1 | \hypertarget{classmigamma__fix}{ |
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2 | \section{migamma\_\-fix Class Reference} |
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3 | \label{classmigamma__fix}\index{migamma\_\-fix@{migamma\_\-fix}} |
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4 | } |
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5 | Inverse-Gamma random walk around a fixed point. |
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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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10 | Inheritance diagram for migamma\_\-fix:\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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14 | \includegraphics[width=62pt]{classmigamma__fix__inherit__graph} |
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15 | \end{center} |
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16 | \end{figure} |
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17 | Collaboration diagram for migamma\_\-fix:\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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21 | \includegraphics[height=400pt]{classmigamma__fix__coll__graph} |
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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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27 | \hypertarget{classmigamma__fix_85ff4fae4d3faefed060c515f255207e}{ |
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28 | \hyperlink{classmigamma__fix_85ff4fae4d3faefed060c515f255207e}{migamma\_\-fix} (const \hyperlink{classRV}{RV} \&\hyperlink{classmpdf_f6687c07ff07d47812dd565368ca59eb}{rv}, const \hyperlink{classRV}{RV} \&\hyperlink{classmpdf_acb7dda792b3cd5576f39fa3129abbab}{rvc})} |
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29 | \label{classmigamma__fix_85ff4fae4d3faefed060c515f255207e} |
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30 | |
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31 | \begin{CompactList}\small\item\em Constructor. \item\end{CompactList}\item |
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32 | \hypertarget{classmigamma__fix_6266e14eb59fe36f494cfb5934a8e987}{ |
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33 | void \hyperlink{classmigamma__fix_6266e14eb59fe36f494cfb5934a8e987}{set\_\-parameters} (double k0, vec ref0, double l0)} |
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34 | \label{classmigamma__fix_6266e14eb59fe36f494cfb5934a8e987} |
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35 | |
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36 | \begin{CompactList}\small\item\em Set value of {\tt k}. \item\end{CompactList}\item |
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37 | \hypertarget{classmigamma__fix_a69739eebfe05835db11bc3544cec6a1}{ |
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38 | void \hyperlink{classmigamma__fix_a69739eebfe05835db11bc3544cec6a1}{condition} (const vec \&val)} |
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39 | \label{classmigamma__fix_a69739eebfe05835db11bc3544cec6a1} |
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40 | |
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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 | \hypertarget{classmigamma_6cf801c0319ffcfc6317e9f2ecef4cf8}{ |
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43 | void \hyperlink{classmigamma_6cf801c0319ffcfc6317e9f2ecef4cf8}{set\_\-parameters} (double k0)} |
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44 | \label{classmigamma_6cf801c0319ffcfc6317e9f2ecef4cf8} |
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45 | |
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46 | \begin{CompactList}\small\item\em Set value of {\tt k}. \item\end{CompactList}\item |
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47 | virtual vec \hyperlink{classmpdf_3f172b79ec4a5ebc87898a5381141f1b}{samplecond} (const vec \&cond, double \&ll) |
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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 |
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49 | virtual mat \hyperlink{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{samplecond\_\-m} (const vec \&cond, vec \&ll, int N) |
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50 | \begin{CompactList}\small\item\em Returns. \item\end{CompactList}\item |
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51 | \hypertarget{classmpdf_2ef8a6374029d990a678782f6decebbe}{ |
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52 | virtual double \hyperlink{classmpdf_2ef8a6374029d990a678782f6decebbe}{evallogcond} (const vec \&dt, const vec \&cond)} |
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53 | \label{classmpdf_2ef8a6374029d990a678782f6decebbe} |
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54 | |
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55 | \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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56 | \hypertarget{classmpdf_95fcff214848f66f1b489459370573fa}{ |
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57 | virtual vec \hyperlink{classmpdf_95fcff214848f66f1b489459370573fa}{evallogcond\_\-m} (const mat \&Dt, const vec \&cond)} |
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58 | \label{classmpdf_95fcff214848f66f1b489459370573fa} |
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59 | |
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60 | \begin{CompactList}\small\item\em Matrix version of evallogcond. \item\end{CompactList}\item |
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61 | \hypertarget{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{ |
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62 | \hyperlink{classRV}{RV} \hyperlink{classmpdf_15ef062183b1ccdf794732d5fa0b77cd}{\_\-rvc} () const } |
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63 | \label{classmpdf_15ef062183b1ccdf794732d5fa0b77cd} |
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64 | |
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65 | \begin{CompactList}\small\item\em access function \item\end{CompactList}\item |
