linearmodels.panel.results.PanelResults¶

class PanelResults(res)[source]¶

Results container for panel data models that do not include effects

Attributes:

corr_squared_between: Between Coefficient of determination using squared correlation
corr_squared_overall: Overall coefficient of determination using squared correlation
corr_squared_within: Within coefficient of determination using squared correlation
cov: Estimated covariance of parameters
df_model: Model degree of freedom
df_resid: Residual degree of freedom
entity_info: Statistics on observations per entity
estimated_effects: Estimated effects
f_statistic: Joint test of significance for non-constant regressors
f_statistic_robust: Joint test of significance for non-constant regressors
fitted_values: Fitted values
idiosyncratic: Idiosyncratic error
loglik: Log-likelihood of model
model_ss: Residual sum of squares
name: Model name
nobs: Number of observations used to estimate the model
params: Estimated parameters
pvalues: Parameter p-vals.
resid_ss: Residual sum of squares
resids: Model residuals
rsquared: Model Coefficient of determination
rsquared_between: Between Coefficient of determination
rsquared_overall: Overall coefficient of determination
rsquared_within: Within coefficient of determination
s2: Residual variance estimator
std_errors: Estimated parameter standard errors
summary: Model estimation summary.
time_info: Statistics on observations per time interval
total_ss: Total sum of squares
tstats: Parameter t-statistics
wresids: Weighted model residuals

Methods

`conf_int`([level])	Confidence interval construction
`predict`([exog, data, fitted, effects, ...])	In- and out-of-sample predictions
`wald_test`([restriction, value, formula])	Test linear equality constraints using a Wald test

Properties

`corr_squared_between`	Between Coefficient of determination using squared correlation
`corr_squared_overall`	Overall coefficient of determination using squared correlation
`corr_squared_within`	Within coefficient of determination using squared correlation
`cov`	Estimated covariance of parameters
`df_model`	Model degree of freedom
`df_resid`	Residual degree of freedom
`entity_info`	Statistics on observations per entity
`estimated_effects`	Estimated effects
`f_statistic`	Joint test of significance for non-constant regressors
`f_statistic_robust`	Joint test of significance for non-constant regressors
`fitted_values`	Fitted values
`idiosyncratic`	Idiosyncratic error
`loglik`	Log-likelihood of model
`model_ss`	Residual sum of squares
`name`	Model name
`nobs`	Number of observations used to estimate the model
`params`	Estimated parameters
`pvalues`	Parameter p-vals.
`resid_ss`	Residual sum of squares
`resids`	Model residuals
`rsquared`	Model Coefficient of determination
`rsquared_between`	Between Coefficient of determination
`rsquared_overall`	Overall coefficient of determination
`rsquared_within`	Within coefficient of determination
`s2`	Residual variance estimator
`std_errors`	Estimated parameter standard errors
`summary`	Model estimation summary.
`time_info`	Statistics on observations per time interval
`total_ss`	Total sum of squares
`tstats`	Parameter t-statistics
`wresids`	Weighted model residuals