R version 2.13.0 (2011-04-13) Copyright (C) 2011 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i486-pc-linux-gnu (32-bit) 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(210907 + ,81 + ,94 + ,112285 + ,24188 + ,120982 + ,55 + ,103 + ,84786 + ,18273 + ,176508 + ,50 + ,93 + ,83123 + ,14130 + ,179321 + ,125 + ,103 + ,101193 + ,32287 + ,123185 + ,40 + ,51 + ,38361 + ,8654 + ,52746 + ,37 + ,70 + ,68504 + ,9245 + ,385534 + ,63 + ,91 + ,119182 + ,33251 + ,33170 + ,44 + ,22 + ,22807 + ,1271 + ,101645 + ,88 + ,38 + ,17140 + ,5279 + ,149061 + ,66 + ,93 + ,116174 + ,27101 + ,165446 + ,57 + ,60 + ,57635 + ,16373 + ,237213 + ,74 + ,123 + ,66198 + ,19716 + ,173326 + ,49 + ,148 + ,71701 + ,17753 + ,133131 + ,52 + ,90 + ,57793 + ,9028 + ,258873 + ,88 + ,124 + ,80444 + ,18653 + ,180083 + ,36 + ,70 + ,53855 + ,8828 + ,324799 + ,108 + ,168 + ,97668 + ,29498 + ,230964 + ,43 + ,115 + ,133824 + ,27563 + ,236785 + ,75 + ,71 + ,101481 + ,18293 + ,135473 + ,32 + ,66 + ,99645 + ,22530 + ,202925 + ,44 + ,134 + ,114789 + ,15977 + ,215147 + ,85 + ,117 + ,99052 + ,35082 + ,344297 + ,86 + ,108 + ,67654 + ,16116 + ,153935 + ,56 + ,84 + ,65553 + ,15849 + ,132943 + ,50 + ,156 + ,97500 + ,16026 + ,174724 + ,135 + ,120 + ,69112 + ,26569 + ,174415 + ,63 + ,114 + ,82753 + ,24785 + ,225548 + ,81 + ,94 + ,85323 + ,17569 + ,223632 + ,52 + ,120 + ,72654 + ,23825 + ,124817 + ,44 + ,81 + ,30727 + ,7869 + ,221698 + ,113 + ,110 + ,77873 + ,14975 + ,210767 + ,39 + ,133 + ,117478 + ,37791 + ,170266 + ,73 + ,122 + ,74007 + ,9605 + ,260561 + ,48 + ,158 + ,90183 + ,27295 + ,84853 + ,33 + ,109 + ,61542 + ,2746 + ,294424 + ,59 + ,124 + ,101494 + ,34461 + ,101011 + ,41 + ,39 + ,27570 + ,8098 + ,215641 + ,69 + ,92 + ,55813 + ,4787 + ,325107 + ,64 + ,126 + ,79215 + ,24919 + ,7176 + ,1 + ,0 + ,1423 + ,603 + ,167542 + ,59 + ,70 + ,55461 + ,16329 + ,106408 + ,32 + ,37 + ,31081 + ,12558 + ,96560 + ,129 + ,38 + ,22996 + ,7784 + ,265769 + ,37 + ,120 + ,83122 + ,28522 + ,269651 + ,31 + ,93 + ,70106 + ,22265 + ,149112 + ,65 + ,95 + ,60578 + ,14459 + ,175824 + ,107 + ,77 + ,39992 + ,14526 + ,152871 + ,74 + ,90 + ,79892 + ,22240 + ,111665 + ,54 + ,80 + ,49810 + ,11802 + ,116408 + ,76 + ,31 + ,71570 + ,7623 + ,362301 + ,715 + ,110 + ,100708 + ,11912 + ,78800 + ,57 + ,66 + ,33032 + ,7935 + ,183167 + ,66 + ,138 + ,82875 + ,18220 + ,277965 + ,106 + ,133 + ,139077 + ,19199 + ,150629 + ,54 + ,113 + ,71595 + ,19918 + ,168809 + ,32 + ,100 + ,72260 + ,21884 + ,24188 + ,20 + ,7 + ,5950 + ,2694 + ,329267 + ,71 + ,140 + ,115762 + ,15808 + ,65029 + ,21 + ,61 + ,32551 + ,3597 + ,101097 + ,70 + ,41 + ,31701 + ,5296 + ,218946 + ,112 + ,96 + ,80670 + ,25239 + ,244052 + ,66 + ,164 + ,143558 + ,29801 + ,341570 + ,190 + ,78 + ,117105 + ,18450 + ,103597 + ,66 + ,49 + ,23789 + ,7132 + ,233328 + ,165 + ,102 + ,120733 + ,34861 + ,256462 + ,56 + ,124 + ,105195 + ,35940 + ,206161 + ,61 + ,99 + ,73107 + ,16688 + ,311473 + ,53 + ,129 + ,132068 + ,24683 + ,235800 + ,127 + ,62 + ,149193 + ,46230 + ,177939 + ,63 + ,73 + ,46821 + ,10387 + ,207176 + ,38 + ,114 + ,87011 + ,21436 + ,196553 + ,50 + ,99 + ,95260 + ,30546 + ,174184 + ,52 + ,70 + ,55183 + ,19746 + ,143246 + ,42 + ,104 + ,106671 + ,15977 + ,187559 + ,76 + ,116 + ,73511 + ,22583 + ,187681 + ,67 + ,91 + ,92945 + ,17274 + ,119016 + ,50 + ,74 + ,78664 + ,16469 + ,182192 + ,53 + ,138 + ,70054 + ,14251 + ,73566 + ,39 + ,67 + ,22618 + ,3007 + ,194979 + ,50 + ,151 + ,74011 + ,16851 + ,167488 + ,77 + ,72 + ,83737 + ,21113 + ,143756 + ,57 + ,120 + ,69094 + ,17401 + ,275541 + ,73 + ,115 + ,93133 + ,23958 + ,243199 + ,34 + ,105 + ,95536 + ,23567 + ,182999 + ,39 + ,104 + ,225920 + ,13065 + ,135649 + ,46 + ,108 + ,62133 + ,15358 + ,152299 + ,63 + ,98 + ,61370 + ,14587 + ,120221 + ,35 + ,69 + ,43836 + ,12770 + ,346485 + ,106 + ,111 + ,106117 + ,24021 + ,145790 + ,43 + ,99 + ,38692 + ,9648 + ,193339 + ,47 + ,71 + ,84651 + ,20537 + ,80953 + ,31 + ,27 + ,56622 + ,7905 + ,122774 + ,162 + ,69 + ,15986 + ,4527 + ,130585 + ,57 + ,107 + ,95364 + ,30495 + ,112611 + ,36 + ,73 + ,26706 + ,7117 + ,286468 + ,263 + ,107 + ,89691 + ,17719 + ,241066 + ,78 + ,93 + ,67267 + ,27056 + ,148446 + ,63 + ,129 + ,126846 + ,33473 + ,204713 + ,54 + ,69 + ,41140 + ,9758 + ,182079 + ,63 + ,118 + ,102860 + ,21115 + ,140344 + ,77 + ,73 + ,51715 + ,7236 + ,220516 + ,79 + ,119 + ,55801 + ,13790 + ,243060 + ,110 + ,104 + ,111813 + ,32902 + ,162765 + ,56 + ,107 + ,120293 + ,25131 + ,182613 + ,56 + ,99 + ,138599 + ,30910 + ,232138 + ,43 + ,90 + ,161647 + ,35947 + ,265318 + ,111 + ,197 + ,115929 + ,29848 + ,85574 + ,71 + ,36 + ,24266 + ,6943 + ,310839 + ,62 + ,85 + ,162901 + ,42705 + ,225060 + ,56 + ,139 + ,109825 + ,31808 + ,232317 + ,74 + ,106 + ,129838 + ,26675 + ,144966 + ,60 + ,50 + ,37510 + ,8435 + ,43287 + ,43 + ,64 + ,43750 + ,7409 + ,155754 + ,68 + ,31 + ,40652 + ,14993 + ,164709 + ,53 + ,63 + ,87771 + ,36867 + ,201940 + ,87 + ,92 + ,85872 + ,33835 + ,235454 + ,46 + ,106 + ,89275 + ,24164 + ,220801 + ,105 + ,63 + ,44418 + ,12607 + ,99466 + ,32 + ,69 + ,192565 + ,22609 + ,92661 + ,133 + ,41 + ,35232 + ,5892 + ,133328 + ,79 + ,56 + ,40909 + ,17014 + ,61361 + ,51 + ,25 + ,13294 + ,5394 + ,125930 + ,207 + ,65 + ,32387 + ,9178 + ,100750 + ,67 + ,93 + ,140867 + ,6440 + ,224549 + ,47 + ,114 + ,120662 + ,21916 + ,82316 + ,34 + ,38 + ,21233 + ,4011 + ,102010 + ,66 + ,44 + ,44332 + ,5818 + ,101523 + ,76 + ,87 + ,61056 + ,18647 + ,243511 + ,65 + ,110 + ,101338 + ,20556 + ,22938 + ,9 + ,0 + ,1168 + ,238 + ,41566 + ,42 + ,27 + ,13497 + ,70 + ,152474 + ,45 + ,83 + ,65567 + ,22392 + ,61857 + ,25 + ,30 + ,25162 + ,3913 + ,99923 + ,115 + ,80 + ,32334 + ,12237 + ,132487 + ,97 + ,98 + ,40735 + ,8388 + ,317394 + ,53 + ,82 + ,91413 + ,22120 + ,21054 + ,2 + ,0 + ,855 + ,338 + ,209641 + ,52 + ,60 + ,97068 + ,11727 + ,22648 + ,44 + ,28 + ,44339 + ,3704 + ,31414 + ,22 + ,9 + ,14116 + ,3988 + ,46698 + ,35 + ,33 + ,10288 + ,3030 + ,131698 + ,74 + ,59 + ,65622 + ,13520 + ,91735 + ,103 + ,49 + ,16563 + ,1421 + ,244749 + ,144 + ,115 + ,76643 + ,20923 + ,184510 + ,60 + ,140 + ,110681 + ,20237 + ,79863 + ,134 + ,49 + ,29011 + ,3219 + ,128423 + ,89 + ,120 + ,92696 + ,3769 + ,97839 + ,42 + ,66 + ,94785 + ,12252 + ,38214 + ,52 + ,21 + ,8773 + ,1888 + ,151101 + ,98 + ,124 + ,83209 + ,14497 + ,272458 + ,99 + ,152 + ,93815 + ,28864 + ,172494 + ,52 + ,139 + ,86687 + ,21721 + ,108043 + ,29 + ,38 + ,34553 + ,4821 + ,328107 + ,125 + ,144 + ,105547 + ,33644 + ,250579 + ,106 + ,120 + ,103487 + ,15923 + ,351067 + ,95 + ,160 + ,213688 + ,42935 + ,158015 + ,40 + ,114 + ,71220 + ,18864 + ,98866 + ,140 + ,39 + ,23517 + ,4977 + ,85439 + ,43 + ,78 + ,56926 + ,7785 + ,229242 + ,128 + ,119 + ,91721 + ,17939 + ,351619 + ,142 + ,141 + ,115168 + ,23436 + ,84207 + ,73 + ,101 + ,111194 + ,325 + ,120445 + ,72 + ,56 + ,51009 + ,13539 + ,324598 + ,128 + ,133 + ,135777 + ,34538 + ,131069 + ,61 + ,83 + ,51513 + ,12198 + ,204271 + ,73 + ,116 + ,74163 + ,26924 + ,165543 + ,148 + ,90 + ,51633 + ,12716 + ,141722 + ,64 + ,36 + ,75345 + ,8172 + ,116048 + ,45 + ,50 + ,33416 + ,10855 + ,250047 + ,58 + ,61 + ,83305 + ,11932 + ,299775 + ,97 + ,97 + ,98952 + ,14300 + ,195838 + ,50 + ,98 + ,102372 + ,25515 + ,173260 + ,37 + ,78 + ,37238 + ,2805 + ,254488 + ,50 + ,117 + ,103772 + ,29402 + ,104389 + ,105 + ,148 + ,123969 + ,16440 + ,136084 + ,69 + ,41 + ,27142 + ,11221 + ,199476 + ,46 + ,105 + ,135400 + ,28732 + ,92499 + ,57 + ,55 + ,21399 + ,5250 + ,224330 + ,52 + ,132 + ,130115 + ,28608 + ,135781 + ,98 + ,44 + ,24874 + ,8092 + ,74408 + ,61 + ,21 + ,34988 + ,4473 + ,81240 + ,89 + ,50 + ,45549 + ,1572 + ,14688 + ,0 + ,0 + ,6023 + ,2065 + ,181633 + ,48 + ,73 + ,64466 + ,14817 + ,271856 + ,91 + ,86 + ,54990 + ,16714 + ,7199 + ,0 + ,0 + ,1644 + ,556 + ,46660 + ,7 + ,13 + ,6179 + ,2089 + ,17547 + ,3 + ,4 + ,3926 + ,2658 + ,133368 + ,54 + ,57 + ,32755 + ,10695 + ,95227 + ,70 + ,48 + ,34777 + ,1669 + ,152601 + ,36 + ,46 + ,73224 + ,16267 + ,98146 + ,37 + ,48 + ,27114 + ,7768 + ,79619 + ,123 + ,32 + ,20760 + ,7252 + ,59194 + ,247 + ,68 + ,37636 + ,6387 + ,139942 + ,46 + ,87 + ,65461 + ,18715 + ,118612 + ,72 + ,43 + ,30080 + ,7936 + ,72880 + ,41 + ,67 + ,24094 + ,8643 + ,65475 + ,24 + ,46 + ,69008 + ,7294 + ,99643 + ,45 + ,46 + ,54968 + ,4570 + ,71965 + ,33 + ,56 + ,46090 + ,7185 + ,77272 + ,27 + ,48 + ,27507 + ,10058 + ,49289 + ,36 + ,44 + ,10672 + ,2342 + ,135131 + ,87 + ,60 + ,34029 + ,8509 + ,108446 + ,90 + ,65 + ,46300 + ,13275 + ,89746 + ,114 + ,55 + ,24760 + ,6816 + ,44296 + ,31 + ,38 + ,18779 + ,1930 + ,77648 + ,45 + ,52 + ,21280 + ,8086 + ,181528 + ,69 + ,60 + ,40662 + ,10737 + ,134019 + ,51 + ,54 + ,28987 + ,8033 + ,124064 + ,34 + ,86 + ,22827 + ,7058 + ,92630 + ,60 + ,24 + ,18513 + ,6782 + ,121848 + ,45 + ,52 + ,30594 + ,5401 + ,52915 + ,54 + ,49 + ,24006 + ,6521 + ,81872 + ,25 + ,61 + ,27913 + ,10856 + ,58981 + ,38 + ,61 + ,42744 + ,2154 + ,53515 + ,52 + ,81 + ,12934 + ,6117 + ,60812 + ,67 + ,43 + ,22574 + ,5238 + ,56375 + ,74 + ,40 + ,41385 + ,4820 + ,65490 + ,38 + ,40 + ,18653 + ,5615 + ,80949 + ,30 + ,56 + ,18472 + ,4272 + ,76302 + ,26 + ,68 + ,30976 + ,8702 + ,104011 + ,67 + ,79 + ,63339 + ,15340 + ,98104 + ,132 + ,47 + ,25568 + ,8030 + ,67989 + ,42 + ,57 + ,33747 + ,9526 + ,30989 + ,35 + ,41 + ,4154 + ,1278 + ,135458 + ,118 + ,29 + ,19474 + ,4236 + ,73504 + ,68 + ,3 + ,35130 + ,3023 + ,63123 + ,43 + ,60 + ,39067 + ,7196 + ,61254 + ,76 + ,30 + ,13310 + ,3394 + ,74914 + ,64 + ,79 + ,65892 + ,6371 + ,31774 + ,48 + ,47 + ,4143 + ,1574 + ,81437 + ,64 + ,40 + ,28579 + ,9620 + ,87186 + ,56 + ,48 + ,51776 + ,6978 + ,50090 + ,71 + ,36 + ,21152 + ,4911 + ,65745 + ,75 + ,42 + ,38084 + ,8645 + ,56653 + ,39 + ,49 + ,27717 + ,8987 + ,158399 + ,42 + ,57 + ,32928 + ,5544 + ,46455 + ,39 + ,12 + ,11342 + ,3083 + ,73624 + ,93 + ,40 + ,19499 + ,6909 + ,38395 + ,38 + ,43 + ,16380 + ,3189 + ,91899 + ,60 + ,33 + ,36874 + ,6745 + ,139526 + ,71 + ,77 + ,48259 + ,16724 + ,52164 + ,52 + ,43 + ,16734 + ,4850 + ,51567 + ,27 + ,45 + ,28207 + ,7025 + ,70551 + ,59 + ,47 + ,30143 + ,6047 + ,84856 + ,40 + ,43 + ,41369 + ,7377 + ,102538 + ,79 + ,45 + ,45833 + ,9078 + ,86678 + ,44 + ,50 + ,29156 + ,4605 + ,85709 + ,65 + ,35 + ,35944 + ,3238 + ,34662 + ,10 + ,7 + ,36278 + ,8100 + ,150580 + ,124 + ,71 + ,45588 + ,9653 + ,99611 + ,81 + ,67 + ,45097 + ,8914 + ,19349 + ,15 + ,0 + ,3895 + ,786 + ,99373 + ,92 + ,62 + ,28394 + ,6700 + ,86230 + ,42 + ,54 + ,18632 + ,5788 + ,30837 + ,10 + ,4 + ,2325 + ,593 + ,31706 + ,24 + ,25 + ,25139 + ,4506 + ,89806 + ,64 + ,40 + ,27975 + ,6382 + ,62088 + ,45 + ,38 + ,14483 + ,5621 + ,40151 + ,22 + ,19 + ,13127 + ,3997 + ,27634 + ,56 + ,17 + ,5839 + ,520 + ,76990 + ,94 + ,67 + ,24069 + ,8891 + ,37460 + ,19 + ,14 + ,3738 + ,999 + ,54157 + ,35 + ,30 + ,18625 + ,7067 + ,49862 + ,32 + ,54 + ,36341 + ,4639 + ,84337 + ,35 + ,35 + ,24548 + ,5654 + ,64175 + ,48 + ,59 + ,21792 + ,6928 + ,59382 + ,49 + ,24 + ,26263 + ,1514 + ,119308 + ,48 + ,58 + ,23686 + ,9238 + ,76702 + ,62 + ,42 + ,49303 + ,8204 + ,103425 + ,96 + ,46 + ,25659 + ,5926 + ,70344 + ,45 + ,61 + ,28904 + ,5785 + ,43410 + ,63 + ,3 + ,2781 + ,4 + ,104838 + ,71 + ,52 + ,29236 + ,5930 + ,62215 + ,26 + ,25 + ,19546 + ,3710 + ,69304 + ,48 + ,40 + ,22818 + ,705 + ,53117 + ,29 + ,32 + ,32689 + ,443 + ,19764 + ,19 + ,4 + ,5752 + ,2416 + ,86680 + ,45 + ,49 + ,22197 + ,7747 + ,84105 + ,45 + ,63 + ,20055 + ,5432 + ,77945 + ,67 + ,67 + ,25272 + ,4913 + ,89113 + ,30 + ,32 + ,82206 + ,2650 + ,91005 + ,36 + ,23 + ,32073 + ,2370 + ,40248 + ,34 + ,7 + ,5444 + ,775 + ,64187 + ,36 + ,54 + ,20154 + ,5576 + ,50857 + ,34 + ,37 + ,36944 + ,1352 + ,56613 + ,37 + ,35 + ,8019 + ,3080 + ,62792 + ,46 + ,51 + ,30884 + ,10205 + ,72535 + ,44 + ,39 + ,19540 + ,6095) + ,dim=c(5 + ,289) + ,dimnames=list(c('time_in_rfc' + ,'compendium_views_pr' + ,'feedback_messages_p120' + ,'totsize' + ,'totrevisions') + ,1:289)) > y <- array(NA,dim=c(5,289),dimnames=list(c('time_in_rfc','compendium_views_pr','feedback_messages_p120','totsize','totrevisions'),1:289)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'No Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '4' > library(lattice) > library(lmtest) Loading required package: zoo > n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test > par1 <- as.numeric(par1) > x <- t(y) > k <- length(x[1,]) > n <- length(x[,1]) > x1 <- cbind(x[,par1], x[,1:k!=par1]) > mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) > colnames(x1) <- mycolnames #colnames(x)[par1] > x <- x1 > if (par3 == 'First Differences'){ + x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep=''))) + for (i in 1:n-1) { + for (j in 1:k) { + x2[i,j] <- x[i+1,j] - x[i,j] + } + } + x <- x2 + } > if (par2 == 'Include Monthly Dummies'){ + x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep =''))) + for (i in 1:11){ + x2[seq(i,n,12),i] <- 1 + } + x <- cbind(x, x2) + } > if (par2 == 'Include Quarterly Dummies'){ + x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep =''))) + for (i in 1:3){ + x2[seq(i,n,4),i] <- 1 + } + x <- cbind(x, x2) + } > k <- length(x[1,]) > if (par3 == 'Linear Trend'){ + x <- cbind(x, c(1:n)) + colnames(x)[k+1] <- 't' + } > x totsize time_in_rfc compendium_views_pr feedback_messages_p120 totrevisions 1 112285 210907 81 94 24188 2 84786 120982 55 103 18273 3 83123 176508 50 93 14130 4 101193 179321 125 103 32287 5 38361 123185 40 51 8654 6 68504 52746 37 70 9245 7 119182 385534 63 91 33251 8 22807 33170 44 22 1271 9 17140 101645 88 38 5279 10 116174 149061 66 93 27101 11 57635 165446 57 60 16373 12 66198 237213 74 123 19716 13 71701 173326 49 148 17753 14 57793 133131 52 90 9028 15 80444 258873 88 124 18653 16 53855 180083 36 70 8828 17 97668 324799 108 168 29498 18 133824 230964 43 115 27563 19 101481 236785 75 71 18293 20 99645 135473 32 66 22530 21 114789 202925 44 134 15977 22 99052 215147 85 117 35082 23 67654 344297 86 108 16116 24 65553 153935 56 84 15849 25 97500 132943 50 156 16026 26 69112 174724 135 120 26569 27 82753 174415 63 114 24785 28 85323 225548 81 94 17569 29 72654 223632 52 120 23825 30 30727 124817 44 81 7869 31 77873 221698 113 110 14975 32 117478 210767 39 133 37791 33 74007 170266 73 122 9605 34 90183 260561 48 158 27295 35 61542 84853 33 109 2746 36 101494 294424 59 124 34461 37 27570 101011 41 39 8098 38 55813 215641 69 92 4787 39 79215 325107 64 126 24919 40 1423 7176 1 0 603 41 55461 167542 59 70 16329 42 31081 106408 32 37 12558 43 22996 96560 129 38 7784 44 83122 265769 37 120 28522 45 70106 269651 31 93 22265 46 60578 149112 65 95 14459 47 39992 175824 107 77 14526 48 79892 152871 74 90 22240 49 49810 111665 54 80 11802 50 71570 116408 76 31 7623 51 100708 362301 715 110 11912 52 33032 78800 57 66 7935 53 82875 183167 66 138 18220 54 139077 277965 106 133 19199 55 71595 150629 54 113 19918 56 72260 168809 32 100 21884 57 5950 24188 20 7 2694 58 115762 329267 71 140 15808 59 32551 65029 21 61 3597 60 31701 101097 70 41 5296 61 80670 218946 112 96 25239 62 143558 244052 66 164 29801 63 117105 341570 190 78 18450 64 23789 103597 66 49 7132 65 120733 233328 165 102 34861 66 105195 256462 56 124 35940 67 73107 206161 61 99 16688 68 132068 311473 53 129 24683 69 149193 235800 127 62 46230 70 46821 177939 63 73 10387 71 87011 207176 38 114 21436 72 95260 196553 50 99 30546 73 55183 174184 52 70 19746 74 106671 143246 42 104 15977 75 73511 187559 76 116 22583 76 92945 187681 67 91 17274 77 78664 119016 50 74 16469 78 70054 182192 53 138 14251 79 22618 73566 39 67 3007 80 74011 194979 50 151 16851 81 83737 167488 77 72 21113 82 69094 143756 57 120 17401 83 93133 275541 73 115 23958 84 95536 243199 34 105 23567 85 225920 182999 39 104 13065 86 62133 135649 46 108 15358 87 61370 152299 63 98 14587 88 43836 120221 35 69 12770 89 106117 346485 106 111 24021 90 38692 145790 43 99 9648 91 84651 193339 47 71 20537 92 56622 80953 31 27 7905 93 15986 122774 162 69 4527 94 95364 130585 57 107 30495 95 26706 112611 36 73 7117 96 89691 286468 263 107 17719 97 67267 241066 78 93 27056 98 126846 148446 63 129 33473 99 41140 204713 54 69 9758 100 102860 182079 63 118 21115 101 51715 140344 77 73 7236 102 55801 220516 79 119 13790 103 111813 243060 110 104 32902 104 120293 162765 56 107 25131 105 138599 182613 56 99 30910 106 161647 232138 43 90 35947 107 115929 265318 111 197 29848 108 24266 85574 71 36 6943 109 162901 310839 62 85 42705 110 109825 225060 56 139 31808 111 129838 