R version 3.3.2 (2016-10-31) -- "Sincere Pumpkin Patch"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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Type 'contributors()' for more information and
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Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- c(66.7
+ ,11.6
+ ,59.6
+ ,26.1
+ ,13.3
+ ,33.9
+ ,62.2
+ ,52.4
+ ,6.0
+ ,30.2
+ ,61.8
+ ,83.7
+ ,26.9
+ ,32.7
+ ,11.5
+ ,17.2
+ ,32.2
+ ,67.9
+ ,55.7
+ ,37.2
+ ,16.2
+ ,51.1
+ ,28.5
+ ,46.3
+ ,4.5
+ ,94.0
+ ,57.5
+ ,50.6
+ ,60.1
+ ,4.0
+ ,5.5
+ ,29.6
+ ,24.6
+ ,87.4
+ ,71.6
+ ,12.3
+ ,34.5
+ ,94.0
+ ,71.3
+ ,66.3
+ ,87.8
+ ,59.0
+ ,4.7
+ ,0.2
+ ,37.8
+ ,46.9
+ ,2.5
+ ,81.8
+ ,75.9
+ ,61.3
+ ,79.7
+ ,40.0
+ ,27.7
+ ,97.2
+ ,64.3
+ ,75.2
+ ,101.0
+ ,69.3
+ ,35.2
+ ,9.1
+ ,72.0
+ ,61.1
+ ,24.4
+ ,56.1
+ ,11.5
+ ,60.1
+ ,59.1
+ ,7.4
+ ,28.0
+ ,85.3
+ ,3.8
+ ,50.2
+ ,46.9
+ ,40.0
+ ,53.4
+ ,5.5
+ ,64.7
+ ,1.8
+ ,62.6
+ ,53.7
+ ,37.8
+ ,41.9
+ ,60.2
+ ,18.8
+ ,90.8
+ ,17.0
+ ,6.5
+ ,3.3
+ ,2.8
+ ,28.9
+ ,12.8
+ ,6.4
+ ,15.6
+ ,66.3
+ ,62.1
+ ,119.1
+ ,58.4
+ ,7.8
+ ,40.4
+ ,62.6
+ ,39.6
+ ,99.1
+ ,21.6
+ ,67.3
+ ,12.8
+ ,10.5
+ ,51.1
+ ,19.7
+ ,49.3
+ ,9.9
+ ,1.6
+ ,5.7
+ ,47.7
+ ,67.9
+ ,104.7
+ ,27.3
+ ,50.9
+ ,35.1
+ ,26.6
+ ,44.1
+ ,54.1
+ ,45.2
+ ,8.7
+ ,38.4
+ ,61.0
+ ,12.1
+ ,45.6
+ ,57.2
+ ,19.3
+ ,76.8
+ ,22.5
+ ,36.2
+ ,38.6
+ ,71.5
+ ,53.3
+ ,77.7
+ ,38.7
+ ,8.7
+ ,66.8
+ ,6.7
+ ,32.4
+ ,1.2
+ ,22.0
+ ,26.9
+ ,53.6
+ ,76.0
+ ,14.6
+ ,51.8
+ ,5.5
+ ,50.7
+ ,72.2
+ ,47.7
+ ,70.2
+ ,25.7
+ ,13.2
+ ,108.2
+ ,79.1
+ ,36.9
+ ,37.8
+ ,16.6
+ ,45.9
+ ,7.4
+ ,57.1
+ ,32.5
+ ,55.9
+ ,21.4
+ ,46.1
+ ,93.2
+ ,12.2
+ ,41.9
+ ,49.0
+ ,66.7
+ ,21.0
+ ,55.4
+ ,13.8
+ ,39.5
+ ,51.9
+ ,36.3
+ ,46.3
+ ,51.0
+ ,6.0
+ ,19.7
+ ,42.9
+ ,7.0
+ ,40.0
+ ,35.6
+ ,7.8
+ ,15.7
+ ,36.9
+ ,87.2
+ ,53.9
+ ,51.8
+ ,47.6
+ ,37.7
+ ,87.2
+ ,26.8
+ ,64.6
+ ,26.1
+ ,34.4
+ ,13.4
+ ,64.2
+ ,34.0
+ ,19.6
+ ,21.7
+ ,5.2
+ ,62.6
+ ,3.8
+ ,3.7
+ ,63.6
+ ,32.0
+ ,64.3
+ ,24.9
+ ,2.8
+ ,54.5
+ ,120.2
+ ,13.5
+ ,37.0
+ ,56.2
+ ,45.5
+ ,6.6
+ ,31.8
+ ,8.2
+ ,41.2
+ ,49.0
+ ,1.5
+ ,13.6
+ ,112.5
+ ,28.3
+ ,72.1
+ ,9.7
+ ,16.4
+ ,54.5
+ ,22.4
+ ,39.5
+ ,55.7
+ ,72.1
+ ,51.3
+ ,81.9
+ ,73.3
+ ,26.3
+ ,48.3
+ ,54.6
+ ,17.0
+ ,23.2
+ ,61.0
+ ,1.2
+ ,69.4
+ ,46.8
+ ,18.3
+ ,15.7
+ ,50.1
+ ,37.3
+ ,89.6
+ ,45.3
+ ,22.7
+ ,19.8
+ ,32.5
+ ,87.6
