A high-speed algorithm for computing conditional probabilities of substrings of sequentially observed data
| Autor: | Samuel L. Moise, Lloyd M. Nirenberg, Jochen Haber |
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| Rok vydání: | 1973 |
| Předmět: |
Theoretical computer science
Computer science Computation Probabilistic logic Conditional probability Experimental and Cognitive Psychology Substring Arts and Humanities (miscellaneous) Developmental and Educational Psychology Sequential data Psychology (miscellaneous) Interpersonal interaction Algorithm General Psychology |
| Zdroj: | Behavior Research Methods & Instrumentation. 5:291-294 |
| ISSN: | 1554-3528 1554-351X |
| DOI: | 10.3758/bf03200188 |
| Popis: | An algorithm is described that computes relative frequencies of occurrence of all arbitrarily long substrings of sequential data, such as are obtained from experiments in learning/memory and verbal interaction. The algorithm offers high speed and provides systematization for the computation of empirical conditional probabilities. Use of this algorithm allows application of probabilistic and information theoretic disciplines to reveal dependencies between events separated arbitrarily in time. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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