R version 2.9.0 (2009-04-17) Copyright (C) 2009 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. 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 <- array(list(1.4562 + ,8.1000 + ,7.9000 + ,8.7000 + ,104.5000 + ,2443.2700 + ,16.2000 + ,16.3000 + ,3.0000 + ,-12.0000 + ,65.0000 + ,1.4268 + ,8.3000 + ,8.1000 + ,8.9000 + ,89.1000 + ,2293.4100 + ,12.5000 + ,13.6000 + ,6.0000 + ,-11.0000 + ,55.0000 + ,1.4088 + ,8.1000 + ,8.3000 + ,8.9000 + ,82.6000 + ,2070.8300 + ,14.8000 + ,14.3000 + ,7.0000 + ,-11.0000 + ,57.0000 + ,1.4016 + ,7.4000 + ,8.1000 + ,8.1000 + ,102.7000 + ,2029.6000 + ,15.4000 + ,15.5000 + ,-4.0000 + ,-17.0000 + ,57.0000 + ,1.3650 + ,7.3000 + ,7.4000 + ,8.0000 + ,91.8000 + ,2052.0200 + ,13.6000 + ,13.9000 + ,-5.0000 + ,-18.0000 + ,57.0000 + ,1.3190 + ,7.7000 + ,7.3000 + ,8.3000 + ,94.1000 + ,1864.4400 + ,14.2000 + ,14.3000 + ,-7.0000 + ,-19.0000 + ,65.0000 + ,1.3050 + ,8.0000 + ,7.7000 + ,8.5000 + ,103.1000 + ,1670.0700 + ,15.0000 + ,15.8000 + ,-10.0000 + ,-22.0000 + ,69.0000 + ,1.2785 + ,8.0000 + ,8.0000 + ,8.7000 + ,93.2000 + ,1810.9900 + ,14.1000 + ,14.5000 + ,-21.0000 + ,-24.0000 + ,70.0000 + ,1.3239 + ,7.7000 + ,8.0000 + ,8.6000 + ,91.0000 + ,1905.4100 + ,13.7000 + ,15.1000 + ,-22.0000 + ,-24.0000 + ,71.0000 + ,1.3449 + ,6.9000 + ,7.7000 + ,8.3000 + ,94.3000 + ,1862.8300 + ,14.4000 + ,15.8000 + ,-16.0000 + ,-20.0000 + ,71.0000 + ,1.2732 + ,6.6000 + ,6.9000 + ,7.9000 + ,99.4000 + ,2014.4500 + ,15.6000 + ,17.2000 + ,-25.0000 + ,-25.0000 + ,73.0000 + ,1.3322 + ,6.9000 + ,6.6000 + ,7.9000 + ,115.7000 + ,2197.8200 + ,19.7000 + ,20.4000 + ,-22.0000 + ,-22.0000 + ,68.0000 + ,1.4369 + ,7.5000 + ,6.9000 + ,8.1000 + ,116.8000 + ,2962.3400 + ,20.4000 + ,21.3000 + ,-22.0000 + ,-17.0000 + ,65.0000 + ,1.4975 + ,7.9000 + ,7.5000 + ,8.3000 + ,99.8000 + ,3047.0300 + ,16.1000 + ,18.2000 + ,-19.0000 + ,-9.0000 + ,57.0000 + ,1.5770 + ,7.7000 + ,7.9000 + ,8.1000 + ,96.0000 + ,3032.6000 + ,20.1000 + ,20.2000 + ,-21.0000 + ,-11.0000 + ,41.0000 + ,1.5553 + ,6.5000 + ,7.7000 + ,7.4000 + ,115.9000 + ,3504.3700 + ,20.6000 + ,21.1000 + ,-31.0000 + ,-13.0000 + ,21.0000 + ,1.5557 + ,6.1000 + ,6.5000 + ,7.3000 + ,109.1000 + ,3801.0600 + ,19.3000 + ,19.7000 + ,-28.0000 + ,-11.0000 + ,21.0000 + ,1.5750 + ,6.4000 + ,6.1000 + ,7.7000 + ,117.3000 + ,3857.6200 + ,20.5000 + ,21.5000 + ,-23.0000 + ,-9.0000 + ,17.0000 + ,1.5527 + ,6.8000 + ,6.4000 + ,8.0000 + ,109.8000 + ,3674.4000 + ,19.2000 + ,20.2000 + ,-17.0000 + ,-7.0000 + ,9.0000 + ,1.4748 + ,7.1000 + ,6.8000 + ,8.0000 + ,112.8000 + ,3720.9800 + ,19.0000 + ,19.0000 + ,-12.0000 + ,-3.0000 + ,11.0000 + ,1.4718 + ,7.3000 + ,7.1000 + ,7.7000 + ,110.7000 + ,3844.4900 + ,18.7000 + ,20.2000 + ,-14.0000 + ,-3.0000 + ,6.0000 + ,1.4570 + ,7.2000 + ,7.3000 + ,6.9000 + ,100.0000 + ,4116.6800 + ,16.5000 + ,18.0000 + ,-18.0000 + ,-6.0000 + ,-2.0000 + ,1.4684 + ,7.0000 + ,7.2000 + ,6.6000 + ,113.3000 + ,4105.1800 + ,19.0000 + ,19.5000 + ,-16.0000 + ,-4.0000 + ,0.0000 + ,1.4227 + ,7.0000 + ,7.0000 + ,6.9000 + ,122.4000 + ,4435.2300 + ,20.5000 + ,20.3000 + ,-22.0000 + ,-8.0000 + ,5.0000 + ,1.3896 + ,7.0000 + ,7.0000 + ,7.5000 + ,112.5000 + ,4296.4900 + ,18.4000 + ,18.0000 + ,-9.0000 + ,-1.0000 + ,3.0000 + ,1.3622 + ,7.3000 + ,7.0000 + ,7.9000 + ,104.2000 + ,4202.5200 + ,16.2000 + ,16.4000 + ,-10.0000 + ,-2.0000 + ,7.0000 + ,1.3716 + ,7.5000 + ,7.3000 + ,7.7000 + ,92.5000 + ,4562.8400 + ,18.1000 + ,17.8000 + ,-10.0000 + ,-2.0000 + ,4.0000 + ,1.3419 + ,7.2000 + ,7.5000 + ,6.5000 + ,117.2000 + ,4621.4000 + ,19.3000 + ,18.5000 + ,0.0000 + ,-1.0000 + ,8.0000 + ,1.3511 + ,7.7000 + ,7.2000 + ,6.1000 + ,109.3000 + ,4696.9600 + ,18.3000 + ,18.2000 + ,3.0000 + ,1.0000 + ,9.0000 + ,1.3516 + ,8.0000 + ,7.7000 + ,6.4000 + ,106.1000 + ,4591.2700 + ,17.2000 + ,16.7000 + ,2.0000 + ,2.0000 + ,14.0000 + ,1.3242 + ,7.9000 + ,8.0000 + ,6.8000 + ,118.8000 + ,4356.9800 + ,19.6000 + ,19.1000 + ,4.0000 + ,2.0000 + ,12.0000 + ,1.3074 + ,8.0000 + ,7.9000 + ,7.1000 + ,105.3000 + ,4502.6400 + ,17.2000 + ,16.8000 + ,-3.0000 + ,-1.0000 + ,12.0000 + ,1.2999 + ,8.0000 + ,8.0000 + ,7.3000 + ,106.0000 + ,4443.9100 + ,17.4000 + ,17.5000 + ,0.0000 + ,1.0000 + ,7.0000 + ,1.3213 + ,7.9000 + ,8.0000 + ,7.2000 + ,102.0000 + ,4290.8900 + ,16.0000 + ,16.2000 + ,-1.0000 + ,-1.0000 + ,15.0000 + ,1.2881 + ,7.9000 + ,7.9000 + ,7.0000 + ,112.9000 + ,4199.7500 + ,18.5000 + ,17.9000 + ,-7.0000 + ,-8.0000 + ,14.0000 + ,1.2611 + ,8.0000 + ,7.9000 + ,7.0000 + ,116.5000 + ,4138.5200 + ,18.4000 + ,17.7000 + ,2.0000 + ,1.0000 + ,19.0000 + ,1.2727 + ,8.1000 + ,8.0000 + ,7.0000 + ,114.8000 + ,3970.1000 + ,18.2000 + ,17.2000 + ,3.0000 + ,2.0000 + ,39.0000 + ,1.2811 + ,8.1000 + ,8.1000 + ,7.3000 + ,100.5000 + ,3862.2700 + ,14.9000 + ,15.7000 + ,-3.0000 + ,-2.0000 + ,12.0000 + ,1.2684 + ,8.2000 + ,8.1000 + ,7.5000 + ,85.4000 + ,3701.6100 + ,16.3000 + ,15.2000 + ,-5.0000 + ,-2.0000 + ,11.0000 + ,1.2650 + ,8.0000 + ,8.2000 + ,7.2000 + ,114.6000 + ,3570.1200 + ,18.3000 + ,17.7000 + ,0.0000 + ,-2.0000 + ,17.0000 + ,1.2770 + ,8.3000 + ,8.0000 + ,7.7000 + ,109.9000 + ,3801.0600 + ,18.0000 + ,17.4000 + ,-3.0000 + ,-2.0000 + ,16.0000 + ,1.2271 + ,8.5000 + ,8.3000 + ,8.0000 + ,100.7000 + ,3895.5100 + ,15.9000 + ,15.9000 + ,-7.0000 + ,-6.0000 + ,25.0000 + ,1.2020 + ,8.6000 + ,8.5000 + ,7.9000 + ,115.5000 + ,3917.9600 + ,19.6000 + ,19.7000 + ,-7.0000 + ,-4.0000 + ,24.0000 + ,1.1938 + ,8.7000 + ,8.6000 + ,8.0000 + ,100.7000 + ,3813.0600 + ,16.6000 + ,16.7000 + ,-7.0000 + ,-5.0000 + ,28.0000 + ,1.2103 + ,8.7000 + ,8.7000 + ,8.0000 + ,99.0000 + ,3667.0300 + ,16.2000 + ,16.9000 + ,-4.0000 + ,-2.0000 + ,25.0000 + ,1.1856 + ,8.5000 + ,8.7000 + ,7.9000 + ,102.3000 + ,3494.1700 + ,16.6000 + ,18.0000 + ,-3.0000 + ,-1.0000 + ,31.0000 + ,1.1786 + ,8.4000 + ,8.5000 + ,7.9000 + ,108.8000 + ,3363.9900 + ,17.5000 + ,17.6000 + ,-6.0000 + ,-5.0000 + ,24.0000 + ,1.2015 + ,8.5000 + ,8.4000 + ,8.0000 + ,105.9000 + ,3295.3200 + ,16.2000 + ,15.2000 + ,-10.0000 + ,-9.0000 + ,24.0000 + ,1.2256 + ,8.7000 + ,8.5000 + ,8.1000 + ,113.2000 + ,3277.0100 + ,17.5000 + ,16.5000 + ,-10.0000 + ,-8.0000 + ,33.0000 + ,1.2292 + ,8.7000 + ,8.7000 + ,8.1000 + ,95.7000 + ,3257.1600 + ,13.8000 + ,14.7000 + ,-23.0000 + ,-14.0000 + ,37.0000 + ,1.2037 + ,8.6000 + ,8.7000 + ,8.2000 + ,80.9000 + ,3161.6900 + ,14.9000 + ,14.1000 + ,-13.0000 + ,-10.0000 + ,35.0000 + ,1.2165 + ,7.9000 + ,8.6000 + ,8.0000 + ,113.9000 + ,3097.3100 + ,17.2000 + ,16.9000 + ,-18.0000 + ,-11.0000 + ,37.0000 + ,1.2694 + ,8.1000 + ,7.9000 + ,8.3000 + ,98.1000 + ,3061.2600 + ,15.6000 + ,15.2000 + ,-16.0000 + ,-11.0000 + ,38.0000 + ,1.2938 + ,8.2000 + ,8.1000 + ,8.5000 + ,102.8000 + ,3119.3100 + ,16.2000 + ,15.4000 + ,-15.0000 + ,-11.0000 + ,42.0000 + ,1.3201 + ,8.5000 + ,8.2000 + ,8.6000 + ,104.7000 + ,3106.2200 + ,17.4000 + ,16.8000 + ,-5.0000 + ,-5.0000 + ,43.0000 + ,1.3014 + ,8.6000 + ,8.5000 + ,8.7000 + ,95.9000 + ,3080.5800 + ,15.1000 + ,14.8000 + ,2.0000 + ,-2.0000 + ,44.0000 + ,1.3119 + ,8.5000 + ,8.6000 + ,8.7000 + ,94.6000 + ,2981.8500 + ,14.5000 + ,14.1000 + ,-2.0000 + ,-3.0000 + ,32.0000 + ,1.3408 + ,8.3000 + ,8.5000 + ,8.5000 + ,101.6000 + ,2921.4400 + ,15.1000 + ,15.0000 + ,-4.0000 + ,-6.0000 + ,32.0000 + ,1.2991 + ,8.2000 + ,8.3000 + ,8.4000 + ,103.9000 + ,2849.2700 + ,15.5000 + ,14.8000 + ,-4.0000 + ,-6.0000 + ,37.0000 + ,1.2490 + ,8.7000 + ,8.2000 + ,8.5000 + ,110.3000 + ,2756.7600 + ,15.9000 + ,15.0000 + ,-6.0000 + ,-7.0000 + ,38.0000 + ,1.2218 + ,9.3000 + ,8.7000 + ,8.7000 + ,114.1000 + ,2645.6400 + ,15.9000 + ,15.1000 + ,-7.0000 + ,-6.0000 + ,39.0000 + ,1.2176 + ,9.3000 + ,9.3000 + ,8.7000 + ,96.8000 + ,2497.8400 + ,12.3000 + ,12.8000 + ,0.0000 + ,-2.0000 + ,38.0000 + ,1.2266 + ,8.8000 + ,9.3000 + ,8.6000 + ,87.4000 + ,2448.0500 + ,14.4000 + ,13.0000 + ,1.0000 + ,-2.0000 + ,39.0000 + ,1.2138 + ,7.4000 + ,8.8000 + ,7.9000 + ,111.4000 + ,2454.6200 + ,16.0000 + ,15.7000 + ,-3.0000 + ,-4.0000 + ,30.0000 + ,1.2007 + ,7.2000 + ,7.4000 + ,8.1000 + ,97.4000 + ,2407.6000 + ,13.9000 + ,12.8000 + ,6.0000 + ,0.0000 + ,28.0000 + ,1.1985 + ,7.5000 + ,7.2000 + ,8.2000 + ,102.9000 + ,2472.8100 + ,14.7000 + ,13.9000 + ,-2.0000 + ,-6.0000 + ,31.0000 + ,1.2262 + ,8.3000 + ,7.5000 + ,8.5000 + ,112.7000 + ,2408.6400 + ,16.2000 + ,15.4000 + ,2.0000 + ,-4.0000 + ,28.0000 + ,1.2646 + ,8.8000 + ,8.3000 + ,8.6000 + ,97.0000 + ,2440.2500 + ,13.8000 + ,13.2000 + ,5.0000 + ,-3.0000 + ,38.0000 + ,1.2613 + ,8.9000 + ,8.8000 + ,8.5000 + ,95.1000 + ,2350.4400 + ,13.2000 + ,12.7000 + ,7.0000 + ,-1.0000 + ,37.0000 + ,1.2286 + ,8.6000 + ,8.9000 + ,8.3000 + ,96.9000 + ,2196.7200 + ,13.5000 + ,13.5000 + ,4.0000 + ,-3.0000 + ,34.0000 + ,1.1702 + ,8.4000 + ,8.6000 + ,8.2000 + ,98.6000 + ,2174.5600 + ,13.5000 + ,12.8000 + ,0.0000 + ,-6.0000 + ,32.0000 + ,1.1692 + ,8.4000 + ,8.4000 + ,8.7000 + ,111.7000 + ,2120.8800 + ,15.0000 + ,13.9000 + ,0.0000 + ,-6.0000 + ,33.0000 + ,1.1222 + ,8.4000 + ,8.4000 + ,9.3000 + ,109.8000 + ,2093.4800 + ,14.5000 + ,13.3000 + ,-13.0000 + ,-15.0000 + ,39.0000 + ,1.1139 + ,8.4000 + ,8.4000 + ,9.3000 + ,89.9000 + ,2061.4100 + ,10.5000 + ,10.7000 + ,-2.0000 + ,-5.0000 + ,42.0000 + ,1.1372 + ,8.3000 + ,8.4000 + ,8.8000 + ,87.4000 + ,1969.6000 + ,13.7000 + ,12.3000 + ,-10.0000 + ,-11.0000 + ,57.0000 + ,1.1663 + ,7.6000 + ,8.3000 + ,7.4000 + ,104.5000 + ,1959.6700 + ,13.9000 + ,12.9000 + ,-12.0000 + ,-13.0000 + ,36.0000 + ,1.1582 + ,7.6000 + ,7.6000 + ,7.2000 + ,98.1000 + ,1910.4300 + ,13.4000 + ,12.5000 + ,-9.0000 + ,-10.0000 + ,42.0000 + ,1.0848 + ,7.9000 + ,7.6000 + ,7.5000 + ,102.7000 + ,1833.4200 + ,14.0000 + ,13.0000 + ,-4.0000 + ,-9.0000 + ,49.0000 + ,1.0807 + ,8.0000 + ,7.9000 + ,8.3000 + ,105.4000 + ,1635.2500 + ,14.3000 + ,13.9000 + ,-11.0000 + ,-11.0000 + ,44.0000 + ,1.0773 + ,8.2000 + ,8.0000 + ,8.8000 + ,97.0000 + ,1765.9000 + ,13.3000 + ,13.1000 + ,-28.0000 + ,-18.0000 + ,44.0000 + ,1.0622 + ,8.3000 + ,8.2000 + ,8.9000 + ,97.4000 + ,1946.8100 + ,13.2000 + ,13.1000 + ,-19.0000 + ,-13.0000 + ,43.0000 + ,1.0183 + ,8.2000 + ,8.3000 + ,8.6000 + ,92.0000 + ,1995.3700 + ,12.6000 + ,13.0000 + ,-16.0000 + ,-9.0000 + ,50.0000 + ,1.0014 + ,8.1000 + ,8.2000 + ,8.4000 + ,101.7000 + ,2042.0000 + ,13.7000 + ,12.8000 + ,-8.0000 + ,-8.0000 + ,45.0000 + ,0.9811 + ,8.0000 + ,8.1000 + ,8.4000 + ,112.6000 + ,1940.4900 + ,15.6000 + ,14.2000 + ,-1.0000 + ,-4.0000 + ,40.0000 + ,0.9808 + ,7.8000 + ,8.0000 + ,8.4000 + ,106.9000 + ,2065.8100 + ,14.4000 + ,13.0000 + ,-2.0000 + ,-3.0000 + ,38.0000 + ,0.9778 + ,7.6000 + ,7.8000 + ,8.4000 + ,92.1000 + ,2214.9500 + ,11.0000 + ,11.2000 + ,-4.0000 + ,-3.0000 + ,29.0000 + ,0.9922 + ,7.5000 + ,7.6000 + ,8.3000 + ,86.0000 + ,2304.9800 + ,13.7000 + ,12.1000 + ,-5.0000 + ,-3.0000 + ,27.0000 + ,0.9554 + ,6.8000 + ,7.5000 + ,7.6000 + ,104.7000 + ,2555.2800 + ,13.8000 + ,12.9000 + ,0.0000 + ,-1.0000 + ,27.0000 + ,0.9170 + ,6.9000 + ,6.8000 + ,7.6000 + ,102.0000 + ,2799.4300 + ,14.3000 + ,13.2000 + ,5.0000 + ,0.0000 + ,27.0000 + ,0.8858 + ,7.1000 + ,6.9000 + ,7.9000 + ,103.1000 + ,2811.7000 + ,14.0000 + ,13.2000 + ,5.0000 + ,1.0000 + ,32.0000 + ,0.8758 + ,7.3000 + ,7.1000 + ,8.0000 + ,106.0000 + ,2735.7000 + ,14.6000 + ,13.5000 + ,2.0000 + ,0.0000 + ,24.0000 + ,0.8700 + ,7.4000 + ,7.3000 + ,8.2000 + ,96.1000 + ,2745.8800 + ,13.1000 + ,12.4000 + ,6.0000 + ,2.0000 + ,22.0000 + ,0.8833 + ,7.6000 + ,7.4000 + ,8.3000 + ,96.2000 + ,2720.2500 + ,13.2000 + ,12.4000 + ,3.0000 + ,1.0000 + ,22.0000 + ,0.8924 + ,7.6000 + ,7.6000 + ,8.2000 + ,90.7000 + ,2638.5300 + ,11.6000 + ,11.6000 + ,1.0000 + ,-1.0000 + ,23.0000 + ,0.8883 + ,7.5000 + ,7.6000 + ,8.1000 + ,102.3000 + ,2659.8100 + ,13.3000 + ,12.6000 + ,-9.0000 + ,-8.0000 + ,23.0000 + ,0.9059 + ,7.5000 + ,7.5000 + ,8.0000 + ,109.4000 + ,2641.6500 + ,14.4000 + ,13.1000 + ,-26.0000 + ,-18.0000 + ,28.0000 + ,0.9111 + ,6.8000 + ,7.5000 + ,7.8000 + ,101.0000 + ,2604.4200 + ,13.3000 + ,12.3000 + ,-25.0000 + ,-14.0000 + ,36.0000 + ,0.9005 + ,6.4000 + ,6.8000 + ,7.6000 + ,94.7000 + ,2892.6300 + ,11.3000 + ,11.4000 + ,-13.0000 + ,-4.0000 + ,60.0000 + ,0.8607 + ,6.2000 + ,6.4000 + ,7.5000 + ,81.0000 + ,2915.0300 + ,13.2000 + ,11.8000 + ,-6.0000 + ,0.0000 + ,43.0000 + ,0.8532 + ,6.0000 + ,6.2000 + ,6.8000 + ,106.2000 + ,2845.2600 + ,14.1000 + ,13.4000 + ,-1.0000 + ,4.0000 + ,23.0000 + ,0.8742 + ,6.3000 + ,6.0000 + ,6.9000 + ,101.9000 + ,2794.8300 + ,14.0000 + ,13.6000 + ,1.0000 + ,4.0000 + ,15.0000 + ,0.8920 + ,6.3000 + ,6.3000 + ,7.1000 + ,96.4000 + ,2848.9600 + ,12.9000 + ,12.9000 + ,1.0000 + ,3.0000 + ,7.0000 + ,0.9095 + ,6.1000 + ,6.3000 + ,7.3000 + ,110.4000 + ,2833.1800 + ,15.2000 + ,14.5000 + ,-2.0000 + ,3.0000 + ,6.0000 + ,0.9217 + ,6.1000 + ,6.1000 + ,7.4000 + ,100.5000 + ,2995.5500 + ,13.6000 + ,13.3000 + ,2.0000 + ,7.0000 + ,8.0000 + ,0.9383 + ,6.3000 + ,6.1000 + ,7.6000 + ,98.8000 + ,2987.1000 + ,13.7000 + ,13.5000 + ,3.0000 + ,8.0000 + ,5.0000) + ,dim=c(11 + ,105) + ,dimnames=list(c('WSK' + ,'WER' + ,'WER(d-1)' + ,'WER(d-12)' + ,'INP' + ,'BE2' + ,'Uit' + ,'INV' + ,'CE-AES' + ,'CE-CV' + ,'CE-WER') + ,1:105)) > y <- array(NA,dim=c(11,105),dimnames=list(c('WSK','WER','WER(d-1)','WER(d-12)','INP','BE2','Uit','INV','CE-AES','CE-CV','CE-WER'),1:105)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par4 = 'yes' > par3 = '3' > par2 = 'equal' > par1 = '2' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Dr. Ian E. Holliday > #To cite this work: Ian E. Holliday, 2009, YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: > #Technical description: > library(party) Loading required package: survival Loading required package: splines Loading required package: grid Loading required package: modeltools Loading required package: stats4 Loading required package: coin Loading required package: mvtnorm Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric Loading required package: sandwich Loading required package: strucchange Loading required package: vcd Loading required package: MASS Loading required package: colorspace > library(Hmisc) Attaching package: 'Hmisc' The following object(s) are masked from package:survival : untangle.specials The following object(s) are masked from package:base : format.pval, round.POSIXt, trunc.POSIXt, units > par1 <- as.numeric(par1) > par3 <- as.numeric(par3) > x <- data.frame(t(y)) > is.data.frame(x) [1] TRUE > x <- x[!is.na(x[,par1]),] > k <- length(x[1,]) > n <- length(x[,1]) > colnames(x)[par1] [1] "WER" > x[,par1] [1] 8.1 8.3 8.1 7.4 7.3 7.7 8.0 8.0 7.7 6.9 6.6 6.9 7.5 7.9 7.7 6.5 6.1 6.4 [19] 6.8 7.1 7.3 7.2 7.0 7.0 7.0 7.3 7.5 7.2 7.7 8.0 7.9 8.0 8.0 7.9 7.9 8.0 [37] 8.1 8.1 8.2 8.0 8.3 8.5 8.6 8.7 8.7 8.5 8.4 8.5 8.7 8.7 8.6 7.9 8.1 8.2 [55] 8.5 8.6 8.5 8.3 8.2 8.7 9.3 9.3 8.8 7.4 7.2 7.5 8.3 8.8 8.9 8.6 8.4 8.4 [73] 8.4 8.4 8.3 7.6 7.6 7.9 8.0 8.2 8.3 8.2 8.1 8.0 7.8 7.6 7.5 6.8 6.9 7.1 [91] 7.3 7.4 7.6 7.6 7.5 7.5 6.8 6.4 6.2 6.0 6.3 6.3 6.1 6.1 6.3 > if (par2 == 'kmeans') { + cl <- kmeans(x[,par1], par3) + print(cl) + clm <- matrix(cbind(cl$centers,1:par3),ncol=2) + clm <- clm[sort.list(clm[,1]),] + for (i in 1:par3) { + cl$cluster[cl$cluster==clm[i,2]] <- paste('C',i,sep='') + } + cl$cluster <- as.factor(cl$cluster) + print(cl$cluster) + x[,par1] <- cl$cluster + } > if (par2 == 'quantiles') { + x[,par1] <- cut2(x[,par1],g=par3) + } > if (par2 == 'hclust') { + hc <- hclust(dist(x[,par1])^2, 'cen') + print(hc) + memb <- cutree(hc, k = par3) + dum <- c(mean(x[memb==1,par1])) + for (i in 2:par3) { + dum <- c(dum, mean(x[memb==i,par1])) + } + hcm <- matrix(cbind(dum,1:par3),ncol=2) + hcm <- hcm[sort.list(hcm[,1]),] + for (i in 1:par3) { + memb[memb==hcm[i,2]] <- paste('C',i,sep='') + } + memb <- as.factor(memb) + print(memb) + x[,par1] <- memb + } > if (par2=='equal') { + ed <- cut(as.numeric(x[,par1]),par3,labels=paste('C',1:par3,sep='')) + x[,par1] <- as.factor(ed) + } > table(x[,par1]) C1 C2 C3 21 54 30 > colnames(x) [1] "WSK" "WER" "WER.d.1." "WER.d.12." "INP" "BE2" [7] "Uit" "INV" "CE.AES" "CE.CV" "CE.WER" > colnames(x)[par1] [1] "WER" > x[,par1] [1] C2 C3 C2 C2 C2 C2 C2 C2 C2 C1 C1 C1 C2 C2 C2 C1 C1 C1 C1 C2 C2 C2 C1 C1 C1 [26] C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C2 C3 C3 C3 C3 C3 C3 C3 C3 C3 C3 [51] C3 C2 C2 C2 C3 C3 C3 C3 C2 C3 C3 C3 C3 C2 C2 C2 C3 C3 C3 C3 C3 C3 C3 C3 C3 [76] C2 C2 C2 C2 C2 C3 C2 C2 C2 C2 C2 C2 C1 C1 C2 C2 C2 C2 C2 C2 C2 C1 C1 C1 C1 [101] C1 C1 C1 C1 C1 Levels: C1 C2 C3 > if (par2 == 'none') { + m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x) + } > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > if (par2 != 'none') { + m <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data = x) + if (par4=='yes') { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'10-Fold Cross Validation',3+2*par3,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'',1,TRUE) + a<-table.element(a,'Prediction (training)',par3+1,TRUE) + a<-table.element(a,'Prediction (testing)',par3+1,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Actual',1,TRUE) + for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE) + a<-table.element(a,'CV',1,TRUE) + for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE) + a<-table.element(a,'CV',1,TRUE) + a<-table.row.end(a) + for (i in 1:10) { + ind <- sample(2, nrow(x), replace=T, prob=c(0.9,0.1)) + m.ct <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data =x[ind==1,]) + if (i==1) { + m.ct.i.pred <- predict(m.ct, newdata=x[ind==1,]) + m.ct.i.actu <- x[ind==1,par1] + m.ct.x.pred <- predict(m.ct, newdata=x[ind==2,]) + m.ct.x.actu <- x[ind==2,par1] + } else { + m.ct.i.pred <- c(m.ct.i.pred,predict(m.ct, newdata=x[ind==1,])) + m.ct.i.actu <- c(m.ct.i.actu,x[ind==1,par1]) + m.ct.x.pred <- c(m.ct.x.pred,predict(m.ct, newdata=x[ind==2,])) + m.ct.x.actu <- c(m.ct.x.actu,x[ind==2,par1]) + } + } + print(m.ct.i.tab <- table(m.ct.i.actu,m.ct.i.pred)) + numer <- 0 + for (i in 1:par3) { + print(m.ct.i.tab[i,i] / sum(m.ct.i.tab[i,])) + numer <- numer + m.ct.i.tab[i,i] + } + print(m.ct.i.cp <- numer / sum(m.ct.i.tab)) + print(m.ct.x.tab <- table(m.ct.x.actu,m.ct.x.pred)) + numer <- 0 + for (i in 1:par3) { + print(m.ct.x.tab[i,i] / sum(m.ct.x.tab[i,])) + numer <- numer + m.ct.x.tab[i,i] + } + print(m.ct.x.cp <- numer / sum(m.ct.x.tab)) + for (i in 1:par3) { + a<-table.row.start(a) + a<-table.element(a,paste('C',i,sep=''),1,TRUE) + for (jjj in 1:par3) a<-table.element(a,m.ct.i.tab[i,jjj]) + a<-table.element(a,round(m.ct.i.tab[i,i]/sum(m.ct.i.tab[i,]),4)) + for (jjj in 1:par3) a<-table.element(a,m.ct.x.tab[i,jjj]) + a<-table.element(a,round(m.ct.x.tab[i,i]/sum(m.ct.x.tab[i,]),4)) + a<-table.row.end(a) + } + a<-table.row.start(a) + a<-table.element(a,'Overall',1,TRUE) + for (jjj in 1:par3) a<-table.element(a,'-') + a<-table.element(a,round(m.ct.i.cp,4)) + for (jjj in 1:par3) a<-table.element(a,'-') + a<-table.element(a,round(m.ct.x.cp,4)) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/www/html/rcomp/tmp/1miuz1293033412.tab") + } + } m.ct.i.pred m.ct.i.actu 1 2 3 1 129 61 0 2 18 433 33 3 0 57 216 [1] 0.6789474 [1] 0.8946281 [1] 0.7912088 [1] 0.8215417 m.ct.x.pred m.ct.x.actu 1 2 3 1 7 13 0 2 1 50 5 3 0 8 19 [1] 0.35 [1] 0.8928571 [1] 0.7037037 [1] 0.7378641 > m Conditional inference tree with 3 terminal nodes Response: as.factor(WER) Inputs: WSK, WER.d.1., WER.d.12., INP, BE2, Uit, INV, CE.AES, CE.CV, CE.WER Number of observations: 105 1) WER.d.1. <= 8.1; criterion = 1, statistic = 68.479 2) WER.d.1. <= 7; criterion = 1, statistic = 34.487 3)* weights = 20 2) WER.d.1. > 7 4)* weights = 50 1) WER.d.1. > 8.1 5)* weights = 35 > postscript(file="/var/www/html/rcomp/tmp/2x9t21293033412.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(m) > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/3x9t21293033412.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,par1] ~ as.factor(where(m)),main='Response by Terminal Node',xlab='Terminal Node',ylab='Response') > dev.off() null device 1 > if (par2 == 'none') { + forec <- predict(m) + result <- as.data.frame(cbind(x[,par1],forec,x[,par1]-forec)) + colnames(result) <- c('Actuals','Forecasts','Residuals') + print(result) + } > if (par2 != 'none') { + print(cbind(as.factor(x[,par1]),predict(m))) + myt <- table(as.factor(x[,par1]),predict(m)) + print(myt) + } [,1] [,2] [1,] 2 2 [2,] 3 2 [3,] 2 3 [4,] 2 2 [5,] 2 2 [6,] 2 2 [7,] 2 2 [8,] 2 2 [9,] 2 2 [10,] 1 2 [11,] 1 1 [12,] 1 1 [13,] 2 1 [14,] 2 2 [15,] 2 2 [16,] 1 2 [17,] 1 1 [18,] 1 1 [19,] 1 1 [20,] 2 1 [21,] 2 2 [22,] 2 2 [23,] 1 2 [24,] 1 1 [25,] 1 1 [26,] 2 1 [27,] 2 2 [28,] 2 2 [29,] 2 2 [30,] 2 2 [31,] 2 2 [32,] 2 2 [33,] 2 2 [34,] 2 2 [35,] 2 2 [36,] 2 2 [37,] 2 2 [38,] 2 2 [39,] 2 2 [40,] 2 3 [41,] 3 2 [42,] 3 3 [43,] 3 3 [44,] 3 3 [45,] 3 3 [46,] 3 3 [47,] 3 3 [48,] 3 3 [49,] 3 3 [50,] 3 3 [51,] 3 3 [52,] 2 3 [53,] 2 2 [54,] 2 2 [55,] 3 3 [56,] 3 3 [57,] 3 3 [58,] 3 3 [59,] 2 3 [60,] 3 3 [61,] 3 3 [62,] 3 3 [63,] 3 3 [64,] 2 3 [65,] 2 2 [66,] 2 2 [67,] 3 2 [68,] 3 3 [69,] 3 3 [70,] 3 3 [71,] 3 3 [72,] 3 3 [73,] 3 3 [74,] 3 3 [75,] 3 3 [76,] 2 3 [77,] 2 2 [78,] 2 2 [79,] 2 2 [80,] 2 2 [81,] 3 3 [82,] 2 3 [83,] 2 3 [84,] 2 2 [85,] 2 2 [86,] 2 2 [87,] 2 2 [88,] 1 2 [89,] 1 1 [90,] 2 1 [91,] 2 2 [92,] 2 2 [93,] 2 2 [94,] 2 2 [95,] 2 2 [96,] 2 2 [97,] 1 2 [98,] 1 1 [99,] 1 1 [100,] 1 1 [101,] 1 1 [102,] 1 1 [103,] 1 1 [104,] 1 1 [105,] 1 1 C1 C2 C3 C1 16 5 0 C2 4 42 8 C3 0 3 27 > postscript(file="/var/www/html/rcomp/tmp/4pisn1293033412.