+ ,53.4
+ ,10.0
+ ,9.3
+ ,9.0
+ ,33.3
+ ,65.2
+ ,50.3
+ ,62.2
+ ,56.1
+ ,8.8
+ ,40.9
+ ,32.5
+ ,99.2
+ ,45.8
+ ,53.5
+ ,13.4
+ ,93.3
+ ,17.5
+ ,62.4
+ ,38.1
+ ,48.9
+ ,22.3
+ ,49.3
+ ,41.2
+ ,43.4
+ ,33.4
+ ,39.6
+ ,79.5
+ ,60.6
+ ,30.5
+ ,6.2
+ ,8.4
+ ,90.9
+ ,18.6
+ ,29.7
+ ,5.2
+ ,26.1
+ ,19.2
+ ,0.7
+ ,34.6
+ ,98.5
+ ,28.1
+ ,60.8
+ ,17.3
+ ,92.1
+ ,38.2
+ ,9.9
+ ,4.8
+ ,41.2
+ ,1.1
+ ,64.4
+ ,45.5
+ ,90.1
+ ,26.8
+ ,23.2
+ ,58.9
+ ,24.5
+ ,61.7
+ ,1.5
+ ,25.6
+ ,5.9
+ ,24.7
+ ,12.9
+ ,43.1
+ ,34.3
+ ,34.5
+ ,3.1
+ ,54.7
+ ,74.9
+ ,67.5
+ ,13.6
+ ,47.8
+ ,43.2
+ ,8.7
+ ,79.0
+ ,15.3
+ ,36.0
+ ,46.2
+ ,65.8
+ ,11.3
+ ,94.0
+ ,4.9
+ ,69.8
+ ,48.9
+ ,30.8
+ ,25.6
+ ,86.1
+ ,54.3
+ ,6.5
+ ,21.6
+ ,4.5
+ ,40.4
+ ,8.1
+ ,3.6
+ ,91.4
+ ,4.6
+ ,69.4
+ ,9.9
+ ,7.0
+ ,13.6
+ ,6.5
+ ,42.2
+ ,48.3
+ ,11.7
+ ,2.2
+ ,65.1
+ ,22.9
+ ,119.8
+ ,39.5
+ ,42.1
+ ,19.1
+ ,5.0
+ ,57.0
+ ,10.6
+ ,11.4
+ ,42.7
+ ,62.2
+ ,22.7
+ ,75.0
+ ,25.9
+ ,22.9
+ ,98.0
+ ,57.6
+ ,55.3
+ ,33.1
+ ,2.8
+ ,49.5
+ ,97.3
+ ,8.2
+ ,56.5
+ ,46.8
+ ,51.8
+ ,60.3
+ ,65.5
+ ,83.2
+ ,11.1
+ ,11.1
+ ,51.7
+ ,45.7
+ ,31.5
+ ,57.1
+ ,18.2
+ ,35.8
+ ,41.0
+ ,45.7
+ ,33.3
+ ,21.0
+ ,16.0
+ ,51.3
+ ,22.5
+ ,10.9
+ ,41.1
+ ,5.8
+ ,14.0
+ ,35.3
+ ,44.5
+ ,17.8
+ ,81.1
+ ,22.5
+ ,1.7
+ ,38.2
+ ,11.8
+ ,16.2
+ ,74.8
+ ,36.3
+ ,17.2
+ ,52.0
+ ,63.5
+ ,31.2
+ ,20.0
+ ,39.3
+ ,25.8
+ ,55.7
+ ,8.4
+ ,69.0
+ ,45.1
+ ,44.1
+ ,57.5
+ ,37.8
+ ,55.7
+ ,30.4
+ ,49.0
+ ,44.0
+ ,61.5
+ ,93.3
+ ,16.8
+ ,4.6
+ ,6.5
+ ,62.7
+ ,0.9
+ ,95.8
+ ,45.4
+ ,59.9
+ ,19.5
+ ,67.1
+ ,55.7
+ ,74.7
+ ,51.0
+ ,68.1
+ ,36.2
+ ,50.4
+ ,32.3
+ ,79.1
+ ,18.6
+ ,13.5
+ ,60.0
+ ,16.7
+ ,46.7
+ ,83.0
+ ,4.0
+ ,32.0
+ ,71.5
+ ,41.3
+ ,4.3
+ ,30.1
+ ,20.5
+ ,10.2
+ ,52.9
+ ,46.6
+ ,54.4
+ ,5.5
+ ,30.9
+ ,62.0
+ ,5.8
+ ,19.9
+ ,113.1
+ ,35.1
+ ,13.2
+ ,102.1
+ ,36.7
+ ,44.9
+ ,44.9
+ ,26.4
+ ,54.2
+ ,47.0
+ ,33.6
+ ,74.7
+ ,74.2
+ ,56.0
+ ,37.3
+ ,48.2
+ ,88.5
+ ,56.2
+ ,89.4
+ ,84.0
+ ,44.0
+ ,57.0
+ ,94.9
+ ,45.7
+ ,71.4
+ ,76.1
+ ,29.6
+ ,56.6
+ ,3.0
+ ,8.5
+ ,43.7
+ ,54.1
+ ,26.9
+ ,27.6
+ ,10.5
+ ,34.1
+ ,13.1
+ ,34.4
+ ,50.8
+ ,65.8
+ ,54.2
+ ,61.3
+ ,5.9
+ ,55.5
+ ,53.6
+ ,52.6
+ ,59.8
+ ,11.2
+ ,7.7
+ ,12.9
+ ,26.9
+ ,44.4
+ ,39.5
+ ,68.1
+ ,11.2
+ ,37.9
+ ,76.9
+ ,15.4
+ ,14.5
+ ,27.8
+ ,32.7
+ ,16.1
+ ,58.8
+ ,16.4
+ ,58.1
+ ,52.7
+ ,48.2
+ ,54.6
+ ,110.4
+ ,30.5
+ ,6.2
+ ,68.8
+ ,34.9
