Class Reference}
3\label{classbdm_1_1migamma__fix}\index{bdm::migamma\_\-fix@{bdm::migamma\_\-fix}}
4}
5Inverse-Gamma random walk around a fixed point. 
6
7
8{\tt \#include $<$libEF.h$>$}
9
10Inheritance diagram for bdm::migamma\_\-fix:\nopagebreak
11\begin{figure}[H]
12\begin{center}
13\leavevmode
14\includegraphics[width=76pt]{classbdm_1_1migamma__fix__inherit__graph}
15\end{center}
16\end{figure}
17Collaboration diagram for bdm::migamma\_\-fix:\nopagebreak
18\begin{figure}[H]
19\begin{center}
20\leavevmode
21\includegraphics[height=400pt]{classbdm_1_1migamma__fix__coll__graph}
22\end{center}
23\end{figure}
24\subsection*{Public Member Functions}
25\begin{CompactItemize}
26\item 
27\hypertarget{classbdm_1_1migamma__fix_3c6aacebccbe6d73f8d442e82d3cb53a}{
28\hyperlink{classbdm_1_1migamma__fix_3c6aacebccbe6d73f8d442e82d3cb53a}{migamma\_\-fix} (const \hyperlink{classbdm_1_1RV}{RV} \&\hyperlink{classbdm_1_1mpdf_9bcfb45435d30983f436d41c298cbb51}{rv}, const \hyperlink{classbdm_1_1RV}{RV} \&\hyperlink{classbdm_1_1mpdf_5a5f08950daa08b85b01ddf4e1c36288}{rvc})}
29\label{classbdm_1_1migamma__fix_3c6aacebccbe6d73f8d442e82d3cb53a}
30
31\begin{CompactList}\small\item\em Constructor. \item\end{CompactList}\item 
32\hypertarget{classbdm_1_1migamma__fix_17f9ce1068660a4e8c05173bef7d7440}{
33void \hyperlink{classbdm_1_1migamma__fix_17f9ce1068660a4e8c05173bef7d7440}{set\_\-parameters} (double k0, vec ref0, double l0)}
34\label{classbdm_1_1migamma__fix_17f9ce1068660a4e8c05173bef7d7440}
35
36\begin{CompactList}\small\item\em Set value of {\tt k}. \item\end{CompactList}\item 
37\hypertarget{classbdm_1_1migamma__fix_cfbabd293795d44aae1b7c874e57c4b8}{
38void \hyperlink{classbdm_1_1migamma__fix_cfbabd293795d44aae1b7c874e57c4b8}{condition} (const vec \&val)}
39\label{classbdm_1_1migamma__fix_cfbabd293795d44aae1b7c874e57c4b8}
40
41\begin{CompactList}\small\item\em Update {\tt ep} so that it represents this \hyperlink{classbdm_1_1mpdf}{mpdf} conditioned on {\tt rvc} = cond. \item\end{CompactList}\item 
42\hypertarget{classbdm_1_1migamma_1d7023b1565551d0260eb1ba832bebaf}{
43void \hyperlink{classbdm_1_1migamma_1d7023b1565551d0260eb1ba832bebaf}{set\_\-parameters} (double k0)}
44\label{classbdm_1_1migamma_1d7023b1565551d0260eb1ba832bebaf}
45
46\begin{CompactList}\small\item\em Set value of {\tt k}. \item\end{CompactList}\item 
47virtual vec \hyperlink{classbdm_1_1mpdf_f0c1db6fcbb3aae2dd6123884457a367}{samplecond} (const vec \&cond)
48\begin{CompactList}\small\item\em Returns a sample from the density conditioned on {\tt cond}, $x \sim epdf(rv|cond)$. \item\end{CompactList}\item 
49virtual mat \hyperlink{classbdm_1_1mpdf_ee26963a637b2ea1fb1933652981e652}{samplecond\_\-m} (const vec \&cond, vec \&ll, int N)
50\begin{CompactList}\small\item\em Returns. \item\end{CompactList}\item 
51\hypertarget{classbdm_1_1mpdf_6336a8a72462e2a56a3989a220f18b1b}{
52virtual double \hyperlink{classbdm_1_1mpdf_6336a8a72462e2a56a3989a220f18b1b}{evallogcond} (const vec \&dt, const vec \&cond)}
53\label{classbdm_1_1mpdf_6336a8a72462e2a56a3989a220f18b1b}
54
55\begin{CompactList}\small\item\em Shortcut for conditioning and evaluation of the internal \hyperlink{classbdm_1_1epdf}{epdf}. In some cases, this operation can be implemented efficiently. \item\end{CompactList}\item 
56\hypertarget{classbdm_1_1mpdf_0b0ed1ed663071bb7cf4a1349eb94fcb}{
57virtual vec \hyperlink{classbdm_1_1mpdf_0b0ed1ed663071bb7cf4a1349eb94fcb}{evallogcond\_\-m} (const mat \&Dt, const vec \&cond)}
