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        <title>@ND - lab:projects:19time_delay_embedding_dfa</title>
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       <dc:date>2026-05-13T16:15:12+00:00</dc:date>
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        <dc:date>2016-01-24T14:48:26+00:00</dc:date>
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        <title>index</title>
        <link>https://nd.psychstat.org/lab/projects/19time_delay_embedding_dfa/index</link>
        <description>Time delay embedding for DFA

	*  R code to process results from mkfm6
	*  Non-stationary data

Programs

	*  Mplus input file for continuous data 
TITLE:        categorical DFM

DATA:         FILE = data1.txt;

VARIABLE:     NAMES = y11 y12 y13 y14 y15 y16 y17 y18 
                      y21 y22 y23 y24 y25 y26 y27 y28; 
              USEVARIABLES = y11 y12 y13 y14 y15 y16 y17 y18 
                      y21 y22 y23 y24 y25 y26 y27 y28;

MODEL:         !Lag 0
               f11 by y11 @ 1;
      …</description>
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        <dc:date>2016-01-24T14:48:26+00:00</dc:date>
        <dc:creator>Anonymous (anonymous@undisclosed.example.com)</dc:creator>
        <title>r_code_to_process_results_from_mkfm6</title>
        <link>https://nd.psychstat.org/lab/projects/19time_delay_embedding_dfa/r_code_to_process_results_from_mkfm6</link>
        <description>R code related to Kalman filter methods

	*  Process results


## process results
allse&lt;-NULL
allpar&lt;-NULL
SS&lt;-200
for (i in 1:500){
	filename&lt;-paste(&#039;out&#039;, SS, i, &#039;.txt&#039;, sep=&#039;&#039;)
	if (file.exists(filename)){
		temp&lt;-readLines(filename)
		temp&lt;-temp[substr(temp, 1, 4)==&#039; nr &#039;]
		temp&lt;-substr(temp, 15, 71)
		if (length(temp)&gt;0){
			temp&lt;-read.table(textConnection(temp))
			allse&lt;-rbind(allse, temp$V5)
			allpar&lt;-rbind(allpar, temp$V1)
		}
	}
}

index&lt;-(apply(allse, 1, min) &gt; 0) &amp; (apply(allse, 1,…</description>
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