miscmodels.tmodel.TLinearModel()
statsmodels.miscmodels.tmodel.TLinearModel
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class statsmodels.miscmodels.tmodel.TLinearModel(endog, exog=None, loglike=None, score=None, hessian=None, missing='none', extra_params_names=None, **kwds)
[source] -
Maximum Likelihood Estimation of Linear Model with t-distributed errors
This is an example for generic MLE.
Except for defining the negative log-likelihood method, all methods and results are generic. Gradients and Hessian and all resulting statistics are based on numerical differentiation.
Attributes
endog_names
Names of endogenous variables exog_names
Names of exogenous variables Methods
expandparams
(params)expand to full parameter array when some parameters are fixed fit
([start_params, method, maxiter, ...])Fit the model using maximum likelihood. from_formula
(formula, data[, subset, drop_cols])Create a Model from a formula and dataframe. hessian
(params)Hessian of log-likelihood evaluated at params information
(params)Fisher information matrix of model initialize
()jac
(*args, **kwds)jac
is deprecated, usescore_obs
instead!loglike
(params)loglikeobs
(params)nloglike
(params)nloglikeobs
(params)Loglikelihood of linear model with t distributed errors. predict
(params[, exog])reduceparams
(params)score
(params)Gradient of log-likelihood evaluated at params score_obs
(params, **kwds)Jacobian/Gradient of log-likelihood evaluated at params for each observation. Methods
expandparams
(params)expand to full parameter array when some parameters are fixed fit
([start_params, method, maxiter, ...])Fit the model using maximum likelihood. from_formula
(formula, data[, subset, drop_cols])Create a Model from a formula and dataframe. hessian
(params)Hessian of log-likelihood evaluated at params information
(params)Fisher information matrix of model initialize
()jac
(*args, **kwds)jac
is deprecated, usescore_obs
instead!loglike
(params)loglikeobs
(params)nloglike
(params)nloglikeobs
(params)Loglikelihood of linear model with t distributed errors. predict
(params[, exog])reduceparams
(params)score
(params)Gradient of log-likelihood evaluated at params score_obs
(params, **kwds)Jacobian/Gradient of log-likelihood evaluated at params for each observation. Attributes
endog_names
Names of endogenous variables exog_names
Names of exogenous variables
© 2009–2012 Statsmodels Developers
© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3-clause BSD License.
http://www.statsmodels.org/stable/generated/statsmodels.miscmodels.tmodel.TLinearModel.html