232317 74 106 26675 112 37510 144966 60 50 8435 113 43750 43287 43 64 7409 114 40652 155754 68 31 14993 115 87771 164709 53 63 36867 116 85872 201940 87 92 33835 117 89275 235454 46 106 24164 118 44418 220801 105 63 12607 119 192565 99466 32 69 22609 120 35232 92661 133 41 5892 121 40909 133328 79 56 17014 122 13294 61361 51 25 5394 123 32387 125930 207 65 9178 124 140867 100750 67 93 6440 125 120662 224549 47 114 21916 126 21233 82316 34 38 4011 127 44332 102010 66 44 5818 128 61056 101523 76 87 18647 129 101338 243511 65 110 20556 130 1168 22938 9 0 238 131 13497 41566 42 27 70 132 65567 152474 45 83 22392 133 25162 61857 25 30 3913 134 32334 99923 115 80 12237 135 40735 132487 97 98 8388 136 91413 317394 53 82 22120 137 855 21054 2 0 338 138 97068 209641 52 60 11727 139 44339 22648 44 28 3704 140 14116 31414 22 9 3988 141 10288 46698 35 33 3030 142 65622 131698 74 59 13520 143 16563 91735 103 49 1421 144 76643 244749 144 115 20923 145 110681 184510 60 140 20237 146 29011 79863 134 49 3219 147 92696 128423 89 120 3769 148 94785 97839 42 66 12252 149 8773 38214 52 21 1888 150 83209 151101 98 124 14497 151 93815 272458 99 152 28864 152 86687 172494 52 139 21721 153 34553 108043 29 38 4821 154 105547 328107 125 144 33644 155 103487 250579 106 120 15923 156 213688 351067 95 160 42935 157 71220 158015 40 114 18864 158 23517 98866 140 39 4977 159 56926 85439 43 78 7785 160 91721 229242 128 119 17939 161 115168 351619 142 141 23436 162 111194 84207 73 101 325 163 51009 120445 72 56 13539 164 135777 324598 128 133 34538 165 51513 131069 61 83 12198 166 74163 204271 73 116 26924 167 51633 165543 148 90 12716 168 75345 141722 64 36 8172 169 33416 116048 45 50 10855 170 83305 250047 58 61 11932 171 98952 299775 97 97 14300 172 102372 195838 50 98 25515 173 37238 173260 37 78 2805 174 103772 254488 50 117 29402 175 123969 104389 105 148 16440 176 27142 136084 69 41 11221 177 135400 199476 46 105 28732 178 21399 92499 57 55 5250 179 130115 224330 52 132 28608 180 24874 135781 98 44 8092 181 34988 74408 61 21 4473 182 45549 81240 89 50 1572 183 6023 14688 0 0 2065 184 64466 181633 48 73 14817 185 54990 271856 91 86 16714 186 1644 7199 0 0 556 187 6179 46660 7 13 2089 188 3926 17547 3 4 2658 189 32755 133368 54 57 10695 190 34777 95227 70 48 1669 191 73224 152601 36 46 16267 192 27114 98146 37 48 7768 193 20760 79619 123 32 7252 194 37636 59194 247 68 6387 195 65461 139942 46 87 18715 196 30080 118612 72 43 7936 197 24094 72880 41 67 8643 198 69008 65475 24 46 7294 199 54968 99643 45 46 4570 200 46090 71965 33 56 7185 201 27507 77272 27 48 10058 202 10672 49289 36 44 2342 203 34029 135131 87 60 8509 204 46300 108446 90 65 13275 205 24760 89746 114 55 6816 206 18779 44296 31 38 1930 207 21280 77648 45 52 8086 208 40662 181528 69 60 10737 209 28987 134019 51 54 8033 210 22827 124064 34 86 7058 211 18513 92630 60 24 6782 212 30594 121848 45 52 5401 213 24006 52915 54 49 6521 214 27913 81872 25 61 10856 215 42744 58981 38 61 2154 216 12934 53515 52 81 6117 217 22574 60812 67 43 5238 218 41385 56375 74 40 4820 219 18653 65490 38 40 5615 220 18472 80949 30 56 4272 221 30976 76302 26 68 8702 222 63339 104011 67 79 15340 223 25568 98104 132 47 8030 224 33747 67989 42 57 9526 225 4154 30989 35 41 1278 226 19474 135458 118 29 4236 227 35130 73504 68 3 3023 228 39067 63123 43 60 7196 229 13310 61254 76 30 3394 230 65892 74914 64 79 6371 231 4143 31774 48 47 1574 232 28579 81437 64 40 9620 233 51776 87186 56 48 6978 234 21152 50090 71 36 4911 235 38084 65745 75 42 8645 236 27717 56653 39 49 8987 237 32928 158399 42 57 5544 238 11342 46455 39 12 3083 239 19499 73624 93 40 6909 240 16380 38395 38 43 3189 241 36874 91899 60 33 6745 242 48259 139526 71 77 16724 243 16734 52164 52 43 4850 244 28207 51567 27 45 7025 245 30143 70551 59 47 6047 246 41369 84856 40 43 7377 247 45833 102538 79 45 9078 248 29156 86678 44 50 4605 249 35944 85709 65 35 3238 250 36278 34662 10 7 8100 251 45588 150580 124 71 9653 252 45097 99611 81 67 8914 253 3895 19349 15 0 786 254 28394 99373 92 62 6700 255 18632 86230 42 54 5788 256 2325 30837 10 4 593 257 25139 31706 24 25 4506 258 27975 89806 64 40 6382 259 14483 62088 45 38 5621 260 13127 40151 22 19 3997 261 5839 27634 56 17 520 262 24069 76990 94 67 8891 263 3738 37460 19 14 999 264 18625 54157 35 30 7067 265 36341 49862 32 54 4639 266 24548 84337 35 35 5654 267 21792 64175 48 59 6928 268 26263 59382 49 24 1514 269 23686 119308 48 58 9238 270 49303 76702 62 42 8204 271 25659 103425 96 46 5926 272 28904 70344 45 61 5785 273 2781 43410 63 3 4 274 29236 104838 71 52 5930 275 19546 62215 26 25 3710 276 22818 69304 48 40 705 277 32689 53117 29 32 443 278 5752 19764 19 4 2416 279 22197 86680 45 49 7747 280 20055 84105 45 63 5432 281 25272 77945 67 67 4913 282 82206 89113 30 32 2650 283 32073 91005 36 23 2370 284 5444 40248 34 7 775 285 20154 64187 36 54 5576 286 36944 50857 34 37 1352 287 8019 56613 37 35 3080 288 30884 62792 46 51 10205 289 19540 72535 44 39 6095 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) time_in_rfc compendium_views_pr 1284.69927 0.08112 -11.57040 feedback_messages_p120 totrevisions 293.82542 1.92670 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -34910 -12531 -5229 8853 154512 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1284.69927 2886.32705 0.445 0.65659 time_in_rfc 0.08112 0.03015 2.690 0.00757 ** compendium_views_pr -11.57040 27.12478 -0.427 0.67002 feedback_messages_p120 