spreg.diagnostics.t_stat¶

spreg.diagnostics.t_stat(reg, z_stat=False)[source]¶

Calculates the t-statistics (or z-statistics) and associated p-values. [Gre03]

Parameters

regregression object: output instance from a regression model
z_statboolean: If True run z-stat instead of t-stat

Returns

ts_resultlist of tuples: each tuple includes value of t statistic (or z statistic) and associated p-value

Examples

>>> import numpy as np
>>> import libpysal
>>> from libpysal import examples
>>> import diagnostics
>>> from ols import OLS

Read the DBF associated with the Columbus data.

>>> db = libpysal.open(libpysal.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 t-statistics for the regression coefficients.

>>> testresult = diagnostics.t_stat(reg)

Print the tuples that contain the t-statistics and their significances.

>>> print("%12.12f"%testresult[0][0], "%12.12f"%testresult[0][1], "%12.12f"%testresult[1][0], "%12.12f"%testresult[1][1], "%12.12f"%testresult[2][0], "%12.12f"%testresult[2][1])
('14.490373143689', '0.000000000000', '-4.780496191297', '0.000018289595', '-2.654408642718', '0.010874504910')