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| 25 | <div id="navbar_title"> |
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| 26 | <h1>SAXO Documentation</h1> |
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| 32 | <table cellspacing="0"> |
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| 35 | <td><a href="./../../overview.html" title="Overview of library">Overview</a></td> |
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| 39 | <td >Directory</td> |
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| 43 | <td><a href="./../../idldoc-categories.html" title="Browse library by category">Categories</a></td> |
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| 47 | <td><a href="./../../idldoc-index.html" title="Index of files, routines, and parameters">Index</a></td> |
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| 51 | <td><a href="./../../search-page.html" title="Search library">Search</a></td> |
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| 54 | <td id="selected">File</td> |
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| 56 | |
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| 57 | <td><a href="../../../../ToBeReviewed/STATISTICS//c_timecorrelate.pro" title="Source code of a file">Source</a></td> |
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| 61 | <td><a href="./../../idldoc-help.html" title="Help on IDLdoc">Help</a></td> |
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| 64 | <td >Etc</td> |
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| 70 | </div> |
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| 72 | <div id="secondary_navbar"> |
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| 73 | |
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| 74 | <a href="a_timecorrelate.html"><<prev file</a> | next file >> <a href="c_timecorrelate.html" target="_TOP">view single page</a> | <a href="./../../index.html" target="_TOP">view frames</a> summary: fields | <a href="#routine_summary">routine</a> details: <a href="#routine_details">routine</a> |
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| 75 | |
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| 76 | </div> |
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| 77 | |
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| 78 | |
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| 79 | <div id="container"> |
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| 80 | |
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| 81 | <h1 class="directory"><a href="directory-overview.html">ToBeReviewed/STATISTICS/</a></h1> |
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| 82 | <h2 class="pro_file">c_timecorrelate.pro</h2> |
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| 83 | |
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| 84 | <div id="file_attr"> |
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| 85 | <dl> |
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| 86 | </dl> |
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| 87 | </div> |
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| 88 | |
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| 89 | <div id="file_comments"> |
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| 90 | |
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| 91 | |
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| 92 | |
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| 93 | This function computes the "time cross correlation" Pxy(L) or |
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| 94 | the "time cross covariance" between 2 arrays (this is some |
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| 95 | kind of c_correlate but for multidimenstionals arrays) as a |
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| 96 | function of the lag (L). |
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| 97 | </div> |
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| 98 | |
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| 99 | |
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| 100 | |
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| 101 | |
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| 102 | |
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| 103 | |
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| 104 | |
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| 105 | |
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| 106 | <div id="routine_summary"> |
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| 107 | <h2>Routine summary</h2> |
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| 108 | |
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| 109 | <dl> |
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| 110 | |
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| 111 | <dt><p><a href="#_timecross_cov"><span class="result">result = </span>timecross_cov(<span class="result">Xd, Yd, M, nT, Ndim</span>, Double=<span class="result">Double</span>, ZERO2NAN=<span class="result">ZERO2NAN</span>)</a></p><dt> |
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| 112 | <dd></dd> |
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| 113 | |
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| 114 | <dt><p><a href="#_c_timecorrelate"><span class="result">result = </span>c_timecorrelate(<span class="result">X, Y, Lag</span>, Covariance=<span class="result">Covariance</span>, Double=<span class="result">Double</span>)</a></p><dt> |
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| 115 | <dd></dd> |
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| 116 | |
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| 117 | </dl> |
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| 118 | </div> |
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| 119 | |
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| 120 | |
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| 121 | <div id="routine_details"> |
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| 122 | |
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| 123 | |
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| 124 | <div class="routine_details" id="_timecross_cov"> |
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| 125 | |
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| 126 | <h2><a class="top" href="#container">top</a>timecross_cov <span class="categories"> |
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| 127 | Statistics |
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| 128 | </span></h2> |
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| 129 | |
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| 130 | <p class="header"> |
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| 131 | <span class="result">result = </span>timecross_cov(<span class="result"><a href="#_timecross_cov_param_Xd">Xd</a>, <a href="#_timecross_cov_param_Yd">Yd</a>, <a href="#_timecross_cov_param_M">M</a>, <a href="#_timecross_cov_param_nT">nT</a>, <a href="#_timecross_cov_param_Ndim">Ndim</a></span>, <a href="#_timecross_cov_keyword_Double">Double</a>=<span class="result">Double</span>, <a href="#_timecross_cov_keyword_ZERO2NAN">ZERO2NAN</a>=<span class="result">ZERO2NAN</span>)</p> |
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| 132 | |
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| 133 | <div class="comments"></div> |
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| 134 | |
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| 135 | |
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| 136 | |
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| 137 | |
