`lambda` is printed twice in `GM_Error_Het` results report

[darribas]

Using the tutorial example:

import numpy, pandas, libpysal, spreg

# Read Baltimore data
db = libpysal.io.open(libpysal.examples.get_path("baltim.dbf"), "r")
ds_name = "baltim.dbf"

# Read dependent variable
y_name = "PRICE"
y = numpy.array(db.by_col(y_name)).T
y = y[:, numpy.newaxis]

# Read exogenous variables
x_names = ["NROOM", "NBATH", "PATIO", "FIREPL", "AC", "GAR", "AGE", "LOTSZ", "SQFT"]
x = numpy.array([db.by_col(var) for var in x_names]).T

# Read spatial data
ww = libpysal.io.open(libpysal.examples.get_path("baltim_q.gal"))
w = ww.read()
ww.close()
w_name = "baltim_q.gal"
w.transform = "r"

model = spreg.GM_Error_Het(
    y,
    x,
    w=w,
    name_y=y_name,
    name_x=x_names,
    name_w="baltim_q",
)
print(model.summary)

Returns the following printout:

REGRESSION
----------
SUMMARY OF OUTPUT: SPATIALLY WEIGHTED LEAST SQUARES (HET)
---------------------------------------------------------
Data set            :     unknown
Weights matrix      :    baltim_q
Dependent Variable  :       PRICE                Number of Observations:         211
Mean dependent var  :     44.3072                Number of Variables   :          10
S.D. dependent var  :     23.6061                Degrees of Freedom    :         201
Pseudo R-squared    :      0.6467
N. of iterations    :           1                Step1c computed       :          No

------------------------------------------------------------------------------------
            Variable     Coefficient       Std.Error     z-Statistic     Probability
------------------------------------------------------------------------------------
            CONSTANT      20.0732495       6.7858988       2.9580827       0.0030956
               NROOM       1.0932756       1.3744184       0.7954460       0.4263541
               NBATH       6.3277367       2.3902173       2.6473479       0.0081126
               PATIO       8.3002828       3.3887765       2.4493450       0.0143116
              FIREPL       9.1325847       2.6462219       3.4511787       0.0005581
                  AC       6.7053204       3.1584166       2.1230006       0.0337538
                 GAR       4.4574380       2.7187407       1.6395230       0.1011044
                 AGE      -0.1812099       0.1290087      -1.4046330       0.1601304
               LOTSZ       0.0856008       0.0258313       3.3138441       0.0009202
                SQFT       0.1111843       0.2172385       0.5118076       0.6087857
              lambda       0.4716553       0.0942220       5.0057882       0.0000006
              lambda       0.4716553       0.0942220       5.0057882       0.0000006
------------------------------------------------------------------------------------
================================ END OF REPORT =====================================

I think this is only in the summary printout, the betas, name_x and related vectors are correct.

Versions:

• libpysal = '4.4.0'
• spreg = '1.2.2'