如何使用R中的有序逻辑回归运行极端界限分析？

我正在尝试使用Marek Hlavac的ExtremeBounds R包和大众图书馆中的

polr

函数，使用有序逻辑回归（而不是OLS）来运行极端界限分析

我有一个数据集，由3个因变量和18个自变量组成，有25个观察值。我试图通过实施所有可能的回归组合，来确定18个变量中哪些与每个因变量密切相关。因此，对于下面的代码，我希望以来源国（来源国的人口贩运分数）为因变量，人均GDP为自由变量，其余变量为可疑变量（不包括其他两个因变量），进行极端界限分析

以下是我的数据子集：

head(data)
    Country Transit Destination Origin GDP_Per_Capita_PPP
1 Argentina      NA           3      2          14951.728
2    Belize       1           2   <NA>           7307.061
3    Brazil      NA           1      4          11642.444
4    Canada       3           4      2          37995.005
5     Chile      NA           1      1          15753.963
6  Colombia       1          NA      4           9035.566
  Population Democracy Female_Unemployment Total._Unemployment
1   39289878         8             12.3408             10.0775
2     291329        NA             15.0900              9.3900
3  188167356         8             11.2955              8.6395
4   32571174        10              6.0925              6.3203
5   16354504        10             11.7560              9.0240
6   43200897         7                  NA                  NA
  Female_LF_PR Total_LF_PR Percent_Rural_Pop Gini
1      50.1041     61.7950             9.800 46.7
2           NA          NA            54.704   NA
3      56.8993     67.7640            16.857 55.6
4      61.8830     67.0185            19.787   NA
5      41.3310     56.8750            13.158 47.3
6           NA          NA            23.577   NA
  Percent_phc_ratio Percent_Female_Literacy.rate
1                NA                     98.51077
2                NA                           NA
3                NA                     89.85559
4                NA                           NA
5              29.1                           NA
6                NA                     92.22060
  Percent_total_Literacy_rate Percent_youth_Literacy_rate
1                    98.61080                    99.44608
2                          NA                          NA
3                    89.61523                    97.58230
4                          NA                          NA
5                          NA                          NA
6                    92.29968                    97.88317
  Fertility_rate Percent_Pop_0.14 Population_density
1         2.3970         27.06570          14.356715
2         2.9800         38.25984          12.771986
3         1.9250         26.82929          22.513066
4         1.5862         17.40098           3.581804
5         1.9010         24.11969          21.995695
6         2.1980         29.79432          38.937266
  Percent_Employment_agri Trade_._of_GDP
1                   1.051       40.43348
2                  19.484      123.52556
3                  15.618       26.04170
4                   2.112       68.25132
5                  12.849       73.09865
6                  19.963       39.64136

头部（数据）
国家过境目的地来源地GDP人均购买力平价
1阿根廷NA 3 2 14951.728
2伯利兹127307.061
3巴西NA 1 4 11642.444
4加拿大3 4 2 37995.005
5智利NA 11 15753.963
6哥伦比亚1 NA 49035.566
人口民主女性失业总数
1   39289878         8             12.3408             10.0775
291329 NA 15.0900 9.3900
3  188167356         8             11.2955              8.6395
4   32571174        10              6.0925              6.3203
5   16354504        10             11.7560              9.0240
6 43200897 7不适用
女性占总人口的百分比农村流行基尼
1      50.1041     61.7950             9.800 46.7
2 NA 54.704 NA
3      56.8993     67.7640            16.857 55.6
461.8830 67.0185 19.787 NA
5      41.3310     56.8750            13.158 47.3
6NA 23.577NA
百分比phc比率百分比女性识字率
1 NA 98.51077
2娜娜
3 NA 89.85559
4娜娜
5.29.1不适用
6 NA 92.22060
总识字率百分比青年识字率百分比
1                    98.61080                    99.44608
2娜娜
3                    89.61523                    97.58230
4娜娜
5纳纳
6                    92.29968                    97.88317
生育率百分比流行率0.14人口密度
1         2.3970         27.06570          14.356715
2         2.9800         38.25984          12.771986
3         1.9250         26.82929          22.513066
4         1.5862         17.40098           3.581804
5         1.9010         24.11969          21.995695
6         2.1980         29.79432          38.937266
就业与农业贸易占GDP的百分比
1                   1.051       40.43348
2                  19.484      123.52556
3                  15.618       26.04170
4                   2.112       68.25132
5                  12.849       73.09865
6                  19.963       39.64136

下面是我试图运行的代码：

library(MASS)
library(ExtremeBounds)

data$Origin <- ordered(as.factor(data$Origin))
data$GDP_Per_Capita_PPP = scale(data$GDP_Per_Capita_PPP)
data$Population = scale(data$Population)

doubtful_vars <- c("Population","Democracy","Female_Unemployment","Total._Unemployment","Female_LF_PR","Total_LF_PR","Percent_Rural_Pop","Gini","Percent_phc_ratio", "Percent_Female_Literacy.rate","Percent_total_Literacy_rate","Percent_youth_Literacy_rate","Fertility_rate","Percent_Pop_0.14","Population_density","Percent_Employment_agri","Trade_._of_GDP")

origin_eba <- eba(data = data, y = "Origin", free = "GDP_Per_Capita_PPP", doubtful = doubtful_vars, reg.fun = polr, na.action = na.omit, method = "logistic", Hess = TRUE)

库（MASS）
图书馆（极端图书）
数据$来源