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3<html xmlns="http://www.w3.org/1999/xhtml" xml:lang="en" lang="en">
4  <head>
5    <title>a_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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56
57    <h1><font size="-2">ToBeReviewed/STATISTICS/</font></h1>
58    <h2>a_timecorrelate.pro</h2>
59
60    <dl>
61    </dl>
62
63   
64
65
66 Same function as <a href="/Applications/itt/idl64/help/online_help/A_CORRELATE.html">A_CORRELATE</a> but accept array (until 4
67 dimension) for input and do the autocorrelation or the
68 autocovariance along the time dimension which must be the last
69 one of the input array.
70
71 This function computes the autocorrelation Px(L) or autocovariance
72 Rx(L) of a sample population X as a function of the lag (L).
73
74
75   
76
77     
78      <a name="#_a_timecorrelate"></a>
79
80      <h2>a_timecorrelate  <font size="-1" color="#006633">
81 Statistics
82</font></h2>
83
84      <p><font face="Courier"><i>result = </i>a_timecorrelate(<i><a href="#_a_timecorrelate_keyword_x">x</a>, <a href="#_a_timecorrelate_keyword_lag">lag</a></i>, <a href="#_a_timecorrelate_keyword_COVARIANCE">COVARIANCE</a>=<i>COVARIANCE</i>, <a href="#_a_timecorrelate_keyword_DOUBLE">DOUBLE</a>=<i>DOUBLE</i>, <a href="#_a_timecorrelate_keyword_NVAL">NVAL</a>=<i>NVAL</i>)</font></p>
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91   
92    <h3>Parameters</h3>
93   
94
95    <a name="#_a_timecorrelate_keyword_x"></a>
96    <h4>x&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
97      <font size="-1" color="#006633">in</font>
98     
99     
100      <font size="-1" color="#006633">required</font>
101     
102      <font size="-1" color="#006633">type:</font> <font size="-1" color="#006633"><i>array</i></font>
103     
104     
105    </h4>
106
107   
108 An array which last dimension is the time dimension so
109 size n.
110
111   
112
113    <a name="#_a_timecorrelate_keyword_lag"></a>
114    <h4>lag&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
115      <font size="-1" color="#006633">in</font>
116     
117     
118      <font size="-1" color="#006633">required</font>
119     
120      <font size="-1" color="#006633">type:</font> <font size="-1" color="#006633"><i>scalar or vector</i></font>
121     
122     
123    </h4>
124
125   
126 A scalar or n-element vector, in the interval [-(n-2), (n-2)],
127 of type integer that specifies the absolute distance(s) between
128 indexed elements of X.
129
130   
131   
132
133   
134    <h3>Keywords</h3>
135
136   
137    <a name="#_a_timecorrelate_keyword_COVARIANCE"></a>
138    <h4>COVARIANCE&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
139     
140     
141     
142     
143     
144     
145     
146     
147    </h4>
148
149   
150 If set to a non-zero value, the sample autocovariance
151 is computed.
152
153   
154    <a name="#_a_timecorrelate_keyword_DOUBLE"></a>
155    <h4>DOUBLE&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
156     
157     
158     
159     
160     
161     
162     
163     
164    </h4>
165
166   
167 If set to a non-zero value, computations are done in
168 double precision arithmetic.
169
170   
171    <a name="#_a_timecorrelate_keyword_NVAL"></a>
172    <h4>NVAL&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
173     
174     
175     
176     
177     
178     
179     
180     
181    </h4>
182
183   
184 A named variable that, on exit, contains the number of valid
185 observations (not NAN)
186
187   
188   
189
190    <h3>Examples</h3><pre>
191 Define an n-element sample population.
192 IDL> x = [3.73, 3.67, 3.77, 3.83, 4.67, 5.87, 6.70, 6.97, 6.40, 5.57]
193
194 Compute the autocorrelation of X for LAG = -3, 0, 1, 3, 4, 8
195 IDL> lag = [-3, 0, 1, 3, 4, 8]
196 IDL> result = a_correlate(x, lag)
197
198 The result should be:
199 [0.0146185, 1.00000, 0.810879, 0.0146185, -0.325279, -0.151684]
200
201    </pre><h3>Version history</h3>
202   
203    <h4>Version</h4>
204 $Id: a_timecorrelate.pro 335 2008-03-07 15:09:25Z smasson $
205
206    <h4>History</h4>
207 24/2/2000 Sebastien Masson (smasson@lodyc.jussieu.fr)
208
209 Based on the A_CORRELATE procedure of IDL
210 INTRODUCTION TO STATISTICAL TIME SERIES
211 Wayne A. Fuller
212 ISBN 0-471-28715-6
213
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230    <font size="-3"><p>&nbsp;</p></font>
231    <hr size="1" color="#CCCCCC"/>
232     
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235
236    <p><font color="gray" size="-3">&nbsp;&nbsp;Produced by IDLdoc 2.0.</font></p>
237
238  </body>
239</html>
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