58\label{classbdm_1_1mpdf_0b0ed1ed663071bb7cf4a1349eb94fcb}
59
60\begin{CompactList}\small\item\em Matrix version of evallogcond. \item\end{CompactList}\item 
61\hypertarget{classbdm_1_1mpdf_b3aba7311038bf990d706a64cab60cf8}{
62\hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1mpdf_b3aba7311038bf990d706a64cab60cf8}{\_\-rvc} () const }
63\label{classbdm_1_1mpdf_b3aba7311038bf990d706a64cab60cf8}
64
65\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
66\hypertarget{classbdm_1_1mpdf_222d5280e309c5a053ba73841e98c151}{
67\hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1mpdf_222d5280e309c5a053ba73841e98c151}{\_\-rv} () const }
68\label{classbdm_1_1mpdf_222d5280e309c5a053ba73841e98c151}
69
70\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
71\hypertarget{classbdm_1_1mpdf_1892fe3933488942253679f068e9e7f6}{
72\hyperlink{classbdm_1_1epdf}{epdf} \& \hyperlink{classbdm_1_1mpdf_1892fe3933488942253679f068e9e7f6}{\_\-epdf} ()}
73\label{classbdm_1_1mpdf_1892fe3933488942253679f068e9e7f6}
74
75\begin{CompactList}\small\item\em access function \item\end{CompactList}\item 
76\hypertarget{classbdm_1_1mpdf_05e843fd11c410a99dad2b88c55aca80}{
77\hyperlink{classbdm_1_1epdf}{epdf} $\ast$ \hyperlink{classbdm_1_1mpdf_05e843fd11c410a99dad2b88c55aca80}{\_\-e} ()}
78\label{classbdm_1_1mpdf_05e843fd11c410a99dad2b88c55aca80}
79
80\begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize}
81\subsection*{Protected Attributes}
82\begin{CompactItemize}
83\item 
84\hypertarget{classbdm_1_1migamma__fix_e1c344accac36d7ccc3ffa502e8d2f4e}{
85double \hyperlink{classbdm_1_1migamma__fix_e1c344accac36d7ccc3ffa502e8d2f4e}{l}}
86\label{classbdm_1_1migamma__fix_e1c344accac36d7ccc3ffa502e8d2f4e}
87
88\begin{CompactList}\small\item\em parameter l \item\end{CompactList}\item 
89\hypertarget{classbdm_1_1migamma__fix_5d453e5a2bdfc9a16c8acb8842dc9780}{
90vec \hyperlink{classbdm_1_1migamma__fix_5d453e5a2bdfc9a16c8acb8842dc9780}{refl}}
91\label{classbdm_1_1migamma__fix_5d453e5a2bdfc9a16c8acb8842dc9780}
92
93\begin{CompactList}\small\item\em reference vector \item\end{CompactList}\item 
94\hypertarget{classbdm_1_1migamma_a31b39d4179551b593c9e0d7d756783a}{
95\hyperlink{classbdm_1_1eigamma}{eigamma} \hyperlink{classbdm_1_1migamma_a31b39d4179551b593c9e0d7d756783a}{epdf}}
96\label{classbdm_1_1migamma_a31b39d4179551b593c9e0d7d756783a}
97
98\begin{CompactList}\small\item\em Internal \hyperlink{classbdm_1_1epdf}{epdf} that arise by conditioning on {\tt rvc}. \item\end{CompactList}\item 
99\hypertarget{classbdm_1_1migamma_dc56bc9da542e0103ec16b9be8e5e38c}{
100double \hyperlink{classbdm_1_1migamma_dc56bc9da542e0103ec16b9be8e5e38c}{k}}
101\label{classbdm_1_1migamma_dc56bc9da542e0103ec16b9be8e5e38c}
102
103\begin{CompactList}\small\item\em Constant $k$. \item\end{CompactList}\item 
104\hypertarget{classbdm_1_1migamma_4825c0ef11a148bad9b802a496f56f96}{
105vec $\ast$ \hyperlink{classbdm_1_1migamma_4825c0ef11a148bad9b802a496f56f96}{\_\-beta}}
106\label{classbdm_1_1migamma_4825c0ef11a148bad9b802a496f56f96}
107
108\begin{CompactList}\small\item\em cache of epdf.beta \item\end{CompactList}\item 
109\hypertarget{classbdm_1_1migamma_b6c265b132ff79963bf51dff4c3ef252}{
110vec $\ast$ \hyperlink{classbdm_1_1migamma_b6c265b132ff79963bf51dff4c3ef252}{\_\-alpha}}
111\label{classbdm_1_1migamma_b6c265b132ff79963bf51dff4c3ef252}
112
113\begin{CompactList}\small\item\em chaceh of epdf.alpha \item\end{CompactList}\item 
114\hypertarget{classbdm_1_1mpdf_9bcfb45435d30983f436d41c298cbb51}{
