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In probability theory, a log-t distribution or log-Student t distribution is a probability distribution of a random variable whose logarithm is distributed in accordance with a Student's t-distribution. If X is a random variable with a Student's t-distribution, then Y = exp(X) has a log-t distribution; likewise, if Y has a log-t distribution, then X = log(Y) has a Student's t-distribution.

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dbo:abstract
  • In probability theory, a log-t distribution or log-Student t distribution is a probability distribution of a random variable whose logarithm is distributed in accordance with a Student's t-distribution. If X is a random variable with a Student's t-distribution, then Y = exp(X) has a log-t distribution; likewise, if Y has a log-t distribution, then X = log(Y) has a Student's t-distribution. (en)
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  • 300 (xsd:integer)
dbp:kurtosis
  • does not exist (en)
dbp:mean
  • infinite (en)
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  • does not exist (en)
dbp:name
  • Log-t or Log-Student t (en)
dbp:parameters
  • , degrees of freedom parameter (en)
  • , location parameter (en)
  • , scale parameter (en)
dbp:skewness
  • does not exist (en)
dbp:type
  • density (en)
dbp:variance
  • infinite (en)
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  • In probability theory, a log-t distribution or log-Student t distribution is a probability distribution of a random variable whose logarithm is distributed in accordance with a Student's t-distribution. If X is a random variable with a Student's t-distribution, then Y = exp(X) has a log-t distribution; likewise, if Y has a log-t distribution, then X = log(Y) has a Student's t-distribution. (en)
rdfs:label
  • Log-t distribution (en)
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