293.82542 54.81601 5.360 1.72e-07 *** totrevisions 1.92670 0.22716 8.482 1.24e-15 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 21730 on 284 degrees of freedom Multiple R-squared: 0.715, Adjusted R-squared: 0.711 F-statistic: 178.2 on 4 and 284 DF, p-value: < 2.2e-16 > if (n > n25) { + kp3 <- k + 3 + nmkm3 <- n - k - 3 + gqarr <- array(NA, dim=c(nmkm3-kp3+1,3)) + numgqtests <- 0 + numsignificant1 <- 0 + numsignificant5 <- 0 + numsignificant10 <- 0 + for (mypoint in kp3:nmkm3) { + j <- 0 + numgqtests <- numgqtests + 1 + for (myalt in c('greater', 'two.sided', 'less')) { + j <- j + 1 + gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value + } + if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 + } + gqarr + } [,1] [,2] [,3] [1,] 0.247306462 4.946129e-01 7.526935e-01 [2,] 0.137653897 2.753078e-01 8.623461e-01 [3,] 0.073246590 1.464932e-01 9.267534e-01 [4,] 0.047841585 9.568317e-02 9.521584e-01 [5,] 0.072892695 1.457854e-01 9.271073e-01 [6,] 0.061803741 1.236075e-01 9.381963e-01 [7,] 0.043519965 8.703993e-02 9.564800e-01 [8,] 0.036678376 7.335675e-02 9.633216e-01 [9,] 0.020191751 4.038350e-02 9.798082e-01 [10,] 0.011429816 2.285963e-02 9.885702e-01 [11,] 0.009090695 1.818139e-02 9.909093e-01 [12,] 0.031844059 6.368812e-02 9.681559e-01 [13,] 0.022058637 4.411727e-02 9.779414e-01 [14,] 0.056154511 1.123090e-01 9.438455e-01 [15,] 0.090442863 1.808857e-01 9.095571e-01 [16,] 0.064499893 1.289998e-01 9.355001e-01 [17,] 0.047850126 9.570025e-02 9.521499e-01 [18,] 0.035454291 7.090858e-02 9.645457e-01 [19,] 0.025639963 5.127993e-02 9.743600e-01 [20,] 0.026087858 5.217572e-02 9.739121e-01 [21,] 0.022206729 4.441346e-02 9.777933e-01 [22,] 0.044019410 8.803882e-02 9.559806e-01 [23,] 0.052657983 1.053160e-01 9.473420e-01 [24,] 0.058308547 1.166171e-01 9.416915e-01 [25,] 0.061904500 1.238090e-01 9.380955e-01 [26,] 0.053303771 1.066075e-01 9.466962e-01 [27,] 0.062046951 1.240939e-01 9.379530e-01 [28,] 0.051327774 1.026555e-01 9.486722e-01 [29,] 0.050591655 1.011833e-01 9.494083e-01 [30,] 0.053880426 1.077609e-01 9.461196e-01 [31,] 0.041379119 8.275824e-02 9.586209e-01 [32,] 0.043652692 8.730538e-02 9.563473e-01 [33,] 0.053717039 1.074341e-01 9.462830e-01 [34,] 0.044147513 8.829503e-02 9.558525e-01 [35,] 0.045366901 9.073380e-02 9.546331e-01 [36,] 0.035131242 7.026248e-02 9.648688e-01 [37,] 0.039760726 7.952145e-02 9.602393e-01 [38,] 0.036734135 7.346827e-02 9.632659e-01 [39,] 0.028346940 5.669388e-02 9.716531e-01 [40,] 0.026963121 5.392624e-02 9.730369e-01 [41,] 0.020090681 4.018136e-02 9.799093e-01 [42,] 0.015462409 3.092482e-02 9.845376e-01 [43,] 0.032925038 6.585008e-02 9.670750e-01 [44,] 0.042483662 8.496732e-02 9.575163e-01 [45,] 0.036894009 7.378802e-02 9.631060e-01 [46,] 0.028609644 5.721929e-02 9.713904e-01 [47,] 0.091523189 1.830464e-01 9.084768e-01 [48,] 0.078030803 1.560616e-01 9.219692e-01 [49,] 0.066078529 1.321571e-01 9.339215e-01 [50,] 0.056624524 1.132490e-01 9.433755e-01 [51,] 0.062095890 1.241918e-01 9.379041e-01 [52,] 0.049652072 9.930414e-02 9.503479e-01 [53,] 0.039464901 7.892980e-02 9.605351e-01 [54,] 0.032452406 6.490481e-02 9.675476e-01 [55,] 0.038279379 7.655876e-02 9.617206e-01 [56,] 0.056991889 1.139838e-01 9.430081e-01 [57,] 0.051951879 1.039038e-01 9.480481e-01 [58,] 0.044495688 8.899138e-02 9.555043e-01 [59,] 0.039954730 7.990946e-02 9.600453e-01 [60,] 0.031903178 6.380636e-02 9.680968e-01 [61,] 0.037285554 7.457111e-02 9.627144e-01 [62,] 0.047232700 9.446540e-02 9.527673e-01 [63,] 0.039844440 7.968888e-02 9.601556e-01 [64,] 0.032131379 6.426276e-02 9.678686e-01 [65,] 0.026038110 5.207622e-02 9.739619e-01 [66,] 0.024215690 4.843138e-02 9.757843e-01 [67,] 0.038114809 7.622962e-02 9.618852e-01 [68,] 0.035829090 7.165818e-02 9.641709e-01 [69,] 0.034406166 6.881233e-02 9.655938e-01 [70,] 0.031196667 6.239333e-02 9.688033e-01 [71,] 0.026815344 5.363069e-02 9.731847e-01 [72,] 0.022779799 4.555960e-02 9.772202e-01 [73,] 0.021165493 4.233099e-02 9.788345e-01 [74,] 0.017348551 3.469710e-02 9.826514e-01 [75,] 0.014477934 2.895587e-02 9.855221e-01 [76,] 0.011687993 2.337599e-02 9.883120e-01 [77,] 0.009214021 1.842804e-02 9.907860e-01 [78,] 0.991698312 1.660338e-02 8.301688e-03 [79,] 0.990094462 1.981108e-02 9.905538e-03 [80,] 0.987923251 2.415350e-02 1.207675e-02 [81,] 0.985938020 2.812396e-02 1.406198e-02 [82,] 0.982354871 3.529026e-02 1.764513e-02 [83,] 0.982723012 3.455398e-02 1.727699e-02 [84,] 0.979010422 4.197916e-02 2.098958e-02 [85,] 0.979492128 4.101574e-02 2.050787e-02 [86,] 0.980352658 3.929468e-02 1.964734e-02 [87,] 0.976279684 4.744063e-02 2.372032e-02 [88,] 0.975502727 4.899455e-02 2.449727e-02 [89,] 0.971038225 5.792355e-02 2.896177e-02 [90,] 0.976731085 4.653783e-02 2.326892e-02 [91,] 0.974095946 5.180811e-02 2.590405e-02 [92,] 0.971663585 5.667283e-02 2.833641e-02 [93,] 0.967583106 6.483379e-02 3.241689e-02 [94,] 0.960843921 7.831216e-02 3.915608e-02 [95,] 0.962774944 7.445011e-02 3.722506e-02 [96,] 0.955165972 8.966806e-02 4.483403e-02 [97,] 0.958723655 8.255269e-02 4.127634e-02 [98,] 0.968599462 6.280108e-02 3.140054e-02 [99,] 0.984239873 3.152025e-02 1.576013e-02 [100,] 0.984296615 3.140677e-02 1.570338e-02 [101,] 0.981209146 3.758171e-02 1.879085e-02 [102,] 0.984679688 3.064062e-02 1.532031e-02 [103,] 0.982322807 3.535439e-02 1.767719e-02 [104,] 0.984475895 3.104821e-02 1.552411e-02 [105,] 0.981200128 3.759974e-02 1.879987e-02 [106,] 0.977084284 4.583143e-02 