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add regression model comparison with null hypothesis
1 parent a26eb06 commit d69c8aa

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Lines changed: 21 additions & 3 deletions

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compare_timeseries.py

Lines changed: 21 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -248,12 +248,30 @@ def compare_timeseries(parameters):
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df[s]['Trend Err ({0}) Gt/yr'.format(com_lbl)] = fit['error'][1]
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df[s]['Seasonal ({0}) Gt'.format(com_lbl)] = np.sqrt(fit['beta'][4]**2 + fit['beta'][5]**2)
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df[s]['Seasonal Err ({0}) Gt'.format(com_lbl)] = np.sqrt(fit['error'][4]**2 + fit['error'][5]**2)
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df[s]['R2 x1 ({0})'.format(com_lbl)] = fit['R2']
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df[s]['BIC x1 ({0})'.format(com_lbl)] = fit['AIC']
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df[s]['AIC x1 ({0})'.format(com_lbl)] = fit['BIC']
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#-- compare with no trend case
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fit = tsregress(tdec[s][ind[s]],mass[s][ind[s]],ORDER=0,CYCLES=[0.5,1])
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df[s]['R2 x0 ({0})'.format(com_lbl)] = fit['R2']
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df[s]['BIC x0 ({0})'.format(com_lbl)] = fit['AIC']
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df[s]['AIC x0 ({0})'.format(com_lbl)] = fit['BIC']
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#------------------------------------------------------
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#-- also get trend for 2015 onwards
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#------------------------------------------------------
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ind15 = np.squeeze(np.nonzero(tdec[s]>2015))
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fit = tsregress(tdec[s][ind15],mass[s][ind15],ORDER=1,CYCLES=[0.5,1])
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df[s]['Trend (2015+) Gt/yr'.format(com_lbl)] = fit['beta'][1]
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df[s]['Trend Err (2015+) Gt/yr'.format(com_lbl)] = fit['error'][1]
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df[s]['Trend (2015+) Gt/yr'] = fit['beta'][1]
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df[s]['Trend Err (2015+) Gt/yr'] = fit['error'][1]
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df[s]['R2 x1 (2015+)'] = fit['R2']
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df[s]['BIC x1 (2015+)'] = fit['AIC']
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df[s]['AIC x1 (2015+)'] = fit['BIC']
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#-- compare with no trend case
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fit = tsregress(tdec[s][ind[s]],mass[s][ind[s]],ORDER=0,CYCLES=[0.5,1])
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df[s]['R2 x0 (2015+)'] = fit['R2']
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df[s]['BIC x0 (2015+)'] = fit['AIC']
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df[s]['AIC x0 (2015+)'] = fit['BIC']
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#-- write regression results to file
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df = pd.DataFrame(df)
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df.to_csv(mscn_file.replace('.txt','_comparison_regession.csv'))

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