+ ,57.9
+ ,22.5
+ ,74.5
+ ,37.3
+ ,62.7
+ ,41.6
+ ,63.7
+ ,52.1
+ ,64.4
+ ,2.7
+ ,52.9
+ ,40.1
+ ,100.7
+ ,53.3
+ ,22.2
+ ,28.7
+ ,23.9
+ ,86.7
+ ,26.0
+ ,79.0
+ ,5.0
+ ,50.2
+ ,61.1
+ ,38.8
+ ,44.7
+ ,35.8
+ ,23.8
+ ,5.6
+ ,55.2
+ ,18.4
+ ,52.8
+ ,48.5
+ ,80.2
+ ,14.3
+ ,21.4
+ ,36.0
+ ,31.2
+ ,16.8
+ ,20.5
+ ,13.8
+ ,72.7
+ ,55.5
+ ,41.2
+ ,5.8
+ ,61.5
+ ,85.5
+ ,29.4
+ ,2.1
+ ,2.6
+ ,64.4
+ ,46.2
+ ,60.2
+ ,60.7
+ ,113.2
+ ,40.3
+ ,24.6
+ ,117.9
+ ,7.0
+ ,40.0
+ ,44.6
+ ,57.9
+ ,41.8
+ ,33.5
+ ,67.5
+ ,43.8
+ ,29.6
+ ,4.4
+ ,27.2
+ ,34.3
+ ,54.3
+ ,25.2
+ ,16.7
+ ,23.6
+ ,24.8
+ ,4.2
+ ,39.6
+ ,9.9
+ ,60.4
+ ,46.8
+ ,36.5
+ ,26.6
+ ,21.7
+ ,30.2
+ ,52.9
+ ,12.6
+ ,69.9
+ ,103.4
+ ,30.3
+ ,62.1
+ ,16.8
+ ,6.8
+ ,61.2
+ ,62.4
+ ,69.8
+ ,30.1
+ ,36.1
+ ,7.9
+ ,86.2
+ ,90.0
+ ,61.1
+ ,48.7
+ ,82.5
+ ,15.0
+ ,36.8
+ ,8.8
+ ,122.4
+ ,5.8
+ ,60.3
+ ,81.0
+ ,47.1
+ ,1.7
+ ,48.1
+ ,2.4
+ ,11.8
+ ,47.8
+ ,20.8
+ ,86.3
+ ,24.3
+ ,14.4
+ ,58.8
+ ,11.3
+ ,15.0
+ ,42.0
+ ,88.2
+ ,11.4
+ ,5.3
+ ,57.4
+ ,34.4
+ ,45.8
+ ,7.2
+ ,68.3
+ ,28.5
+ ,53.6
+ ,52.3
+ ,26.8
+ ,4.2
+ ,27.3
+ ,1.3
+ ,7.6
+ ,6.4
+ ,39.2
+ ,49.7
+ ,6.0
+ ,38.8
+ ,48.6
+ ,77.3
+ ,9.8
+ ,10.7
+ ,11.2
+ ,18.7
+ ,11.1
+ ,7.7
+ ,65.5
+ ,92.7
+ ,8.4
+ ,10.6
+ ,56.6
+ ,22.3
+ ,39.5
+ ,7.6
+ ,12.8
+ ,28.1
+ ,61.0
+ ,28.7
+ ,37.6
+ ,7.1
+ ,29.0
+ ,52.8
+ ,1.8
+ ,48.5
+ ,41.0
+ ,13.1
+ ,34.5
+ ,67.0
+ ,62.5
+ ,14.2
+ ,59.9
+ ,64.9
+ ,51.5
+ ,32.3
+ ,75.4
+ ,13.3
+ ,29.8
+ ,5.1
+ ,70.4
+ ,25.7
+ ,22.7
+ ,13.8
+ ,40.0
+ ,22.0
+ ,26.6
+ ,35.8
+ ,6.7
+ ,59.2
+ ,56.5
+ ,44.0
+ ,46.8
+ ,24.1
+ ,9.3
+ ,75.7
+ ,7.3
+ ,1.7
+ ,18.8
+ ,47.4
+ ,45.9
+ ,80.2
+ ,22.5
+ ,73.3
+ ,46.3
+ ,56.3
+ ,18.5
+ ,14.4
+ ,67.5
+ ,44.3
+ ,48.1
+ ,67.2
+ ,90.1
+ ,27.6
+ ,38.8
+ ,64.7
+ ,33.1
+ ,9.9
+ ,37.8
+ ,17.7
+ ,10.8
+ ,41.9
+ ,46.2
+ ,94.7
+ ,39.0
+ ,42.8
+ ,8.9
+ ,29.0
+ ,11.8
+ ,16.6
+ ,25.9
+ ,58.0
+ ,54.1
+ ,38.9
+ ,35.7
+ ,79.3
+ ,3.8
+ ,27.5
+ ,10.2
+ ,74.5
+ ,14.7
+ ,64.2
+ ,6.6
+ ,89.5
+ ,6.2
+ ,63.0
+ ,55.8
+ ,29.9
+ ,71.0
+ ,12.1
+ ,42.4
+ ,3.6
+ ,52.2
+ ,61.5
+ ,5.6
+ ,25.4
+ ,2.9
+ ,43.8
+ ,2.9
+ ,56.5
+ ,21.6
+ ,63.3
+ ,21.7
+ ,36.7
+ ,46.6
+ ,24.4
+ ,9.2
+ ,40.0
+ ,54.3
+ ,49.1
+ ,51.9
+ ,31.7
+ ,23.1
+ ,67.2
+ ,40.5
+ ,96.6
+ ,74.1
+ ,20.3
+ ,17.5
+ ,16.2
+ ,49.5
+ ,29.9
+ ,28.3
+ ,54.2
+ ,59.0
+ ,45.4
+ ,45.2
+ ,36.9
+ ,63.7
+ ,73.7
+ ,26.2
+ ,15.3
+ ,33.6
+ ,19.2
