linearmodels.iv.results.IVGMMResults¶
- class IVGMMResults(results, model)[source]¶
Results from GMM estimation of IV models
- Parameters:
- Attributes:
cov
Estimated covariance of parameters
cov_config
Parameter values from covariance estimator
cov_estimator
Type of covariance estimator used to compute covariance
cov_type
Covariance estimator used
debiased
Flag indicating whether covariance uses a small-sample adjustment
df_model
Model degree of freedom
df_resid
Residual degree of freedom
f_statistic
Model F-statistic
first_stage
First stage regression results
fitted_values
Fitted values
has_constant
Flag indicating the model includes a constant or equivalent
idiosyncratic
Idiosyncratic error
iterations
Iterations used in GMM estimation
j_stat
J-test of overidentifying restrictions
kappa
k-class estimator value
method
Method used to estimate model parameters
model_ss
Residual sum of squares
nobs
Number of observations
params
Estimated parameters
pvalues
Parameter p-vals.
resid_ss
Residual sum of squares
resids
Estimated residuals
rsquared
Coefficient of determination (R**2)
rsquared_adj
Sample-size adjusted coefficient of determination (R**2)
s2
Residual variance estimator
std_errors
Estimated parameter standard errors
summary
Model estimation summary.
total_ss
Total sum of squares
tstats
Parameter t-statistics
weight_config
Weighting matrix configuration used in estimation
weight_matrix
Weight matrix used in the final-step GMM estimation
weight_type
Weighting matrix method used in estimation
wresids
Weighted estimated residuals
Methods
c_stat
([variables])C-test of endogeneity
conf_int
([level])Confidence interval construction
predict
([exog, endog, data, fitted, ...])In- and out-of-sample predictions
wald_test
([restriction, value, formula])Test linear equality constraints using a Wald test
Properties
Estimated covariance of parameters
Parameter values from covariance estimator
Type of covariance estimator used to compute covariance
Covariance estimator used
Flag indicating whether covariance uses a small-sample adjustment
Model degree of freedom
Residual degree of freedom
Model F-statistic
First stage regression results
Fitted values
Flag indicating the model includes a constant or equivalent
Idiosyncratic error
Iterations used in GMM estimation
J-test of overidentifying restrictions
k-class estimator value
Method used to estimate model parameters
Residual sum of squares
Number of observations
Estimated parameters
Parameter p-vals.
Residual sum of squares
Estimated residuals
Coefficient of determination (R**2)
Sample-size adjusted coefficient of determination (R**2)
Residual variance estimator
Estimated parameter standard errors
Model estimation summary.
Total sum of squares
Parameter t-statistics
Weighting matrix configuration used in estimation
Weight matrix used in the final-step GMM estimation
Weighting matrix method used in estimation
Weighted estimated residuals