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# LogLikelihood

 LogLikelihood gives the log-likelihood function for observations , , ... from the distribution dist.
• The log-likelihood function LogLikelihood is given by , where is the probability density function at , PDF.
Get the log-likelihood function for a normal distribution:
Compute a log-likelihood for numeric data:
Plot log-likelihood contours as a function of and :
Compute the log-likelihood for multivariate data:
Get the log-likelihood function for a normal distribution:
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Compute a log-likelihood for numeric data:
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Plot log-likelihood contours as a function of and :
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Compute the log-likelihood for multivariate data:
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 Scope   (9)
Compute the log-likelihood for a continuous distribution:
Compute the log-likelihood for a discrete distribution:
Plot the log-likelihood, assuming is unknown:
Obtain the log-likelihood for a continuous multivariate distribution with unknown parameters:
Visualize the log-likelihood surface, assuming :
For a multivariate discrete distribution with known parameters:
Compute the log-likelihood for a truncated standard normal:
Plot the log-likelihood contours as a function of the truncation points:
Compute the log-likelihood for a constructed distribution:
Compute the log-likelihood for a product distribution:
Obtain the result as a sum of the independent component-wise log-likelihoods:
Compute the log-likelihood for a copula distribution:
Plot the log-likelihood as a function of the kernel parameter:
Compute the log-likelihood for a component mixture:
 Applications   (2)
Visualize the log-likelihood surface for a distribution of two parameters:
Visualize as contours of equal log-likelihood:
Show log-likelihood functions with mixed continuous and discrete parameters:
LogLikelihood is the log of Likelihood:
LogLikelihood is the sum of logs of PDF values for data:
EstimatedDistribution estimates parameters by maximizing the log-likelihood:
FindDistributionParameters gives the parameter estimates as rules:
Visualize the log-likelihood function near the optimal value:
Visualize isosurfaces for an exponential power log-likelihood:
Visualize isosurfaces for a bivariate normal log-likelihood:
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