Delete OLS

OLS

-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-"""
-Created on Tue Dec 10 11:14:16 2019
-
-@author: Martin Renoult
-correspondence: martin.renoult@misu.su.se
-"""
-
-## Library
-
-import numpy as np
-import statsmodels.api as sm
-
-from pymc3 import *
-
-#------------------------------------------------------------------------------
-## Model data
-# x = ECS
-# y = Tropical temperature
-
-# In the following order:
-# PMIP2[MIROC, IPSL, CCSM, ECHAM, FGOALS, HadCM3, ECBILT]
-# PMIP3[NCAR-CCSM4, IPSL-CM5A-LR, MIROC-ESM, MPI-ESM-P, CNRM-CM5, MRI-CGCM3, FGOALS-g2]
-
-x = [4,4.4,2.7,3.4,2.3,3.3,1.8,
-     3.2,4.13,4.67,3.45,3.25,2.6,3.37]
-
-y = [-2.74899797,-2.82983243,-2.11649457,-3.15521371,-2.35793821,-2.77644642,-1.33816631,
-     -2.5957031, -3.3755188, -2.5169983, -2.5567322, -1.6669922, -2.81839, -3.1465664]
-
-# PMIP2 only
-x_pmip2 = [4,4.4,2.7,3.4,2.3,3.3,1.8]
-y_pmip2 = [-2.74899797,-2.82983243,-2.11649457,-3.15521371,-2.35793821,-2.77644642,-1.33816631]
-
-# PMIP2+3
-x_pmip23 = [4,4.4,2.7,3.4,2.3,3.3,1.8,
-     3.2,4.13,4.67,3.45,3.25,2.6,3.37]
-
-y_pmip23 = [-2.74899797,-2.82983243,-2.11649457,-3.15521371,-2.35793821,-2.77644642,-1.33816631,
-     -2.5957031, -3.3755188, -2.5169983, -2.5567322, -1.6669922, -2.81839, -3.1465664]
-
-# PMIP3 only
-#x_3 = [3.2,4.13,4.67,3.45,3.25,2.6,3.37]
-#
-#y_3 = [-2.5957031, -3.3755188, -2.5169983, -2.5567322, -1.6669922, -2.81839, -3.1465664]
-
-list_predict_t_stats = list()
-low_bound = list()
-up_bound = list()
-
-# OLS on the dataset of Schmidt et al., 2014
-y_pmip23 = sm.add_constant(y_pmip23)
-model_schmidt = sm.OLS(x_pmip23, y_pmip23)
-results_schmidt = model_schmidt.fit()
-
-coeff_schmidt = results_schmidt.params
-resid_schmidt = results_schmidt.resid
-mse_resid_schmidt = results_schmidt.mse_resid
-
-y_pmip23 = y_pmip23[:,1:]
-
-# OLS on the dataset of Hargreaves et al., 2012
-y_pmip2 = sm.add_constant(y_pmip2)
-model_hargreaves = sm.OLS(x_pmip2, y_pmip2)
-results_hargreaves = model_hargreaves.fit()
-
-coeff_hargreaves = results_hargreaves.params
-resid_hargreaves = results_hargreaves.resid
-mse_resid_hargreaves = results_hargreaves.mse_resid
-
-y_pmip2 = y_pmip2[:,1:]
-
-ran_renoult = np.linspace(0, 20, 1000)
-ran_schmidt = np.linspace(-6, 10, 500)
-
-prediction_schmidt = (ran_schmidt-coeff_schmidt[0])/coeff_schmidt[1]
-prediction_hargreaves = (ran_schmidt-coeff_hargreaves[0])/coeff_hargreaves[1]
-
-# "Real" observed data of tropical LGM
-T = -2.2
-stdT = 0.4
-distrib_T = np.random.normal(loc=T, scale=stdT, size=100000)
-
-# Inference
-inference_schmidt = distrib_T*coeff_schmidt[1]+coeff_schmidt[0]+np.random.normal(loc=0, scale=mse_resid_schmidt**0.5, size=100000)
-inference_hargreaves = distrib_T*coeff_hargreaves[1]+coeff_hargreaves[0]+np.random.normal(loc=0, scale=mse_resid_hargreaves**0.5, size=100000)
-
-# Some statistics
-median_23 = np.median(inference_schmidt)
-median_23 = np.round(median_23, decimals=2)
-
-median_2 = np.median(inference_hargreaves)
-median_2 = np.round(median_2, decimals=2)
-
-post_stats_90_23 = np.percentile(inference_schmidt, q=(5, 95))
-post_stats_90_2 = np.percentile(inference_hargreaves, q=(5, 95))
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