+ ,0.1
+ ,48.7
+ ,25.8
+ ,56.0
+ ,2.6
+ ,38.4
+ ,67.9
+ ,86.1
+ ,36.3
+ ,5.7
+ ,4.0
+ ,7.2
+ ,70.4
+ ,8.2
+ ,22.0
+ ,38.6
+ ,46.7
+ ,44.7
+ ,23.7
+ ,11.8
+ ,47.1
+ ,64.4
+ ,7.6
+ ,56.5
+ ,8.1
+ ,49.6
+ ,89.9
+ ,62.8
+ ,44.4
+ ,23.9
+ ,73.5
+ ,73.4
+ ,3.1
+ ,28.1
+ ,22.3
+ ,6.7
+ ,31.6
+ ,30.0
+ ,29.1
+ ,111.9
+ ,36.9
+ ,45.7
+ ,18.3
+ ,15.5
+ ,23.9
+ ,4.9
+ ,7.2
+ ,39.6
+ ,22.5
+ ,40.2
+ ,51.4
+ ,82.9
+ ,8.2
+ ,86.1
+ ,11.1
+ ,50.4
+ ,30.0
+ ,25.0
+ ,55.6
+ ,83.8
+ ,47.1
+ ,1.3
+ ,35.1
+ ,15.0
+ ,43.8
+ ,30.9
+ ,40.6
+ ,47.2
+ ,68.5
+ ,77.2
+ ,66.2
+ ,13.2
+ ,21.5
+ ,41.8
+ ,34.2
+ ,60.8
+ ,94.5
+ ,68.0
+ ,50.3
+ ,10.7
+ ,25.9
+ ,32.1
+ ,93.9
+ ,74.1
+ ,34.1
+ ,33.4
+ ,31.7
+ ,33.9
+ ,14.7
+ ,42.0
+ ,1.3
+ ,3.4
+ ,96.4
+ ,66.1
+ ,66.6
+ ,9.4
+ ,4.4
+ ,2.2
+ ,25.2
+ ,41.0
+ ,161.6
+ ,0.3
+ ,28.4
+ ,31.1
+ ,37.4
+ ,41.6
+ ,42.8
+ ,42.3
+ ,13.7
+ ,88.7
+ ,25.6
+ ,30.4
+ ,80.1
+ ,48.3
+ ,68.7
+ ,17.3
+ ,66.0
+ ,9.7
+ ,9.0
+ ,48.6
+ ,66.3
+ ,19.9
+ ,33.3
+ ,2.6
+ ,65.4
+ ,106.5
+ ,75.1
+ ,12.6
+ ,49.7
+ ,80.0
+ ,32.3
+ ,30.0
+ ,11.4
+ ,9.6
+ ,41.3
+ ,30.0
+ ,47.8
+ ,25.6
+ ,25.1
+ ,7.2
+ ,9.4
+ ,1.6
+ ,45.8
+ ,41.8
+ ,16.7
+ ,42.6
+ ,79.4
+ ,15.1
+ ,8.1
+ ,26.8
+ ,10.7
+ ,113.2
+ ,46.1
+ ,51.4
+ ,62.2
+ ,11.4
+ ,42.2
+ ,25.0
+ ,23.4
+ ,46.3
+ ,52.1
+ ,9.7
+ ,46.9
+ ,8.2
+ ,22.5
+ ,7.9
+ ,44.3
+ ,14.3
+ ,38.7
+ ,8.8
+ ,5.5
+ ,19.7
+ ,34.4
+ ,9.5
+ ,4.2
+ ,2.5
+ ,48.1
+ ,64.5
+ ,68.1
+ ,8.9
+ ,20.3
+ ,23.0
+ ,32.8
+ ,10.9
+ ,35.1
+ ,10.6
+ ,86.1
+ ,9.7
+ ,16.8
+ ,51.2
+ ,30.8
+ ,13.6
+ ,25.7
+ ,88.2
+ ,65.1
+ ,35.1
+ ,86.5
+ ,63.8
+ ,5.9
+ ,40.5
+ ,47.2
+ ,8.8
+ ,11.7
+ ,5.5
+ ,8.4
+ ,38.0
+ ,47.0
+ ,46.3
+ ,95.6
+ ,31.7
+ ,34.4
+ ,6.4
+ ,30.6
+ ,33.1
+ ,44.5
+ ,3.2
+ ,47.8
+ ,46.6
+ ,43.4
+ ,33.3
+ ,26.1
+ ,7.8
+ ,27.8
+ ,29.0
+ ,59.0
+ ,16.1
+ ,11.8
+ ,7.0
+ ,13.7
+ ,48.3
+ ,8.5
+ ,21.1
+ ,6.3
+ ,56.9
+ ,7.0
+ ,74.9
+ ,31.0
+ ,19.7
+ ,28.4
+ ,43.7
+ ,46.1
+ ,35.8
+ ,53.4
+ ,52.2
+ ,46.2
+ ,111.2
+ ,31.9
+ ,56.0
+ ,25.3
+ ,33.3
+ ,4.9
+ ,24.0
+ ,17.7
+ ,31.9
+ ,41.3
+ ,13.6
+ ,11.4
+ ,94.0
+ ,21.2
+ ,71.8
+ ,142.7
+ ,38.9
+ ,55.5
+ ,7.8
+ ,35.5
+ ,82.6
+ ,23.2
+ ,65.4
+ ,32.5
+ ,24.5
+ ,11.8
+ ,46.1
+ ,69.5
+ ,67.0
+ ,13.8
+ ,18.8
+ ,16.5
+ ,11.0
+ ,39.3
+ ,18.1
+ ,70.2
+ ,9.5
+ ,53.8
+ ,47.2
+ ,37.3
+ ,22.2
+ ,27.7
+ ,6.2
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+ ,21.7
+ ,51.9
+ ,18.0
+ ,26.1
+ ,21.8
