spreg.log_likelihood¶
- spreg.log_likelihood(reg)[source]¶
Calculates the log-likelihood value for the regression. [Gre03]
- Parameters:
- reg
regression
object
output instance from a regression model
- reg
- Returns:
- ll_result
float
value for the log-likelihood of the regression.
- ll_result
Examples
>>> import numpy as np >>> import libpysal >>> from libpysal import examples >>> import spreg >>> from spreg import OLS
Read the DBF associated with the Columbus data.
>>> db = libpysal.io.open(examples.get_path("columbus.dbf"),"r")
Create the dependent variable vector.
>>> y = np.array(db.by_col("CRIME")) >>> y = np.reshape(y, (49,1))
Create the matrix of independent variables.
>>> X = [] >>> X.append(db.by_col("INC")) >>> X.append(db.by_col("HOVAL")) >>> X = np.array(X).T
Run an OLS regression.
>>> reg = OLS(y,X)
Calculate the log-likelihood for the regression.
>>> testresult = spreg.log_likelihood(reg)
Print the result.
>>> testresult -187.3772388121491