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66 | \hypertarget{classmpdf_71256ffb5fbd08f41d650e606a5bd585}{ |
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67 | \hyperlink{classRV}{RV} \hyperlink{classmpdf_71256ffb5fbd08f41d650e606a5bd585}{\_\-rv} () const } |
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68 | \label{classmpdf_71256ffb5fbd08f41d650e606a5bd585} |
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69 | |
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70 | \begin{CompactList}\small\item\em access function \item\end{CompactList}\item |
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71 | \hypertarget{classmpdf_e17780ee5b2cfe05922a6c56af1462f8}{ |
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72 | \hyperlink{classepdf}{epdf} \& \hyperlink{classmpdf_e17780ee5b2cfe05922a6c56af1462f8}{\_\-epdf} ()} |
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73 | \label{classmpdf_e17780ee5b2cfe05922a6c56af1462f8} |
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74 | |
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75 | \begin{CompactList}\small\item\em access function \item\end{CompactList}\item |
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76 | \hypertarget{classmpdf_75ded3b0f657cd7da6590691a810963c}{ |
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77 | \hyperlink{classepdf}{epdf} $\ast$ \hyperlink{classmpdf_75ded3b0f657cd7da6590691a810963c}{\_\-e} ()} |
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78 | \label{classmpdf_75ded3b0f657cd7da6590691a810963c} |
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79 | |
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80 | \begin{CompactList}\small\item\em access function \item\end{CompactList}\end{CompactItemize} |
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81 | \subsection*{Protected Attributes} |
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82 | \begin{CompactItemize} |
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83 | \item |
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84 | \hypertarget{classmigamma__fix_13e0b9e3faf370a5ac24f2d8534047ec}{ |
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85 | double \hyperlink{classmigamma__fix_13e0b9e3faf370a5ac24f2d8534047ec}{l}} |
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86 | \label{classmigamma__fix_13e0b9e3faf370a5ac24f2d8534047ec} |
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87 | |
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88 | \begin{CompactList}\small\item\em parameter l \item\end{CompactList}\item |
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89 | \hypertarget{classmigamma__fix_7d0576daba2a1de5dc040dbfbd7dd446}{ |
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90 | vec \hyperlink{classmigamma__fix_7d0576daba2a1de5dc040dbfbd7dd446}{refl}} |
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91 | \label{classmigamma__fix_7d0576daba2a1de5dc040dbfbd7dd446} |
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92 | |
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93 | \begin{CompactList}\small\item\em reference vector \item\end{CompactList}\item |
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94 | \hypertarget{classmigamma_74712a98f587efdf35da540f7f5b5d0d}{ |
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95 | \hyperlink{classeigamma}{eigamma} \hyperlink{classmigamma_74712a98f587efdf35da540f7f5b5d0d}{epdf}} |
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96 | \label{classmigamma_74712a98f587efdf35da540f7f5b5d0d} |
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97 | |
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98 | \begin{CompactList}\small\item\em Internal \hyperlink{classepdf}{epdf} that arise by conditioning on {\tt rvc}. \item\end{CompactList}\item |
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99 | \hypertarget{classmigamma_8425bc642c6f7876b578e666c841fa9c}{ |
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100 | double \hyperlink{classmigamma_8425bc642c6f7876b578e666c841fa9c}{k}} |
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101 | \label{classmigamma_8425bc642c6f7876b578e666c841fa9c} |
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102 | |
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103 | \begin{CompactList}\small\item\em Constant $k$. \item\end{CompactList}\item |
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104 | \hypertarget{classmigamma_92c2e81705d8edb58181b61af75574e0}{ |
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105 | vec $\ast$ \hyperlink{classmigamma_92c2e81705d8edb58181b61af75574e0}{\_\-beta}} |
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106 | \label{classmigamma_92c2e81705d8edb58181b61af75574e0} |
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107 | |
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108 | \begin{CompactList}\small\item\em cache of epdf.beta \item\end{CompactList}\item |
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109 | \hypertarget{classmigamma_fb9bf89eb2c15fc267c97eef2218ebfa}{ |
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110 | vec $\ast$ \hyperlink{classmigamma_fb9bf89eb2c15fc267c97eef2218ebfa}{\_\-alpha}} |
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111 | \label{classmigamma_fb9bf89eb2c15fc267c97eef2218ebfa} |
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112 | |
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113 | \begin{CompactList}\small\item\em chaceh of epdf.alpha \item\end{CompactList}\item |
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114 | \hypertarget{classmpdf_f6687c07ff07d47812dd565368ca59eb}{ |
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115 | \hyperlink{classRV}{RV} \hyperlink{classmpdf_f6687c07ff07d47812dd565368ca59eb}{rv}} |
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116 | \label{classmpdf_f6687c07ff07d47812dd565368ca59eb} |
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117 | |
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118 | \begin{CompactList}\small\item\em modeled random variable \item\end{CompactList}\item |
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119 | \hypertarget{classmpdf_acb7dda792b3cd5576f39fa3129abbab}{ |
