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4	<head>
5	<title>c_timecorrelate.pro (SAXO Documentation Assistant)</title>
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50	<font size=-1><i>SAXO Documentation Assistant</i>: <a href="./../../home.html">Overview</a></font></td>
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57	<h1><font size="-2">ToBeReviewed/STATISTICS/</font></h1>
58	<h2>c_timecorrelate.pro</h2>
59
60	<dl>
61	</dl>
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66
67	This function computes the "time cross correlation" Pxy(L) or
68	the "time cross covariance" between 2 arrays (this is some
69	kind of c_correlate but for multidimenstionals arrays) as a
70	function of the lag (L).
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72
73
74	<h2>Routine summary</h2>
75
76	<dl>
77
78	<dt><a href="#_timecross_cov"><i>result = </i>timecross_cov(<i>Xd, Yd, M, nT, Ndim</i>, Double=<i>Double</i>, ZERO2NAN=<i>ZERO2NAN</i>)</a><dt>
79	<dd><font size="-1"></font></dd>
80
81	<dt><a href="#_c_timecorrelate"><i>result = </i>c_timecorrelate(<i>X, Y, Lag</i>, Covariance=<i>Covariance</i>, Double=<i>Double</i>)</a><dt>
82	<dd><font size="-1"></font></dd>
83
84	</dl>
85
86	<p> </p>
87
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90	<a name="#_timecross_cov"></a>
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92	<h2>timecross_cov <font size="-1" color="#006633">
93	Statistics
94	</font></h2>
95
96	<p><font face="Courier"><i>result = </i>timecross_cov(<i><a href="#_timecross_cov_keyword_Xd">Xd</a>, <a href="#_timecross_cov_keyword_Yd">Yd</a>, <a href="#_timecross_cov_keyword_M">M</a>, <a href="#_timecross_cov_keyword_nT">nT</a>, <a href="#_timecross_cov_keyword_Ndim">Ndim</a></i>, <a href="#_timecross_cov_keyword_Double">Double</a>=<i>Double</i>, <a href="#_timecross_cov_keyword_ZERO2NAN">ZERO2NAN</a>=<i>ZERO2NAN</i>)</font></p>
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103	<h3>Parameters</h3>
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106	<a name="#_timecross_cov_keyword_Xd"></a>
107	<h4>Xd
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116	</h4>
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123	<a name="#_timecross_cov_keyword_Yd"></a>
124	<h4>Yd
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133	</h4>
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140	<a name="#_timecross_cov_keyword_M"></a>
141	<h4>M
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150	</h4>
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157	<a name="#_timecross_cov_keyword_nT"></a>
158	<h4>nT
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167	</h4>
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174	<a name="#_timecross_cov_keyword_Ndim"></a>
175	<h4>Ndim
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184	</h4>
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193	<h3>Keywords</h3>
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196	<a name="#_timecross_cov_keyword_Double"></a>
197	<h4>Double
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206	</h4>
207
208
209	If set to a non-zero value, computations are done in
210	double precision arithmetic.
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213	<a name="#_timecross_cov_keyword_ZERO2NAN"></a>
214	<h4>ZERO2NAN
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223	</h4>
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231	<h3>Examples</h3>
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234	<h3>Version history</h3>
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236	<h4>Version</h4>
237	$Id: c_timecorrelate.pro 157 2006-08-21 09:01:50Z navarro $
238
239	<h4>History</h4>
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258	<font size="-3"><p> </p></font>
259	<hr size="1" color="#CCCCCC"/>
260
261	<a name="#_c_timecorrelate"></a>
262
263	<h2>c_timecorrelate <font size="-1" color="#006633">
264	Statistics
265	</font></h2>
266
267	<p><font face="Courier"><i>result = </i>c_timecorrelate(<i><a href="#_c_timecorrelate_keyword_X">X</a>, <a href="#_c_timecorrelate_keyword_Y">Y</a>, <a href="#_c_timecorrelate_keyword_Lag">Lag</a></i>, <a href="#_c_timecorrelate_keyword_Covariance">Covariance</a>=<i>Covariance</i>, <a href="#_c_timecorrelate_keyword_Double">Double</a>=<i>Double</i>)</font></p>
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274	<h3>Parameters</h3>
275
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277	<a name="#_c_timecorrelate_keyword_X"></a>
278	<h4>X
279	<font size="-1" color="#006633">in</font>
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282	<font size="-1" color="#006633">required</font>
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284	<font size="-1" color="#006633">type:</font> <font size="-1" color="#006633"><i>array</i></font>
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287	</h4>
288
289
290	An Array which last dimension is the time dimension of
291	size n, float or double.
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295	<a name="#_c_timecorrelate_keyword_Y"></a>
296	<h4>Y
297	<font size="-1" color="#006633">in</font>
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300	<font size="-1" color="#006633">required</font>
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302	<font size="-1" color="#006633">type:</font> <font size="-1" color="#006633"><i>array</i></font>
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305	</h4>
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308	An Array which last dimension is the time dimension of
309	size n, float or double.
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313	<a name="#_c_timecorrelate_keyword_Lag"></a>
314	<h4>Lag
315	<font size="-1" color="#006633">in</font>
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318	<font size="-1" color="#006633">required</font>
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320	<font size="-1" color="#006633">type:</font> <font size="-1" color="#006633"><i>scalar or vector</i></font>
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323	</h4>
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326	A scalar or n-element vector, in the interval [-(n-2), (n-2)],
327	of type integer that specifies the absolute distance(s) between
328	indexed elements of X.
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334	<h3>Keywords</h3>
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337	<a name="#_c_timecorrelate_keyword_Covariance"></a>
338	<h4>Covariance
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347	</h4>
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350	If set to a non-zero value, the sample cross
351	covariance is computed.
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354	<a name="#_c_timecorrelate_keyword_Double"></a>
355	<h4>Double
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364	</h4>
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367	If set to a non-zero value, computations are done in
368	double precision arithmetic.
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373	<h3>Examples</h3>
374
375	Define two n-element sample populations.
376	x = [3.73, 3.67, 3.77, 3.83, 4.67, 5.87, 6.70, 6.97, 6.40, 5.57]
377	y = [2.31, 2.76, 3.02, 3.13, 3.72, 3.88, 3.97, 4.39, 4.34, 3.95]
378
379	Compute the cross correlation of X and Y for LAG = -5, 0, 1, 5, 6, 7
380	lag = [-5, 0, 1, 5, 6, 7]
381	result = c_timecorrelate(x, y, lag)
382
383	The result should be:
384	[-0.428246, 0.914755, 0.674547, -0.405140, -0.403100, -0.339685]
385
386	<h3>Version history</h3>
387
388	<h4>Version</h4>
389	$Id: c_timecorrelate.pro 157 2006-08-21 09:01:50Z navarro $
390
391	<h4>History</h4>
392	- 01/03/2000 Sebastien Masson (smasson@lodyc.jussieu.fr)
393	Based on the C_CORRELATE procedure of IDL
394	- August 2003 Sebastien Masson
395	update according to the update made in C_CORRELATE by
396	W. Biagiotti and available in IDL 5.5
397
398	INTRODUCTION TO STATISTICAL TIME SERIES
399	Wayne A. Fuller
400	ISBN 0-471-28715-6
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418	<font size="-3"><p> </p></font>
419	<hr size="1" color="#CCCCCC"/>
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424	<p><font color="gray" size="-3">  Produced by IDLdoc 2.0 on Tue Aug 29 14:50:29 2006.</font></p>
425
426	</body>
427	</html>

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