+ ,6.5
+ ,24.2
+ ,41.8
+ ,34.6
+ ,26.7
+ ,49.0
+ ,28.9
+ ,94.2
+ ,22.6
+ ,53.7
+ ,40.2
+ ,20.0
+ ,49.1
+ ,3.0
+ ,94.7
+ ,29.6
+ ,27.9
+ ,21.5
+ ,22.7
+ ,27.3
+ ,4.7
+ ,86.9
+ ,13.0
+ ,26.5
+ ,45.2
+ ,15.8
+ ,48.1
+ ,6.6
+ ,3.7
+ ,28.7
+ ,2.2
+ ,10.7
+ ,24.9
+ ,29.4
+ ,99.4
+ ,70.8
+ ,38.6
+ ,1.2
+ ,35.0
+ ,29.2
+ ,49.6
+ ,41.6
+ ,25.2
+ ,53.6
+ ,19.8
+ ,23.2
+ ,26.2
+ ,17.6
+ ,44.4
+ ,52.1
+ ,53.3
+ ,38.4
+ ,43.7
+ ,41.2
+ ,31.1
+ ,16.4
+ ,21.8
+ ,49.0
+ ,72.9
+ ,14.4
+ ,96.7
+ ,4.8
+ ,40.5
+ ,5.6
+ ,46.9
+ ,93.7
+ ,37.1
+ ,35.4
+ ,7.9
+ ,29.8
+ ,36.0
+ ,18.0
+ ,106.5
+ ,14.2
+ ,6.6
+ ,52.1
+ ,16.0
+ ,12.9
+ ,65.7
+ ,39.9
+ ,69.8
+ ,5.5
+ ,47.7
+ ,3.5
+ ,44.1
+ ,95.1
+ ,70.1
+ ,56.6
+ ,58.5
+ ,70.7
+ ,7.3
+ ,27.4
+ ,37.4
+ ,38.1
+ ,72.4
+ ,101.0
+ ,11.2
+ ,23.5
+ ,80.8
+ ,50.9
+ ,64.9
+ ,28.1
+ ,43.6
+ ,69.8
+ ,49.1
+ ,30.2
+ ,42.8
+ ,62.0
+ ,15.6
+ ,61.7
+ ,25.8
+ ,20.1
+ ,4.2
+ ,35.3
+ ,128.8
+ ,7.9
+ ,43.5
+ ,39.7
+ ,41.5
+ ,63.1
+ ,71.0
+ ,6.2
+ ,11.1
+ ,20.5
+ ,43.9
+ ,90.9
+ ,6.3
+ ,48.0
+ ,90.0
+ ,11.9
+ ,8.6
+ ,11.6
+ ,35.0
+ ,3.6
+ ,1.1
+ ,42.9
+ ,44.6
+ ,29.3
+ ,57.0
+ ,31.9
+ ,15.0
+ ,9.1
+ ,33.2
+ ,47.3
+ ,4.0
+ ,42.9
+ ,11.3
+ ,41.9
+ ,41.9
+ ,3.5
+ ,2.6
+ ,14.5
+ ,79.3
+ ,9.3
+ ,40.0
+ ,101.5
+ ,3.6
+ ,14.9
+ ,42.8
+ ,57.6
+ ,45.2
+ ,4.7
+ ,28.9
+ ,5.0
+ ,60.2
+ ,29.7
+ ,1.9
+ ,77.7
+ ,20.5
+ ,100.4
+ ,55.6
+ ,66.1
+ ,55.6
+ ,13.7
+ ,36.4
+ ,74.2
+ ,66.9
+ ,1.7
+ ,98.3
+ ,32.4
+ ,72.4
+ ,3.7
+ ,13.6
+ ,75.0
+ ,89.6
+ ,44.8
+ ,74.1
+ ,44.0
+ ,51.3
+ ,14.4
+ ,26.3
+ ,9.6
+ ,43.2
+ ,40.6
+ ,30.1
+ ,16.5
+ ,52.9
+ ,17.6
+ ,70.1
+ ,32.2
+ ,3.1
+ ,12.4
+ ,74.5
+ ,23.6
+ ,5.5
+ ,95.1
+ ,34.6
+ ,21.8
+ ,140.9
+ ,9.9
+ ,6.0
+ ,34.6
+ ,15.4
+ ,58.3
+ ,59.3
+ ,0.9
+ ,78.8
+ ,42.9
+ ,57.0
+ ,6.3
+ ,46.4
+ ,4.9
+ ,31.5
+ ,28.6
+ ,13.3
+ ,77.6
+ ,36.4
+ ,21.8
+ ,59.7
+ ,2.3
+ ,39.5
+ ,38.8
+ ,62.7
+ ,57.4
+ ,38.6
+ ,28.2
+ ,52.1
+ ,48.1
+ ,3.7
+ ,20.8
+ ,37.0
+ ,21.0
+ ,31.7
+ ,41.5
+ ,18.8
+ ,70.7
+ ,45.1
+ ,96.9
+ ,35.1
+ ,27.0
+ ,134.5
+ ,27.1
+ ,14.3
+ ,24.1
+ ,26.3
+ ,35.9
+ ,25.9
+ ,21.1
+ ,5.6
+ ,38.9
+ ,42.5
+ ,5.8
+ ,40.8
+ ,31.0
+ ,6.7
+ ,7.8
+ ,43.3
+ ,82.5
+ ,84.3
+ ,23.8
+ ,54.8
+ ,34.1
+ ,93.3
+ ,104.9
+ ,89.6
+ ,80.6
+ ,70.4)
> par3 = '512'
> par2 = 'no'
> par1 = '0'
> ylab = 'Density'
> xlab = 'Value'
> par3 <- '512'
> par2 <- 'no'
> par1 <- '0'
> #'GNU S' R Code compiled by R2WASP v. 1.2.327 (Sat, 26 Sep 2015 10:34:04 +0100)
