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162 changes: 161 additions & 1 deletion data/maxlikeli/Econ381totpts.txt
Original file line number Diff line number Diff line change
@@ -1 +1,161 @@
404: Not Found
275.5
351.5
346.25
228.25
108.25
380.75
346.25
360.75
196
414.75
370.5
371.75
143.75
333.5
397.5
405.75
154.75
321
279
326.5
49.5
402.75
389.75
382.25
337.75
311
105.5
380.5
236
326.5
343.75
328.75
316.25
348.25
338.75
375.75
410
17
414.25
21.25
369.625
318.875
336.125
429.875
407.5
415.75
332.375
397
375.875
419.125
270.125
299.25
384.125
335
408.5
414.25
253.5
339.25
338.75
355.375
326.375
240.375
385
435
317.25
365.625
372.75
365.125
349.625
366.75
386.5
391.75
403
258.5
386
411
350.25
402.25
294.625
291.125
378.125
442.0
428.1
347.3
431.8
430.4
426.0
433.5
331.1
405.7
415.5
406.4
418.6
400.7
408.8
404.8
409.4
410.8
402.5
401.0
415.3
390.8
394.6
399.0
380.0
397.5
368.7
394.7
304.3
391.1
388.4
370.3
384.6
383.5
305.6
286.5
367.9
329.8
288.2
338.5
333.6
268.6
335.2
296.3
269.1
243.2
159.4
448.4
449.8
435.9
429.4
428.3
427.5
422.5
409.8
415.8
413.4
416.8
406.7
383.9
389.0
387.2
368.6
399.5
382.6
355.9
389.9
342.5
365.2
320.3
341.5
248.1
305.0
279.2
275.7
204.5
235.0
102.2
112.3
130.6
60.2
8 changes: 4 additions & 4 deletions docs/book/struct_est/MaxLikelihood.md
Original file line number Diff line number Diff line change
Expand Up @@ -117,8 +117,8 @@ import requests
# Download and save the data file Econ381totpts.txt
url = ('https://raw.githubusercontent.com/OpenSourceEcon/CompMethods/' +
'main/data/maxlikeli/Econ381totpts.txt')
data_file = requests.get(url, allow_redirects=True)
open('../../../data/maxlikeli/Econ381totpts.txt', 'wb').write(data_file.content)
# data_file = requests.get(url, allow_redirects=True)
# open('../../../data/maxlikeli/Econ381totpts.txt', 'wb').write(data_file.content)

# Load the data as a NumPy array
data = np.loadtxt('../../../data/maxlikeli/Econ381totpts.txt')
Expand All @@ -132,9 +132,9 @@ Let's create a histogram of the data.
import matplotlib.pyplot as plt

num_bins = 30
count, bins, ignored = plt.hist(pts, num_bins, density=True,
count, bins, ignored = plt.hist(data, num_bins, density=True,
edgecolor='k')
plt.title('Econ 381 scores: 2011-2012', fontsize=20)
plt.title('Intermediate macro scores: 2011-2012', fontsize=15)
plt.xlabel(r'Total points')
plt.ylabel(r'Percent of scores')
plt.xlim([0, 550]) # This gives the xmin and xmax to be plotted"
Expand Down