115\hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1mpdf_9bcfb45435d30983f436d41c298cbb51}{rv}}
116\label{classbdm_1_1mpdf_9bcfb45435d30983f436d41c298cbb51}
117
118\begin{CompactList}\small\item\em modeled random variable \item\end{CompactList}\item 
119\hypertarget{classbdm_1_1mpdf_5a5f08950daa08b85b01ddf4e1c36288}{
120\hyperlink{classbdm_1_1RV}{RV} \hyperlink{classbdm_1_1mpdf_5a5f08950daa08b85b01ddf4e1c36288}{rvc}}
121\label{classbdm_1_1mpdf_5a5f08950daa08b85b01ddf4e1c36288}
122
123\begin{CompactList}\small\item\em random variable in condition \item\end{CompactList}\item 
124\hypertarget{classbdm_1_1mpdf_5eea43c56d38e4441bfb30270db949c0}{
125\hyperlink{classbdm_1_1epdf}{epdf} $\ast$ \hyperlink{classbdm_1_1mpdf_5eea43c56d38e4441bfb30270db949c0}{ep}}
126\label{classbdm_1_1mpdf_5eea43c56d38e4441bfb30270db949c0}
127
128\begin{CompactList}\small\item\em pointer to internal \hyperlink{classbdm_1_1epdf}{epdf} \item\end{CompactList}\end{CompactItemize}
129
130
131\subsection{Detailed Description}
132Inverse-Gamma random walk around a fixed point.
133
134Mean value, $\mu$, of this density is given by a geometric combination of {\tt rvc} and given fixed point, $p$. $l$ is the coefficient of the geometric combimation \[ \mu = \mu_{t-1} ^{l} p^{1-l}\]
135
136==== Check == vv = Standard deviation of the random walk is proportional to one $k$-th the mean. This is achieved by setting $\alpha=k$ and $\beta=k/\mu$.
137
138The standard deviation of the walk is then: $\mu/\sqrt(k)$.
139
140\subsection{Member Function Documentation}
141\hypertarget{classbdm_1_1mpdf_f0c1db6fcbb3aae2dd6123884457a367}{
142\index{bdm::migamma\_\-fix@{bdm::migamma\_\-fix}!samplecond@{samplecond}}
143\index{samplecond@{samplecond}!bdm::migamma_fix@{bdm::migamma\_\-fix}}
144\subsubsection[samplecond]{\setlength{\rightskip}{0pt plus 5cm}virtual vec bdm::mpdf::samplecond (const vec \& {\em cond})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
145\label{classbdm_1_1mpdf_f0c1db6fcbb3aae2dd6123884457a367}
146
147
148Returns a sample from the density conditioned on {\tt cond}, $x \sim epdf(rv|cond)$.
149
150\begin{Desc}
151\item[Parameters:]
152\begin{description}
153\item[{\em cond}]is numeric value of {\tt rv} \end{description}
154\end{Desc}
155
156
157References bdm::mpdf::condition(), bdm::mpdf::ep, and bdm::epdf::sample().
158
159Referenced by bdm::MPF$<$ BM\_\-T $>$::bayes(), bdm::PF::bayes(), and bdm::ArxDS::step().\hypertarget{classbdm_1_1mpdf_ee26963a637b2ea1fb1933652981e652}{
160\index{bdm::migamma\_\-fix@{bdm::migamma\_\-fix}!samplecond\_\-m@{samplecond\_\-m}}
161\index{samplecond\_\-m@{samplecond\_\-m}!bdm::migamma_fix@{bdm::migamma\_\-fix}}
162\subsubsection[samplecond\_\-m]{\setlength{\rightskip}{0pt plus 5cm}virtual mat bdm::mpdf::samplecond\_\-m (const vec \& {\em cond}, \/  vec \& {\em ll}, \/  int {\em N})\hspace{0.3cm}{\tt  \mbox{[}inline, virtual, inherited\mbox{]}}}}
163\label{classbdm_1_1mpdf_ee26963a637b2ea1fb1933652981e652}
164
165
166Returns.
167
168\begin{Desc}
169\item[Parameters:]
170\begin{description}
171\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}
172\end{Desc}
173
174
175References bdm::mpdf::condition(), bdm::RV::count(), bdm::mpdf::ep, bdm::epdf::evallog(), bdm::mpdf::rv, and bdm::epdf::sample().
176
177The documentation for this class was generated from the following file:\begin{CompactItemize}
178\item 
179\hyperlink{libEF_8h}{libEF.h}\end{CompactItemize}
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