2.291572e-02 [107,] 0.973622464 5.275507e-02 2.637754e-02 [108,] 0.971042026 5.791595e-02 2.895797e-02 [109,] 0.971083097 5.783381e-02 2.891690e-02 [110,] 0.966371187 6.725763e-02 3.362881e-02 [111,] 0.963378286 7.324343e-02 3.662171e-02 [112,] 0.999993196 1.360832e-05 6.804162e-06 [113,] 0.999990572 1.885609e-05 9.428044e-06 [114,] 0.999989422 2.115637e-05 1.057819e-05 [115,] 0.999985965 2.807096e-05 1.403548e-05 [116,] 0.999981704 3.659156e-05 1.829578e-05 [117,] 0.999999986 2.782083e-08 1.391041e-08 [118,] 0.999999988 2.329414e-08 1.164707e-08 [119,] 0.999999982 3.578410e-08 1.789205e-08 [120,] 0.999999974 5.115065e-08 2.557533e-08 [121,] 0.999999962 7.683389e-08 3.841695e-08 [122,] 0.999999942 1.151855e-07 5.759275e-08 [123,] 0.999999911 1.788569e-07 8.942845e-08 [124,] 0.999999859 2.814232e-07 1.407116e-07 [125,] 0.999999818 3.641843e-07 1.820922e-07 [126,] 0.999999717 5.659311e-07 2.829656e-07 [127,] 0.999999724 5.514328e-07 2.757164e-07 [128,] 0.999999683 6.338603e-07 3.169302e-07 [129,] 0.999999519 9.616423e-07 4.808212e-07 [130,] 0.999999273 1.454247e-06 7.271233e-07 [131,] 0.999999724 5.526165e-07 2.763082e-07 [132,] 0.999999800 4.006204e-07 2.003102e-07 [133,] 0.999999694 6.110081e-07 3.055040e-07 [134,] 0.999999577 8.451661e-07 4.225831e-07 [135,] 0.999999446 1.108133e-06 5.540667e-07 [136,] 0.999999216 1.567431e-06 7.837155e-07 [137,] 0.999999094 1.812880e-06 9.064398e-07 [138,] 0.999998821 2.357816e-06 1.178908e-06 [139,] 0.999998228 3.544793e-06 1.772396e-06 [140,] 0.999999201 1.598545e-06 7.992725e-07 [141,] 0.999999833 3.344004e-07 1.672002e-07 [142,] 0.999999745 5.092633e-07 2.546317e-07 [143,] 0.999999616 7.682160e-07 3.841080e-07 [144,] 0.999999762 4.751181e-07 2.375591e-07 [145,] 0.999999686 6.288543e-07 3.144272e-07 [146,] 0.999999515 9.698823e-07 4.849412e-07 [147,] 0.999999717 5.655962e-07 2.827981e-07 [148,] 0.999999637 7.262276e-07 3.631138e-07 [149,] 0.999999987 2.658475e-08 1.329238e-08 [150,] 0.999999982 3.631493e-08 1.815747e-08 [151,] 0.999999971 5.809027e-08 2.904514e-08 [152,] 0.999999958 8.360571e-08 4.180285e-08 [153,] 0.999999933 1.341026e-07 6.705130e-08 [154,] 0.999999893 2.133880e-07 1.066940e-07 [155,] 1.000000000 2.536141e-10 1.268070e-10 [156,] 1.000000000 4.483764e-10 2.241882e-10 [157,] 1.000000000 7.564705e-10 3.782352e-10 [158,] 0.999999999 1.255726e-09 6.278630e-10 [159,] 1.000000000 6.982698e-10 3.491349e-10 [160,] 0.999999999 1.033628e-09 5.168142e-10 [161,] 1.000000000 2.086648e-10 1.043324e-10 [162,] 1.000000000 2.948681e-10 1.474340e-10 [163,] 1.000000000 2.447794e-10 1.223897e-10 [164,] 1.000000000 1.806779e-10 9.033893e-11 [165,] 1.000000000 2.865922e-10 1.432961e-10 [166,] 1.000000000 5.044492e-10 2.522246e-10 [167,] 1.000000000 8.434066e-10 4.217033e-10 [168,] 1.000000000 3.013981e-11 1.506990e-11 [169,] 1.000000000 2.982787e-11 1.491393e-11 [170,] 1.000000000 3.141228e-12 1.570614e-12 [171,] 1.000000000 4.858919e-12 2.429460e-12 [172,] 1.000000000 5.911218e-13 2.955609e-13 [173,] 1.000000000 7.924905e-13 3.962452e-13 [174,] 1.000000000 1.151455e-12 5.757273e-13 [175,] 1.000000000 7.570481e-13 3.785240e-13 [176,] 1.000000000 1.444096e-12 7.220479e-13 [177,] 1.000000000 2.450563e-12 1.225282e-12 [178,] 1.000000000 2.561975e-12 1.280988e-12 [179,] 1.000000000 4.749424e-12 2.374712e-12 [180,] 1.000000000 7.465993e-12 3.732997e-12 [181,] 1.000000000 1.222390e-11 6.111951e-12 [182,] 1.000000000 1.730619e-11 8.653096e-12 [183,] 1.000000000 2.688819e-11 1.344410e-11 [184,] 1.000000000 2.167831e-11 1.083915e-11 [185,] 1.000000000 3.722194e-11 1.861097e-11 [186,] 1.000000000 6.324277e-11 3.162138e-11 [187,] 1.000000000 8.023693e-11 4.011846e-11 [188,] 1.000000000 1.373446e-10 6.867232e-11 [189,] 1.000000000 2.457863e-10 1.228932e-10 [190,] 1.000000000 3.445298e-10 1.722649e-10 [191,] 1.000000000 2.110562e-11 1.055281e-11 [192,] 1.000000000 8.452039e-12 4.226019e-12 [193,] 1.000000000 9.298574e-12 4.649287e-12 [194,] 1.000000000 1.642161e-11 8.210805e-12 [195,] 1.000000000 2.607993e-11 1.303997e-11 [196,] 1.000000000 4.836109e-11 2.418054e-11 [197,] 1.000000000 9.108640e-11 4.554320e-11 [198,] 1.000000000 1.629286e-10 8.146432e-11 [199,] 1.000000000 3.232725e-10 1.616362e-10 [200,] 1.000000000 4.735364e-10 2.367682e-10 [201,] 1.000000000 7.874413e-10 3.937207e-10 [202,] 0.999999999 1.148784e-09 5.743922e-10 [203,] 1.000000000 8.181316e-10 4.090658e-10 [204,] 0.999999999 1.213680e-09 6.068401e-10 [205,] 0.999999999 2.122241e-09 1.061120e-09 [206,] 0.999999998 4.046034e-09 2.023017e-09 [207,] 0.999999997 5.534234e-09 2.767117e-09 [208,] 0.999999998 4.378304e-09 2.189152e-09 [209,] 0.999999998 4.381449e-09 2.190725e-09 [210,] 0.999999996 8.467806e-09 4.233903e-09 [211,] 0.999999997 6.501512e-09 3.250756e-09 [212,] 0.999999995 1.075548e-08 5.377741e-09 [213,] 0.999999993 1.432909e-08 7.164546e-09 [214,] 0.999999988 2.394299e-08 1.197149e-08 [215,] 0.999999986 2.892739e-08 1.446370e-08 [216,] 0.999999973 5.399832e-08 2.699916e-08 [217,] 0.999999949 1.022625e-07 5.113123e-08 [218,] 0.999999931 1.388426e-07 6.942132e-08 [219,] 0.999999905 1.897843e-07 9.489214e-08 [220,] 0.999999908 1.834712e-07 9.173561e-08 [221,] 0.999999850 3.000216e-07 1.500108e-07 [222,] 0.999999738 5.233774e-07 2.616887e-07 [223,] 0.999999973 5.386325e-08 2.693162e-08 [224,] 0.999999958 8.350081e-08 4.175040e-08 [225,] 0.999999920 1.599373e-07 7.996863e-08 [226,] 0.999999946 1.077790e-07 