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120 | \hyperlink{classRV}{RV} \hyperlink{classmpdf_acb7dda792b3cd5576f39fa3129abbab}{rvc}} |
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121 | \label{classmpdf_acb7dda792b3cd5576f39fa3129abbab} |
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122 | |
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123 | \begin{CompactList}\small\item\em random variable in condition \item\end{CompactList}\item |
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124 | \hypertarget{classmpdf_7aa894208a32f3487827df6d5054424c}{ |
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125 | \hyperlink{classepdf}{epdf} $\ast$ \hyperlink{classmpdf_7aa894208a32f3487827df6d5054424c}{ep}} |
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126 | \label{classmpdf_7aa894208a32f3487827df6d5054424c} |
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127 | |
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128 | \begin{CompactList}\small\item\em pointer to internal \hyperlink{classepdf}{epdf} \item\end{CompactList}\end{CompactItemize} |
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129 | |
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130 | |
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131 | \subsection{Detailed Description} |
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132 | Inverse-Gamma random walk around a fixed point. |
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133 | |
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134 | Mean 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 \[ \mu = \mu_{t-1} ^{l} p^{1-l}\] |
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135 | |
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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 $\beta=k/\mu$. |
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137 | |
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138 | The standard deviation of the walk is then: $\mu/\sqrt(k)$. |
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139 | |
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140 | \subsection{Member Function Documentation} |
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141 | \hypertarget{classmpdf_3f172b79ec4a5ebc87898a5381141f1b}{ |
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142 | \index{migamma\_\-fix@{migamma\_\-fix}!samplecond@{samplecond}} |
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143 | \index{samplecond@{samplecond}!migamma_fix@{migamma\_\-fix}} |
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144 | \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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145 | \label{classmpdf_3f172b79ec4a5ebc87898a5381141f1b} |
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146 | |
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147 | |
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148 | Returns a sample from the density conditioned on {\tt cond}, $x \sim epdf(rv|cond)$. |
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149 | |
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150 | \begin{Desc} |
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151 | \item[Parameters:] |
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152 | \begin{description} |
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153 | \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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154 | \end{Desc} |
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155 | |
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156 | |
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157 | Reimplemented in \hyperlink{classmprod_a48887eb8738a9e5550bfc38eb8e9d68}{mprod}. |
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158 | |
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159 | References mpdf::condition(), mpdf::ep, epdf::evallog(), and epdf::sample(). |
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160 | |
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161 | Referenced by MPF$<$ BM\_\-T $>$::bayes(), and PF::bayes().\hypertarget{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5}{ |
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162 | \index{migamma\_\-fix@{migamma\_\-fix}!samplecond\_\-m@{samplecond\_\-m}} |
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163 | \index{samplecond\_\-m@{samplecond\_\-m}!migamma_fix@{migamma\_\-fix}} |
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164 | \subsubsection[samplecond\_\-m]{\setlength{\rightskip}{0pt plus 5cm}virtual mat mpdf::samplecond\_\-m (const vec \& {\em cond}, \/ vec \& {\em ll}, \/ int {\em N})\hspace{0.3cm}{\tt \mbox{[}inline, virtual, inherited\mbox{]}}}} |
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165 | \label{classmpdf_b1dae6171ee39a6a05976c7b1007a3c5} |
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166 | |
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167 | |
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168 | Returns. |
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169 | |
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170 | \begin{Desc} |
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171 | \item[Parameters:] |
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172 | \begin{description} |
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173 | \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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174 | \end{Desc} |
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175 | |
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176 | |
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177 | References mpdf::condition(), RV::count(), mpdf::ep, epdf::evallog(), mpdf::rv, and epdf::sample(). |
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178 | |
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179 | The documentation for this class was generated from the following file:\begin{CompactItemize} |
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180 | \item |
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181 | work/git/mixpp/bdm/stat/\hyperlink{libEF_8h}{libEF.h}\end{CompactItemize} |
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