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| 138 | <h3>Parameters</h3> |
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| 139 | |
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| 140 | |
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| 141 | <h4 id="_timecross_cov_param_Xd">Xd |
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| 142 | |
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| 143 | |
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| 144 | |
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| 145 | |
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| 146 | |
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| 147 | |
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| 149 | |
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| 150 | </h4> |
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| 151 | |
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| 152 | <div class="comments"> |
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| 153 | |
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| 154 | </div> |
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| 155 | |
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| 156 | <h4 id="_timecross_cov_param_Yd">Yd |
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| 157 | |
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| 158 | |
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| 159 | |
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| 164 | |
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| 165 | </h4> |
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| 166 | |
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| 167 | <div class="comments"> |
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| 168 | |
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| 169 | </div> |
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| 170 | |
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| 171 | <h4 id="_timecross_cov_param_M">M |
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| 172 | |
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| 173 | |
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| 174 | |
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| 175 | |
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| 176 | |
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| 177 | |
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| 178 | |
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| 179 | |
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| 180 | </h4> |
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| 181 | |
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| 182 | <div class="comments"> |
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| 183 | |
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| 184 | </div> |
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| 185 | |
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| 186 | <h4 id="_timecross_cov_param_nT">nT |
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| 187 | |
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| 188 | |
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| 189 | |
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| 190 | |
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| 191 | |
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| 192 | |
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| 193 | |
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| 194 | |
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| 195 | </h4> |
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| 196 | |
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| 197 | <div class="comments"> |
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| 198 | |
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| 199 | </div> |
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| 200 | |
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| 201 | <h4 id="_timecross_cov_param_Ndim">Ndim |
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| 202 | |
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| 203 | |
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| 204 | |
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| 205 | |
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| 206 | |
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| 207 | |
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| 208 | |
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| 209 | |
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| 210 | </h4> |
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| 211 | |
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| 212 | <div class="comments"> |
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| 213 | |
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| 214 | </div> |
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| 215 | |
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| 216 | |
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| 217 | |
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| 218 | |
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| 219 | |
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| 220 | |
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| 221 | <h3>Keywords</h3> |
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| 222 | |
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| 223 | <h4 id="_timecross_cov_keyword_Double">Double |
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| 224 | |
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| 225 | |
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| 226 | |
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| 227 | |
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| 228 | |
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| 229 | |
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| 230 | |
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| 231 | |
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| 232 | </h4> |
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| 233 | |
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| 234 | <div class="comments"> |
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| 235 | If set to a non-zero value, computations are done in |
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| 236 | double precision arithmetic. |
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| 237 | </div> |
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| 238 | |
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| 239 | <h4 id="_timecross_cov_keyword_ZERO2NAN">ZERO2NAN |
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| 240 | |
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| 241 | |
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| 242 | |
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| 243 | |
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| 244 | |
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| 245 | |
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| 246 | |
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| 247 | |
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| 248 | </h4> |
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| 249 | |
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| 250 | <div class="comments"> |
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| 251 | |
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| 252 | </div> |
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| 253 | |
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| 254 | |
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| 255 | |