> #Author: root
> #To cite this work: Wessa, P. (2015), Kernel Density Estimation (v1.0.12) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_density.wasp/
> #Source of accompanying publication: http://www.xycoon.com/density_trace.htm
> #
> if (par1 == '0') bw <- 'nrd0'
> if (par1 != '0') bw <- as.numeric(par1)
> par3 <- as.numeric(par3)
> mydensity <- array(NA, dim=c(par3,8))
> postscript(file="/var/wessaorg/rcomp/tmp/19x5i1488590725.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> mydensity1<-density(x,bw=bw,kernel='gaussian',na.rm=TRUE)
> mydensity[,8] = signif(mydensity1$x,3)
> mydensity[,1] = signif(mydensity1$y,3)
> plot(mydensity1,main='Gaussian Kernel',xlab=xlab,ylab=ylab)
> grid()
> dev.off()
null device 
          1 
> mydensity1

Call:
	density.default(x = x, bw = bw, kernel = "gaussian", na.rm = TRUE)

Data: x (2590 obs.);	Bandwidth 'bw' = 4.954

       x                y            
 Min.   :-14.76   Min.   :3.520e-07  
 1st Qu.: 33.04   1st Qu.:1.141e-04  
 Median : 80.85   Median :2.725e-03  
 Mean   : 80.85   Mean   :5.224e-03  
 3rd Qu.:128.66   3rd Qu.:1.199e-02  
 Max.   :176.46   Max.   :1.498e-02  
> postscript(file="/var/wessaorg/rcomp/tmp/2b1km1488590725.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> mydensity2<-density(x,bw=bw,kernel='epanechnikov',na.rm=TRUE)
> mydensity[,2] = signif(mydensity2$y,3)
> plot(mydensity2,main='Epanechnikov Kernel',xlab=xlab,ylab=ylab)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/339or1488590725.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> mydensity3<-density(x,bw=bw,kernel='rectangular',na.rm=TRUE)
> mydensity[,3] = signif(mydensity3$y,3)
> plot(mydensity3,main='Rectangular Kernel',xlab=xlab,ylab=ylab)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/4jubu1488590725.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> mydensity4<-density(x,bw=bw,kernel='triangular',na.rm=TRUE)
> mydensity[,4] = signif(mydensity4$y,3)
> plot(mydensity4,main='Triangular Kernel',xlab=xlab,ylab=ylab)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/5mad21488590725.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> mydensity5<-density(x,bw=bw,kernel='biweight',na.rm=TRUE)
> mydensity[,5] = signif(mydensity5$y,3)