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > if(par2=='none') { + op <- par(mfrow=c(2,2)) + plot(density(result$Actuals),main='Kernel Density Plot of Actuals') + plot(density(result$Residuals),main='Kernel Density Plot of Residuals') + plot(result$Forecasts,result$Actuals,main='Actuals versus Predictions',xlab='Predictions',ylab='Actuals') + plot(density(result$Forecasts),main='Kernel Density Plot of Predictions') + par(op) + } > if(par2!='none') { + plot(myt,main='Confusion Matrix',xlab='Actual',ylab='Predicted') + } > dev.off() null device 1 > if (par2 == 'none') { + detcoef <- cor(result$Forecasts,result$Actuals) + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goodness of Fit',2,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Correlation',1,TRUE) + a<-table.element(a,round(detcoef,4)) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'R-squared',1,TRUE) + a<-table.element(a,round(detcoef*detcoef,4)) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'RMSE',1,TRUE) + a<-table.element(a,round(sqrt(mean((result$Residuals)^2)),4)) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/www/html/rcomp/tmp/5b19t1293033412.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'#',header=TRUE) + a<-table.element(a,'Actuals',header=TRUE) + a<-table.element(a,'Forecasts',header=TRUE) + a<-table.element(a,'Residuals',header=TRUE) + a<-table.row.end(a) + for (i in 1:length(result$Actuals)) { + a<-table.row.start(a) + a<-table.element(a,i,header=TRUE) + a<-table.element(a,result$Actuals[i]) + a<-table.element(a,result$Forecasts[i]) + a<-table.element(a,result$Residuals[i]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/html/rcomp/tmp/6e17y1293033412.tab") + } > if (par2 != 'none') { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Confusion Matrix (predicted in columns / actuals in rows)',par3+1,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'',1,TRUE) + for (i in 1:par3) { + a<-table.element(a,paste('C',i,sep=''),1,TRUE) + } + a<-table.row.end(a) + for (i in 1:par3) { + a<-table.row.start(a) + a<-table.element(a,paste('C',i,sep=''),1,TRUE) + for (j in 1:par3) { + a<-table.element(a,myt[i,j]) + } + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/html/rcomp/tmp/7pso11293033412.tab") + } > > try(system("convert tmp/2x9t21293033412.ps tmp/2x9t21293033412.png",intern=TRUE)) character(0) > try(system("convert tmp/3x9t21293033412.ps tmp/3x9t21293033412.png",intern=TRUE)) character(0) > try(system("convert tmp/4pisn1293033412.ps tmp/4pisn1293033412.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.203 0.485 6.646