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| 256 | <h3>Examples</h3><div class="preformat"> |
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| 257 | |
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| 258 | </div> |
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| 259 | <h3>Version history</h3> |
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| 260 | |
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| 261 | <h4>Version</h4><div class="preformat"> |
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| 262 | $Id: c_timecorrelate.pro 163 2006-08-29 12:59:46Z navarro $ |
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| 263 | </div> |
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| 264 | <h4>History</h4><div class="preformat"> |
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| 265 | |
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| 266 | </div> |
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| 267 | |
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| 268 | |
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| 269 | |
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| 278 | |
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| 279 | |
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| 280 | |
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| 281 | |
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| 282 | |
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| 283 | <h3>Statistics</h3> |
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| 284 | <table class="statistics"> |
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| 285 | <tr><td>McCabe cyclic</td><td> 7</td></tr> |
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| 286 | <tr><td>McCabe essential</td><td> 1</td></tr> |
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| 287 | <tr><td>McCabe modular design</td><td> 1</td></tr> |
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| 288 | </table> |
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| 289 | |
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| 290 | |
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| 291 | </div> |
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| 292 | |
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| 293 | |
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| 294 | <div class="routine_details" id="_c_timecorrelate"> |
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| 295 | |
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| 296 | <h2><a class="top" href="#container">top</a>c_timecorrelate <span class="categories"> |
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| 297 | Statistics |
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| 298 | </span></h2> |
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| 299 | |
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| 300 | <p class="header"> |
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| 301 | <span class="result">result = </span>c_timecorrelate(<span class="result"><a href="#_c_timecorrelate_param_X">X</a>, <a href="#_c_timecorrelate_param_Y">Y</a>, <a href="#_c_timecorrelate_param_Lag">Lag</a></span>, <a href="#_c_timecorrelate_keyword_Covariance">Covariance</a>=<span class="result">Covariance</span>, <a href="#_c_timecorrelate_keyword_Double">Double</a>=<span class="result">Double</span>)</p> |
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| 302 | |
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| 303 | <div class="comments"></div> |
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| 304 | |
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| 305 | |
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| 306 | |
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| 307 | |
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| 308 | <h3>Parameters</h3> |
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| 309 | |
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| 310 | |
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| 311 | <h4 id="_c_timecorrelate_param_X">X |
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| 312 | <span class="attr">in</span> |
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| 313 | |
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| 314 | |
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| 315 | <span class="attr">required</span> |
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| 316 | |
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| 317 | <span class="attr">type:</span> <span class="value">array</span> |
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| 318 | |
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| 319 | |
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| 320 | </h4> |
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| 321 | |
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| 322 | <div class="comments"> |
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| 323 | An Array which last dimension is the time dimension of |
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| 324 | size n, float or double. |
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| 325 | </div> |
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| 326 | |
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| 327 | <h4 id="_c_timecorrelate_param_Y">Y |
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| 328 | <span class="attr">in</span> |
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| 329 | |
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| 330 | |
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| 331 | <span class="attr">required</span> |
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| 332 | |
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| 333 | <span class="attr">type:</span> <span class="value">array</span> |
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| 334 | |
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| 335 | |
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| 336 | </h4> |
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| 337 | |
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| 338 | <div class="comments"> |
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| 339 | An Array which last dimension is the time dimension of |
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| 340 | size n, float or double. |
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| 341 | </div> |
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| 342 | |
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| 343 | <h4 id="_c_timecorrelate_param_Lag">Lag |
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| 344 | <span class="attr">in</span> |
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| 345 | |
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| 346 | |
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| 347 | <span class="attr">required</span> |
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| 348 | |
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| 349 | <span class="attr">type:</span> <span class="value">scalar or vector</span> |
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| 350 | |
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| 351 | |
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| 352 | </h4> |
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| 353 | |
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| 354 | <div class="comments"> |
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| 355 | A scalar or n-element vector, in the interval [-(n-2), (n-2)], |