> plot(mydensity5,main='Biweight Kernel',xlab=xlab,ylab=ylab)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/6rfva1488590725.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> mydensity6<-density(x,bw=bw,kernel='cosine',na.rm=TRUE)
> mydensity[,6] = signif(mydensity6$y,3)
> plot(mydensity6,main='Cosine Kernel',xlab=xlab,ylab=ylab)
> grid()
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/7bbgj1488590725.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> mydensity7<-density(x,bw=bw,kernel='optcosine',na.rm=TRUE)
> mydensity[,7] = signif(mydensity7$y,3)
> plot(mydensity7,main='Optcosine Kernel',xlab=xlab,ylab=ylab)
> grid()
> dev.off()
null device 
          1 
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
> 
> ab<-table.start()
> ab<-table.row.start(ab)
> ab<-table.element(ab,'Properties of Density Trace',2,TRUE)
> ab<-table.row.end(ab)
> ab<-table.row.start(ab)
> ab<-table.element(ab,'Bandwidth',header=TRUE)
> ab<-table.element(ab,mydensity1$bw)
> ab<-table.row.end(ab)
> ab<-table.row.start(ab)
> ab<-table.element(ab,'#Observations',header=TRUE)
> ab<-table.element(ab,mydensity1$n)
> ab<-table.row.end(ab)
> ab<-table.end(ab)
> a <- ab
> table.save(a,file="/var/wessaorg/rcomp/tmp/8k7lk1488590725.tab") 
> b<-table.start()
> b<-table.row.start(b)
> b<-table.element(b,'Maximum Density Values',3,TRUE)
> b<-table.row.end(b)
> b<-table.row.start(b)
> b<-table.element(b,'Kernel',1,TRUE)
> b<-table.element(b,'x-value',1,TRUE)
> b<-table.element(b,'max. density',1,TRUE)
> b<-table.row.end(b)
> b<-table.row.start(b)
> b<-table.element(b,'Gaussian',1,TRUE)
> b<-table.element(b,mydensity1$x[mydensity1$y==max(mydensity1$y)],1)
> b<-table.element(b,mydensity1$y[mydensity1$y==max(mydensity1$y)],1)
> b<-table.row.end(b)
> b<-table.row.start(b)
> b<-table.element(b,'Epanechnikov',1,TRUE)
> b<-table.element(b,mydensity2$x[mydensity2$y==max(mydensity2$y)],1)
> b<-table.element(b,mydensity2$y[mydensity2$y==max(mydensity2$y)],1)
> b<-table.row.end(b)
> b<-table.row.start(b)
> b<-table.element(b,'Rectangular',1,TRUE)
> b<-table.element(b,mydensity3$x[mydensity3$y==max(mydensity3$y)],1)
> b<-table.element(b,mydensity3$y[mydensity3$y==max(mydensity3$y)],1)
> b<-table.row.end(b)
> b<-table.row.start(b)
> b<-table.element(b,'Triangular',1,TRUE)
> b<-table.element(b,mydensity4$x[mydensity4$y==max(mydensity4$y)],1)
> b<-table.element(b,mydensity4$y[mydensity4$y==max(mydensity4$y)],1)
