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Fixed an issue with PPP ER table
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@Farewe
Farewe committed Apr 8, 2022
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14 changes: 0 additions & 14 deletions Readme.Rmd
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Expand Up @@ -238,20 +238,6 @@ In InvaCost, we provide several columns with monetary values expressed in
or `PPP` in their names.


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<thead>
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96 changes: 41 additions & 55 deletions Readme.md
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Expand Up @@ -290,20 +290,6 @@ In InvaCost, we provide several columns with monetary values expressed
in 2017 USD based on the exchange rate or PPP - they contain either
`exchange_rate` or `PPP` in their names.

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font-weight:normal;overflow:hidden;padding:10px 5px;word-break:normal;}
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Expand Down Expand Up @@ -1746,7 +1732,7 @@ global.trend$model.summary
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -97.892418 9.175960 -10.67 1.17e-13 ***
## (Intercept) -97.892418 9.175962 -10.67 1.17e-13 ***
## Year 0.051115 0.004617 11.07 3.59e-14 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Expand Down Expand Up @@ -1833,9 +1819,9 @@ global.trend$model.summary
##
## Formula:
## transf.cost ~ s(Year, k = gam.k)
## <environment: 0x00000000190d3fd8>
## <environment: 0x00000000190c2390>
## ~s(Year, k = gam.k)
## <environment: 0x00000000190d3fd8>
## <environment: 0x00000000190c2390>
##
## Parametric coefficients:
## Estimate Std. Error z value Pr(>|z|)
Expand Down Expand Up @@ -1874,27 +1860,27 @@ global.trend$model.summary
## Termination condition: RSq changed by less than 0.001 at 7 terms
## Importance: Year
## Number of terms at each degree of interaction: 1 5 (additive model)
## GCV 0.1267195 RSS 3.255282 GRSq 0.8060323 RSq 0.8841804 CVRSq 0.643618
## GCV 0.1267195 RSS 3.255282 GRSq 0.8060323 RSq 0.8841804 CVRSq 0.6540798
##
## Note: the cross-validation sd's below are standard deviations across folds
##
## Cross validation: nterms 2.74 sd 1.33 nvars 1.00 sd 0.00
## Cross validation: nterms 2.73 sd 1.31 nvars 1.00 sd 0.00
##
## CVRSq sd MaxErr sd
## 0.644 0.37 1.33 0.81
## CVRSq sd MaxErr sd
## 0.654 0.251 1.42 0.82
##
## varmod: method "lm" min.sd 0.0348 iter.rsq 0.021
## varmod: method "lm" min.sd 0.0347 iter.rsq 0.015
##
## stddev of predictions:
## coefficients iter.stderr iter.stderr%
## (Intercept) 0.16986950 0.18176 107
## transf.cost 0.04487061 0.0467456 104
## (Intercept) 0.19431372 0.184712 95
## transf.cost 0.03844936 0.047283 123
##
## mean smallest largest ratio
## 95% prediction interval 1.362516 1.103573 1.636191 1.48263
## mean smallest largest ratio
## 95% prediction interval 1.358642 1.136756 1.593152 1.401491
##
## 68% 80% 90% 95%
## response values in prediction interval 80 89 98 98
## 68% 80% 90% 95%
## response values in prediction interval 80 89 98 100
## ------------------------------------------------------------------------------------------------------------
##
## ______________________________ Quantile regressions _______________________________
Expand Down Expand Up @@ -2015,29 +2001,29 @@ summarized.summary
## 16 _________________ _________________
## 17 Robust regression - Linear
## 18 Estimate
## 19 Intercept -97.8924183372332
## 20 Year 0.0511148045828304
## 19 Intercept -97.8924184105278
## 20 Year 0.0511148046199673
## 21
## 22 Adjusted R²
## 23 0.760853846899685
## 23 0.760853845866438
## 24
## 25 Summary of model weights
## 26 Min
## 27 0.335498458617593
## 27 0.335498468663771
## 28 Number of outliers
## 29 0
## 30 _________________ _________________
## 31 Robust regression - Quadratic
## 32 Estimate
## 33 Intercept -3184.16167657334
## 34 Year 3.15003560078633
## 33 Intercept -3184.16171557813
## 34 Year 3.15003563972423
## 35
## 36 Adjusted R²
## 37 0.801667183408283
## 37 0.801667174178891
## 38
## 39 Summary of model weights
## 40 Min
## 41 0.177658959792565
## 41 0.177659030983913
## 42 Number of outliers
## 43 0
## 44 _________________ _________________
Expand All @@ -2055,11 +2041,11 @@ summarized.summary
## 56
## 57 Variance model
## 58 Estimate
## 59 Intercept 0.169869500067038
## 60 Intercept 0.0448706129847374
## 59 Intercept 0.19431371609858
## 60 Intercept 0.0384493576779084
## 61
## 62 R² for last iteration
## 63 0.020978141609606
## 63 0.0151450694451187
## 64 _________________ _________________
## 65 Generalized Additive Models
## 66 Parametric coefficients
Expand Down Expand Up @@ -2099,29 +2085,29 @@ summarized.summary
## 16 _________________ _________________
## 17
## 18 Standard error t value
## 19 9.17595970487391 -10.6683574782087
## 20 0.00461676911289358 11.0715531431014
## 19 9.17596178201959 -10.6683550712198
## 20 0.00461677016147957 11.0715506365139
## 21
## 22 R²
## 23 0.766288986742874
## 23 0.766288985733109
## 24
## 25
## 26 25% 50%
## 27 0.895670373377707 0.956019636074724
## 27 0.895670374503898 0.956019637206151
## 28
## 29
## 30 _________________ _________________
## 31
## 32 Standard error t value
## 33 1363.27362843849 -2.33567319879908
## 34 1.36871457009483 2.30145544557773
## 33 1363.27363592829 -2.33567321457804
## 34 1.36871457762435 2.30145546136557
## 35
## 36 R²
## 37 0.810682311435179
## 37 0.810682302625305
## 38
## 39
## 40 25% 50%
## 41 0.886348161233568 0.95927180922917
## 41 0.886348169899944 0.959271817570762
## 42
## 43
## 44 _________________ _________________
Expand All @@ -2139,8 +2125,8 @@ summarized.summary
## 56
## 57
## 58 Standard error (last iteration) Standard error/coefficient %
## 59 0.181760102486301 106.999845419319
## 60 0.0467455702959492 104.178586354168
## 59 0.184711969664206 95.0586368131095
## 60 0.0472830364390933 122.974840919801
## 61
## 62
## 63
Expand Down Expand Up @@ -2183,29 +2169,29 @@ summarized.summary
## 16 _________________ _________________
## 17
## 18 p-value
## 19 1.1681705949797e-13
## 20 3.59412414869921e-14
## 19 1.16817888851562e-13
## 20 3.59415025068386e-14
## 21
## 22
## 23
## 24
## 25
## 26 75% Max
## 27 0.994641723534304 0.999854194997377
## 27 0.994641723689848 0.999854195010966
## 28
## 29
## 30 _________________ _________________
## 31
## 32 p-value
## 33 0.0243578368193137
## 34 0.0263953065469831
## 33 0.0243578359132511
## 34 0.0263953055727227
## 35
## 36
## 37
## 38
## 39
## 40 75% Max
## 41 0.98295451012038 0.999977209664879
## 41 0.982954511952929 0.999977209612746
## 42
## 43
## 44 _________________ _________________
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