ProfileLikelihoodResult

class ProfileLikelihoodResult(*args)

Distribution factory result for profile likelihood estimation.

This class provides all the results obtained after a profile likelihood estimation with respect to the parameter \vect{\theta}^{(1)}: refer to LikelihoodRatioTest().

Parameters:
distributionDistribution

Parent distribution at optimal parameter (\hat{\vect{\theta}}^{(1)}, \hat{\vect{\theta}}^{(2)}).

parameterDistributionDistribution

Asymptotic distribution of (\hat{\vect{\theta}}^{(1)}, \hat{\vect{\theta}}^{(2)}).

logLikelihoodfloat

Maximum profile log-likelihood.

profileLikelihoodFunction

Profile log-likelihood function with respect to the scalar parameter \theta^{(1)}.

parameterfloat

Estimator of \vect{\theta}^{(1)}.

Methods

drawProfileLikelihoodFunction()

Draw the profile likelihood graph with respect to the scalar parameter \theta^{(1)}.

getClassName()

Accessor to the object's name.

getConfidenceLevel()

Confidence level accessor.

getDistribution()

Accessor to the estimated distribution.

getLogLikelihood()

Likelihood value accessor.

getName()

Accessor to the object's name.

getParameter()

Estimator of \vect{\theta}^{(1)}.

getParameterConfidenceInterval()

Confidence interval accessor.

getParameterDistribution()

Accessor to the distribution of the parameter.

getProfileLikelihoodFunction()

Profile log-likelihood function accessor.

hasName()

Test if the object is named.

setConfidenceLevel(confidenceLevel)

Confidence level accessor.

setDistribution(distribution)

Accessor to the estimated distribution.

setLogLikelihood(logLikelihood)

Likelihood value accessor.

setName(name)

Accessor to the object's name.

setParameterDistribution(parameterDistribution)

Accessor to the distribution of the parameter.

__init__(*args)
drawProfileLikelihoodFunction()

Draw the profile likelihood graph with respect to the scalar parameter \theta^{(1)}.

If the parameter \theta^{(1)} is scalar, the graph of the profile log-likelihood: \theta^{(1)} \mapsto \ell_p(\theta^{(1)}) provides:

  • the estimator \hat{\theta}^{(1)} of \theta^{(1)} that maximizes the log-profile likelihood,

  • the (1-\alpha)-confidence interval of \theta^{(1)} built from the profile deviance statistics \mathcal{D}_p (\theta^{(1)}).

Returns:
graphGraph

Profile likelihood graph with respect to the scalar parameter \theta^{(1)}.

getClassName()

Accessor to the object’s name.

Returns:
class_namestr

The object class name (object.__class__.__name__).

getConfidenceLevel()

Confidence level accessor.

Returns:
levelfloat

The confidence level (1-\alpha).

getDistribution()

Accessor to the estimated distribution.

Returns:
distributionDistribution

The estimated distribution.

getLogLikelihood()

Likelihood value accessor.

Returns:
llhfloat

Log-likelihood value.

getName()

Accessor to the object’s name.

Returns:
namestr

The name of the object.

getParameter()

Estimator of \vect{\theta}^{(1)}.

Returns:
parameterfloat

Estimator of \vect{\theta}^{(1)}.

getParameterConfidenceInterval()

Confidence interval accessor.

Returns:
ciInterval

Confidence interval of \vect{\theta}^{(1)}.

getParameterDistribution()

Accessor to the distribution of the parameter.

Returns:
parameterDistributionDistribution

The distribution of the parameter.

getProfileLikelihoodFunction()

Profile log-likelihood function accessor.

Returns:
llFunction

Profile log-likelihood function with respect to \vect{\theta}^{(1)}.

hasName()

Test if the object is named.

Returns:
hasNamebool

True if the name is not empty.

setConfidenceLevel(confidenceLevel)

Confidence level accessor.

Parameters:
levelfloat

The confidence level (1-\alpha).

setDistribution(distribution)

Accessor to the estimated distribution.

Parameters:
distributionDistribution

The estimated distribution.

setLogLikelihood(logLikelihood)

Likelihood value accessor.

Parameters:
llhfloat

Log-likelihood value.

setName(name)

Accessor to the object’s name.

Parameters:
namestr

The name of the object.

setParameterDistribution(parameterDistribution)

Accessor to the distribution of the parameter.

Parameters:
parameterDistributionDistribution

The distribution of the parameter.

Examples using the class

Estimate a GEV on the Venice sea-levels data

Estimate a GEV on the Venice sea-levels data

Estimate a GEV on the Port Pirie sea-levels data

Estimate a GEV on the Port Pirie sea-levels data

Estimate a GPD on the daily rainfall data

Estimate a GPD on the daily rainfall data

Estimate a GEV on race times data

Estimate a GEV on race times data

Estimate a GEV on the Fremantle sea-levels data

Estimate a GEV on the Fremantle sea-levels data