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| 356 | of type integer that specifies the absolute distance(s) between |
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| 357 | indexed elements of X. |
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| 358 | </div> |
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| 359 | |
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| 360 | |
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| 361 | |
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| 362 | |
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| 363 | |
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| 364 | |
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| 365 | <h3>Keywords</h3> |
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| 366 | |
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| 367 | <h4 id="_c_timecorrelate_keyword_Covariance">Covariance |
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| 368 | |
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| 369 | |
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| 370 | |
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| 371 | |
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| 372 | |
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| 373 | |
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| 374 | |
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| 375 | |
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| 376 | </h4> |
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| 377 | |
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| 378 | <div class="comments"> |
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| 379 | If set to a non-zero value, the sample cross |
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| 380 | covariance is computed. |
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| 381 | </div> |
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| 382 | |
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| 383 | <h4 id="_c_timecorrelate_keyword_Double">Double |
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| 384 | |
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| 385 | |
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| 386 | |
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| 387 | |
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| 388 | |
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| 389 | |
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| 390 | |
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| 391 | |
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| 392 | </h4> |
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| 393 | |
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| 394 | <div class="comments"> |
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| 395 | If set to a non-zero value, computations are done in |
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| 396 | double precision arithmetic. |
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| 397 | </div> |
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| 398 | |
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| 399 | |
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| 400 | |
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| 401 | <h3>Examples</h3><div class="preformat"> |
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| 402 | |
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| 403 | Define two n-element sample populations. |
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| 404 | x = [3.73, 3.67, 3.77, 3.83, 4.67, 5.87, 6.70, 6.97, 6.40, 5.57] |
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| 405 | y = [2.31, 2.76, 3.02, 3.13, 3.72, 3.88, 3.97, 4.39, 4.34, 3.95] |
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| 406 | |
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| 407 | Compute the cross correlation of X and Y for LAG = -5, 0, 1, 5, 6, 7 |
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| 408 | lag = [-5, 0, 1, 5, 6, 7] |
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| 409 | result = c_timecorrelate(x, y, lag) |
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| 410 | |
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| 411 | The result should be: |
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| 412 | [-0.428246, 0.914755, 0.674547, -0.405140, -0.403100, -0.339685] |
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| 413 | </div> |
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| 414 | <h3>Version history</h3> |
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| 415 | |
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| 416 | <h4>Version</h4><div class="preformat"> |
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| 417 | $Id: c_timecorrelate.pro 163 2006-08-29 12:59:46Z navarro $ |
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| 418 | </div> |
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| 419 | <h4>History</h4><div class="preformat"> |
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| 420 | - 01/03/2000 Sebastien Masson (smasson@lodyc.jussieu.fr) |
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| 421 | Based on the C_CORRELATE procedure of IDL |
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| 422 | - August 2003 Sebastien Masson |
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| 423 | update according to the update made in C_CORRELATE by |
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| 424 | W. Biagiotti and available in IDL 5.5 |
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| 425 | |
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| 426 | INTRODUCTION TO STATISTICAL TIME SERIES |
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| 427 | Wayne A. Fuller |
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| 428 | ISBN 0-471-28715-6 |
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| 429 | </div> |
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| 430 | |
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| 444 | |
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| 445 | |
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| 446 | <h3>Statistics</h3> |
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| 447 | <table class="statistics"> |
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| 448 | <tr><td>McCabe cyclic</td><td> 33</td></tr> |
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| 449 | <tr><td>McCabe essential</td><td> 1</td></tr> |
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| 450 | <tr><td>McCabe modular design</td><td> 1</td></tr> |
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| 451 | </table> |
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| 452 | |
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| 453 | |
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| 454 | </div> |
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| 455 | |
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| 456 | </div> |
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| 457 | |
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| 458 | |
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| 459 | |
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| 460 | <div id="tagline">Produced by IDLdoc 2.0.</div> |
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| 461 | |
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| 462 | </div> |
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| 463 | |
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| 464 | </body> |
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| 465 | </html> |
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