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# scikits.statsmodels.glm.GLMResults

class `scikits.statsmodels.glm.``GLMResults`(model, params, normalized_cov_params, scale)

  Class to contain GLM results.

  GLMResults inherits from statsmodels.LikelihoodModelResults

  Parameters: | See statsmodels.LikelihoodModelReesults :

  See also

  `statsmodels.LikelihoodModelResults`

  Attributes

  `llf` |
  `normalized_cov_params`() |

  aic | float | Akaike Information Criterion -2 * llf + 2*(df_model + 1)
  bic | float | Bayes Information Criterion deviance - df_resid * log(nobs)
  deviance | float | See statsmodels.family.family for the distribution-specific deviance functions.
  df_model | float | See GLM.df_model
  df_resid | float | See GLM.df_resid
  fittedvalues | array | Linear predicted values for the fitted model. dot(exog, params)
  model | class instance | Pointer to GLM model instance that called fit.
  mu | array | See GLM docstring.
  nobs | float | The number of observations n.
  null_deviance | float | The value of the deviance function for the model fit with a constant as the only regressor.
  params | array | The coefficients of the fitted model. Note that interpretation of the coefficients often depends on the distribution family and the data.
  pearsonX2 | array | Pearson’s Chi-Squared statistic is defined as the sum of the squares of the Pearson residuals.
  pinv_wexog | array | See GLM docstring.
  resid_anscombe | array | Anscombe residuals. See statsmodels.family.family for distribution- specific Anscombe residuals.
  resid_dev | array | Deviance residuals. See statsmodels.family.family for distribution- specific deviance residuals.
  resid_pearson | array | Pearson residuals. The Pearson residuals are defined as (endog - mu)/sqrt(VAR(mu)) where VAR is the distribution specific variance function. See statsmodels.family.family and statsmodels.family.varfuncs for more information.
  resid_response | array | Respnose residuals. The response residuals are defined as endog - fittedvalues
  resid_working | array | Working residuals. The working residuals are defined as resid_response/link’(mu). See statsmodels.family.links for the derivatives of the link functions. They are defined analytically.
  scale | array | The estimate of the scale / dispersion for the model fit. See GLM.fit and GLM.estimate_scale for more information.
  stand_errors | array | The standard errors of the fitted GLM. #TODO still named bse

  Methods

  `conf_int`([alpha, cols]) | Returns the confidence interval of the fitted parameters.
  `cov_params`([r_matrix, column, scale, other]) | Returns the variance/covariance matrix.
  `f_test`(r_matrix[, scale, invcov]) | Compute an Fcontrast/F-test for a contrast matrix.
  `t`([column]) | Return the t-statistic for a given parameter estimate.
  `t_test`(r_matrix[, scale]) | Compute a tcontrast/t-test for a row vector array.

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