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74	<a href="a_correlate2d.html"><<prev file</a> \| <a href="c_timecorrelate.html">next file >></a>    <a href="a_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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90
91
92	Same function as A_CORRELATE but accept array (until 4
93	dimension) for input and do the autocorrelation or the
94	autocovariance along the time dimension which must be the last
95	one of the input array.
96
97	This function computes the autocorrelation Px(L) or autocovariance
98	Rx(L) of a sample population X as a function of the lag (L).
99	</div>
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107
108	<div id="routine_summary">
109	<h2>Routine summary</h2>
110
111	<dl>
112
113	<dt><p><a href="#_timeauto_cov"><span class="result">result = </span>timeauto_cov(<span class="result">x, m, nt</span>, DOUBLE=<span class="result">DOUBLE</span>, ZERO2NAN=<span class="result">ZERO2NAN</span>)</a></p><dt>
114	<dd> </dd>
115
116	<dt><p><a href="#_a_timecorrelate"><span class="result">result = </span>a_timecorrelate(<span class="result">x, lag</span>, COVARIANCE=<span class="result">COVARIANCE</span>, DOUBLE=<span class="result">DOUBLE</span>)</a></p><dt>
117	<dd> </dd>
118
119	</dl>
120	</div>
121
122
123	<div id="routine_details">
124
125
126	<div class="routine_details" id="_timeauto_cov">
127
128	<h2><a class="top" href="#container">top</a>timeauto_cov <span class="categories">
129	Statistics
130	</span></h2>
131
132	<p class="header">
133	<span class="result">result = </span>timeauto_cov(<span class="result"><a href="#_timeauto_cov_param_x">x</a>, <a href="#_timeauto_cov_param_m">m</a>, <a href="#_timeauto_cov_param_nt">nt</a></span>, <a href="#_timeauto_cov_keyword_DOUBLE">DOUBLE</a>=<span class="result">DOUBLE</span>, <a href="#_timeauto_cov_keyword_ZERO2NAN">ZERO2NAN</a>=<span class="result">ZERO2NAN</span>)</p>
134
135	<div class="comments">
136	</div>
137
138
139
140
141	<h3>Parameters</h3>
142
143
144	<h4 id="_timeauto_cov_param_x">x
145	<span class="attr">in</span>
146
147
148	<span class="attr">required</span>
149
150	<span class="attr">type:</span> <span class="value">array</span>
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152
153	</h4>
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155	<div class="comments">
156	An array which last dimension is the time dimension so
157	size n.
158	</div>
159
160	<h4 id="_timeauto_cov_param_m">m
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169	</h4>
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171	<div class="comments">
172	</div>
173
174	<h4 id="_timeauto_cov_param_nt">nt
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183	</h4>
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185	<div class="comments">
186	</div>
187
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191
192
193	<h3>Keywords</h3>
194
195	<h4 id="_timeauto_cov_keyword_DOUBLE">DOUBLE
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204	</h4>
205
206	<div class="comments">
207	If set to a non-zero value, computations are done in
208	double precision arithmetic.
209	</div>
210
211	<h4 id="_timeauto_cov_keyword_ZERO2NAN">ZERO2NAN
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220	</h4>
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222	<div class="comments">
223	</div>
224
225
226
227	<h3>Examples</h3><div class="preformat">
228	</div>
229	<h3>Version history</h3>
230
231	<h4>Version</h4><div class="preformat">
232	$Id: a_timecorrelate.pro 262 2007-08-21 14:19:32Z pinsard $
233	</div>
234	<h4>History</h4><div class="preformat">
235	</div>
236
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252	<h3>Statistics</h3>
253	<table class="statistics">
254	<tr><td>McCabe cyclic</td><td> 8</td></tr>
255	<tr><td>McCabe essential</td><td> 1</td></tr>
256	<tr><td>McCabe modular design</td><td> 1</td></tr>
257	</table>
258
259
260	</div>
261
262
263	<div class="routine_details" id="_a_timecorrelate">
264
265	<h2><a class="top" href="#container">top</a>a_timecorrelate <span class="categories">
266	Statistics
267	</span></h2>
268
269	<p class="header">
270	<span class="result">result = </span>a_timecorrelate(<span class="result"><a href="#_a_timecorrelate_param_x">x</a>, <a href="#_a_timecorrelate_param_lag">lag</a></span>, <a href="#_a_timecorrelate_keyword_COVARIANCE">COVARIANCE</a>=<span class="result">COVARIANCE</span>, <a href="#_a_timecorrelate_keyword_DOUBLE">DOUBLE</a>=<span class="result">DOUBLE</span>)</p>
271
272	<div class="comments">
273	</div>
274
275
276
277
278	<h3>Parameters</h3>
279
280
281	<h4 id="_a_timecorrelate_param_x">x
282	<span class="attr">in</span>
283
284
285	<span class="attr">required</span>
286
287	<span class="attr">type:</span> <span class="value">array</span>
288
289
290	</h4>
291
292	<div class="comments">
293	An array which last dimension is the time dimension so
294	size n.
295	</div>
296
297	<h4 id="_a_timecorrelate_param_lag">lag
298	<span class="attr">in</span>
299
300
301	<span class="attr">required</span>
302
303	<span class="attr">type:</span> <span class="value">scalar or vector</span>
304
305
306	</h4>
307
308	<div class="comments">
309	A scalar or n-elements vector, in the interval [-(n-2),(n-2)],
310	of type integer that specifies the absolute distance(s) between
311	indexed elements of X.
312	</div>
313
314
315
316
317
318
319	<h3>Keywords</h3>
320
321	<h4 id="_a_timecorrelate_keyword_COVARIANCE">COVARIANCE
322
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330	</h4>
331
332	<div class="comments">
333	If set to a non-zero value, the sample autocovariance
334	is computed.
335	</div>
336
337	<h4 id="_a_timecorrelate_keyword_DOUBLE">DOUBLE
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339
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346	</h4>
347
348	<div class="comments">
349	If set to a non-zero value, computations are done in
350	double precision arithmetic.
351	</div>
352
353
354
355	<h3>Examples</h3><div class="preformat">
356	Define an n-elements sample population.
357	IDL> x = [3.73, 3.67, 3.77, 3.83, 4.67, 5.87, 6.70, 6.97, 6.40, 5.57]
358
359	Compute the autocorrelation of X for LAG = -3, 0, 1, 3, 4, 8
360	IDL> lag = [-3, 0, 1, 3, 4, 8]
361	IDL> result = a_correlate(x, lag)
362
363	The result should be:
364	[0.0146185, 1.00000, 0.810879, 0.0146185, -0.325279, -0.151684]
365	</div>
366	<h3>Version history</h3>
367
368	<h4>Version</h4><div class="preformat">
369	$Id: a_timecorrelate.pro 262 2007-08-21 14:19:32Z pinsard $
370	</div>
371	<h4>History</h4><div class="preformat">
372	24/2/2000 Sebastien Masson (smasson@lodyc.jussieu.fr)
373
374	Based on the A_CORRELATE procedure of IDL
375	INTRODUCTION TO STATISTICAL TIME SERIES
376	Wayne A. Fuller
377	ISBN 0-471-28715-6
378	</div>
379
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393
394
395	<h3>Statistics</h3>
396	<table class="statistics">
397	<tr><td>McCabe cyclic</td><td> 13</td></tr>
398	<tr><td>McCabe essential</td><td> 1</td></tr>
399	<tr><td>McCabe modular design</td><td> 1</td></tr>
400	</table>
401
402
403	</div>
404
405	</div>
406
407
408
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410
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