> b<-table.row.end(b)
> b<-table.row.start(b)
> b<-table.element(b,'Biweight',1,TRUE)
> b<-table.element(b,mydensity5$x[mydensity5$y==max(mydensity5$y)],1)
> b<-table.element(b,mydensity5$y[mydensity5$y==max(mydensity5$y)],1)
> b<-table.row.end(b)
> b<-table.row.start(b)
> b<-table.element(b,'Cosine',1,TRUE)
> b<-table.element(b,mydensity6$x[mydensity6$y==max(mydensity6$y)],1)
> b<-table.element(b,mydensity6$y[mydensity6$y==max(mydensity6$y)],1)
> b<-table.row.end(b)
> b<-table.row.start(b)
> b<-table.element(b,'Optcosine',1,TRUE)
> b<-table.element(b,mydensity7$x[mydensity7$y==max(mydensity7$y)],1)
> b<-table.element(b,mydensity7$y[mydensity7$y==max(mydensity7$y)],1)
> b<-table.row.end(b)
> b<-table.end(b)
> a <- b[1]
> table.save(a,file="/var/wessaorg/rcomp/tmp/92jwi1488590725.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Kernel Density Values',8,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'x-value',1,TRUE)
> a<-table.element(a,'Gaussian',1,TRUE)
> a<-table.element(a,'Epanechnikov',1,TRUE)
> a<-table.element(a,'Rectangular',1,TRUE)
> a<-table.element(a,'Triangular',1,TRUE)
> a<-table.element(a,'Biweight',1,TRUE)
> a<-table.element(a,'Cosine',1,TRUE)
> a<-table.element(a,'Optcosine',1,TRUE)
> a<-table.row.end(a)
> if (par2=='yes') {
+ for(i in 1:par3) {
+ a<-table.row.start(a)
+ a<-table.element(a,mydensity[i,8],1,TRUE)
+ for(j in 1:7) {
+ a<-table.element(a,mydensity[i,j],1)
+ }
+ a<-table.row.end(a)
+ }
+ } else {
+ a<-table.row.start(a)
+ a<-table.element(a,'Kernel Density Values are not shown',8)
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/10hytw1488590725.tab") 
> 
> try(system("convert tmp/19x5i1488590725.ps tmp/19x5i1488590725.png",intern=TRUE))
character(0)
> try(system("convert tmp/2b1km1488590725.ps tmp/2b1km1488590725.png",intern=TRUE))
character(0)
> try(system("convert tmp/339or1488590725.ps tmp/339or1488590725.png",intern=TRUE))
character(0)
> try(system("convert tmp/4jubu1488590725.ps tmp/4jubu1488590725.png",intern=TRUE))
character(0)
> try(system("convert tmp/5mad21488590725.ps tmp/5mad21488590725.png",intern=TRUE))
character(0)
> try(system("convert tmp/6rfva1488590725.ps tmp/6rfva1488590725.png",intern=TRUE))
character(0)
> try(system("convert tmp/7bbgj1488590725.ps tmp/7bbgj1488590725.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  3.788   0.188   4.039