5.388951e-08 [227,] 0.999999893 2.132503e-07 1.066251e-07 [228,] 0.999999858 2.845280e-07 1.422640e-07 [229,] 0.999999723 5.540292e-07 2.770146e-07 [230,] 0.999999799 4.026720e-07 2.013360e-07 [231,] 0.999999629 7.414235e-07 3.707117e-07 [232,] 0.999999289 1.422954e-06 7.114771e-07 [233,] 0.999998623 2.754512e-06 1.377256e-06 [234,] 0.999997499 5.001552e-06 2.500776e-06 [235,] 0.999995755 8.490797e-06 4.245398e-06 [236,] 0.999992188 1.562410e-05 7.812050e-06 [237,] 0.999985965 2.806911e-05 1.403455e-05 [238,] 0.999975508 4.898462e-05 2.449231e-05 [239,] 0.999961047 7.790527e-05 3.895263e-05 [240,] 0.999947771 1.044575e-04 5.222875e-05 [241,] 0.999907593 1.848138e-04 9.240688e-05 [242,] 0.999863441 2.731174e-04 1.365587e-04 [243,] 0.999905461 1.890774e-04 9.453871e-05 [244,] 0.999831961 3.360786e-04 1.680393e-04 [245,] 0.999790803 4.183939e-04 2.091970e-04 [246,] 0.999640539 7.189229e-04 3.594615e-04 [247,] 0.999378601 1.242798e-03 6.213992e-04 [248,] 0.999273901 1.452197e-03 7.260986e-04 [249,] 0.999049518 1.900963e-03 9.504817e-04 [250,] 0.998715563 2.568874e-03 1.284437e-03 [251,] 0.997813130 4.373739e-03 2.186870e-03 [252,] 0.996625423 6.749155e-03 3.374577e-03 [253,] 0.994497312 1.100538e-02 5.502688e-03 [254,] 0.991107639 1.778472e-02 8.892361e-03 [255,] 0.986733357 2.653329e-02 1.326664e-02 [256,] 0.984883360 3.023328e-02 1.511664e-02 [257,] 0.976444269 4.711146e-02 2.355573e-02 [258,] 0.970677001 5.864600e-02 2.932300e-02 [259,] 0.958892743 8.221451e-02 4.110726e-02 [260,] 0.939070955 1.218581e-01 6.092905e-02 [261,] 0.913889791 1.722204e-01 8.611021e-02 [262,] 0.936881183 1.262376e-01 6.311882e-02 [263,] 0.968951316 6.209737e-02 3.104868e-02 [264,] 0.954382412 9.123518e-02 4.561759e-02 [265,] 0.928174533 1.436509e-01 7.182547e-02 [266,] 0.897119406 2.057612e-01 1.028806e-01 [267,] 0.846229975 3.075400e-01 1.537700e-01 [268,] 0.806430967 3.871381e-01 1.935690e-01 [269,] 0.724024759 5.519505e-01 2.759752e-01 [270,] 0.624383215 7.512336e-01 3.756168e-01 [271,] 0.506029053 9.879419e-01 4.939709e-01 [272,] 0.420999224 8.419984e-01 5.790008e-01 [273,] 0.431814518 8.636290e-01 5.681855e-01 [274,] 0.429521617 8.590432e-01 5.704784e-01 > postscript(file="/var/wessaorg/rcomp/tmp/1bq2i1324138735.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') > points(x[,1]-mysum$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/25pga1324138735.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/3i4dm1324138735.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4unec1324138735.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5ya4l1324138735.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > qqline(mysum$resid) > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 289 Frequency = 1 1 2 3 4 5 6 20606.6700 8853.3032 13548.9448 -5662.8812 -4112.0629 24988.6534 7 8 9 10 11 12 -3450.0412 10427.7506 -12708.0686 24020.2051 -5586.1063 -27599.8993 13 14 15 16 17 18 -20767.3593 2472.2145 -13194.6443 802.3371 -34910.3750 27406.0727 19 20 21 22 23 24 25750.0111 24940.2796 27397.1925 -20671.4852 -23347.8590 -2788.1571 25 26 27 28 29 30 9295.7695 -31233.4199 -13200.2304 5209.8933 -27332.1512 -19134.4638 31 32 33 34 35 36 -1260.8898 -12343.0801 5402.7953 -30696.0282 16438.4116 -25821.3139 37 38 39 40 41 42 -8495.6540 1579.4586 -32734.4100 -1594.0264 -10760.4657 -13532.0257 43 44 45 46 47 48 -10791.5972 -29505.4596 -22917.1027 -7821.7574 -24928.8268 -2231.1012 49 50 51 52 53 54 -6152.8130 37926.1410 23035.7061 -8666.0738 -8156.4506 40401.5298 55 56 57 58 59 60 -12861.8224 -13894.2464 -4312.6660 16996.7835 1380.6229 774.8861 61 62 63 64 65 66 -13914.3634 17635.1242 31845.5028 -13274.2202 5293.5433 -21925.2613 67 68 69 70 71 72 -5436.6021 20670.4893 22961.6629 -9630.5558 -5436.4281 -9331.7734 73 74 75 76 77 78 -18241.7854 32911.7892 -19703.0636 17191.4151 14829.6387 -13401.6875 79 80 81 82 83 84 -9662.8019 -19345.8019 7923.1776 -11977.8580 -9607.9941 -1341.1615 85 86 87 88 89 90 154512.0012 -10946.3559 -8439.5122 -11673.6568 -943.0085 -21598.7632 91 92 93 94 95 96 7796.7200 25965.4436 -22379.4844 -6048.0030 -18458.4292 2633.3284 97 98 99 100 101 102 -32124.4080 11852.7060 -15200.3143 12180.7928 4546.0645 -23991.6873 103 104 105 106 107 108 -1865.4953 26593.9269 34506.0981 46325.9881 -20985.0337 -7093.5209 109 110 111 112 113 114 29864.3047 -11194.2678 28024.3460 -5782.6883 6371.7421 -10475.8579 115 116 117 118 119 120 -15803.9587 -23008.7979 -8279.1343 -16363.4606 119747.3696 4570.8074 121 122 123 124 125 126 -19511.9610 -10116.3010 -13499.6214 92451.2510 25984.6436 -5228.9006 127 128 129 130 131 132 11398.3289 -9074.6456 9126.3918 -2331.7806 1258.3971 -15095.5205 133 134 135 136 137 138 2794.9567 -22808.6606 -15130.3909 -1716.8660 -2765.6196 39155.5489 139 140 141 142 143 144 26362.6384 209.5180 -9913.8848 11125.8361 -8106.4987 -16931.1971 145 146 147 148 149 150 14997.3736 2198.9890 39502.9928 43051.4033 -4817.7910 6435.5723 151 152 153 154 155 156 -28699.0322 -10679.8927 4385.7227 -28039.3189 17164.6107 55289.9091 157 158 159 160 161 162 -12261.0164 -5215.9449 11290.5062 3793.5401 420.4312 73620.7835 163 164 165 166 167 168 -1752.6275 4019.6375 -7587.2635 -28805.2236 -12311.8735 36982.0155 169 170 171 172 173 174 -12367.1304 21495.5623 18419.8762 7825.2999 -5995.6953 -8603.9883 175 176 177 178 179 180 40270.3008 -18049.4439 32256.9294 -13005.0135 17330.8976 -14810.1425 181 182 183 184 185 186 13584.8672 20984.0797 -431.7885 -994.0575 -24765.8282 -1295.9074 187 188 189 190 191 192 -6654.2363 -5043.8278 -16077.4466 9258.4208 15119.6484 -10774.1520 193 194 195 196 197 198 -8934.8591 2121.5667 -8264.2032 -7917.8856 -18966.9202 35120.5115 199 200 201 202 203 204 23800.2303 9051.9530 -13215.7748 -11634.9953 -11234.3333 -7415.8176 205 206 207 208 209 210 -11778.4050 -624.0760 -16640.8484 -12865.8780 -13922.6018 -26995.6566 211 212 213 214 215 216 -9710.0516 -5739.0140 -7907.6823 -18563.2938 15041.1489 -27675.5181 217 218 219 220 221 222 -5594.9331 15343.8139 -10075.8307 -13717.0228 -12943.5592 1624.6165 223 224 225 226 227 228 -11428.5285 -7668.6328 -13748.6370 -8115.7808 21963.7684 1665.3971 229 230 231 232 233 234 -7418.0801 23783.7742 -16006.1555 -8859.0221 16518.8231 -3414.1060 235 236 237 238 239 240 3337.0243 -9424.7060 -8149.2745 -2725.6733 -11746.4190 -6358.2602 241 242 243 244 245 246 6137.1041 -18368.8762 -10159.4289 -3705.4948 -1642.4992 6816.0711 247 248 249 250 251 252 6432.0329 -2214.3959 11936.3708 14634.2483 -5936.6328 -191.5769 253 254 255 256 257 258 -300.0636 -11013.1463 -16179.7892 -3663.2342 5532.7331 -3903.2209 259 260 261 262 263 264 -13312.7877 -4443.7948 -3036.2596 -19189.9023 -6403.8339 -9078.5646 265 266 267 268 269 270 6577.3492 -4350.3663 -14826.9037 10759.5266 -21561.9828 14366.4880 271 272 273 274 275 276 -7838.0745 -6635.4529 -2185.2316 -6435.6119 -978.2647 3355.6115 277 278 279 280 281 282 17175.2129 -2746.2752 -14921.8672 -16508.2266 -10712.3400 59531.6633 283 284 285 286 287 288 12498.5185 -2262.0722 -12530.6906 18450.8878 -13648.0040 -9609.0665 289 -10321.8695 > postscript(file="/var/wessaorg/rcomp/tmp/6qz5h1324138735.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 289 Frequency = 1 lag(myerror, k = 1) myerror 0 20606.6700 NA 1 8853.3032 20606.6700 2 13548.9448 8853.3032 3 -5662.8812 13548.9448 4 -4112.0629 -5662.8812 5 24988.6534 -4112.0629 6 -3450.0412 24988.6534 7 10427.7506 -3450.0412 8 -12708.0686 10427.7506 9 24020.2051 -12708.0686 10 -5586.1063 24020.2051 11 -27599.8993 -5586.1063 12 -20767.3593 -27599.8993 13 2472.2145 -20767.3593 14 -13194.6443 2472.2145 15 802.3371 -13194.6443 16 -34910.3750 802.3371 17 27406.0727 -34910.3750 18 25750.0111 27406.0727 19 24940.2796 25750.0111 20 27397.1925 24940.2796 21 -20671.4852 27397.1925 22 -23347.8590 -20671.4852 23 -2788.1571 -23347.8590 24 9295.7695 -2788.1571 25 -31233.4199 9295.7695 26 -13200.2304 -31233.4199 27 5209.8933 -13200.2304 28 -27332.1512 5209.8933 29 -19134.4638 -27332.1512 30 -1260.8898 -19134.4638 31 -12343.0801 -1260.8898 32 5402.7953 -12343.0801 33 -30696.0282 5402.7953 34 16438.4116 -30696.0282 35 -25821.3139 16438.4116 36 -8495.6540 -25821.3139 37 1579.4586 -8495.6540 38 -32734.4100 1579.4586 39 -1594.0264 -32734.4100 40 -10760.4657 -1594.0264 41 -13532.0257 -10760.4657 42 -10791.5972 -13532.0257 43 -29505.4596 -10791.5972 44 -22917.1027 -29505.4596 45 -7821.7574 -22917.1027 46 -24928.8268 -7821.7574 47 -2231.1012 -24928.8268 48 -6152.8130 -2231.1012 49 37926.1410 -6152.8130 50 23035.7061 37926.1410 51 -8666.0738 23035.7061 52 -8156.4506 -8666.0738 53 40401.5298 -8156.4506 54 -12861.8224 40401.5298 55 -13894.2464 -12861.8224 56 -4312.6660 -13894.2464 57 16996.7835 -4312.6660 58 1380.6229 16996.7835 59 774.8861 1380.6229 60 -13914.3634 774.8861 61 17635.1242 -13914.3634 62 31845.5028 17635.1242 63 -13274.2202 31845.5028 64 5293.5433 -13274.2202 65 -21925.2613 5293.5433 66 -5436.6021 -21925.2613 67 20670.4893 -5436.6021 68 22961.6629 20670.4893 69 -9630.5558 22961.6629 70 -5436.4281 -9630.5558 71 -9331.7734 -5436.4281 72 -18241.7854 -9331.7734 73 32911.7892 -18241.7854 74 -19703.0636 32911.7892 75 17191.4151 -19703.0636 76 14829.6387 17191.4151 77 -13401.6875 14829.6387 78 -9662.8019 -13401.6875 79 -19345.8019 -9662.8019 80 7923.1776 -19345.8019 81 -11977.8580 7923.1776 82 -9607.9941 -11977.8580 83 -1341.1615 -9607.9941 84 154512.0012 -1341.1615 85 -10946.3559 154512.0012 86 -8439.5122 -10946.3559 87 -11673.6568 -8439.5122 88 -943.0085 -11673.6568 89 -21598.7632 -943.0085 90 7796.7200 -21598.7632 91 25965.4436 7796.7200 92 -22379.4844 25965.4436 93 -6048.0030 -22379.4844 94 -18458.4292 -6048.0030 95 2633.3284 -18458.4292 96 -32124.4080 2633.3284 97 11852.7060 -32124.4080 98 -15200.3143 11852.7060 99 12180.7928 -15200.3143 100 4546.0645 12180.7928 101 -23991.6873 4546.0645 102 -1865.4953 -23991.6873 103 26593.9269 -1865.4953 104 34506.0981 26593.9269 105 46325.9881 34506.0981 106 -20985.0337 46325.9881 107 -7093.5209 -20985.0337 108 29864.3047 -7093.5209 109 -11194.2678 29864.3047 110 28024.3460 -11194.2678 111 -5782.6883 28024.3460 112 6371.7421 -5782.6883 113 -10475.8579 6371.7421 114 -15803.9587 -10475.8579 115 -23008.7979 -15803.9587 116 -8279.1343 -23008.7979 117 -16363.4606 -8279.1343 118 119747.3696 -16363.4606 119 4570.8074 119747.3696 120 -19511.9610 4570.8074 121 -10116.3010 -19511.9610 122 -13499.6214 -10116.3010 123 92451.2510 -13499.6214 124 25984.6436 92451.2510 125 -5228.9006 25984.6436 126 11398.3289 -5228.9006 127 -9074.6456 11398.3289 128 9126.3918 -9074.6456 129 -2331.7806 9126.3918 130 1258.3971 -2331.7806 131 -15095.5205 1258.3971 132 2794.9567 -15095.5205 133 -22808.6606 2794.9567 134 -15130.3909 -22808.6606 135 -1716.8660 -15130.3909 136 -2765.6196 -1716.8660 137 39155.5489 -2765.6196 138 26362.6384 39155.5489 139 209.5180 26362.6384 140 -9913.8848 209.5180 141 11125.8361 -9913.8848 142 -8106.4987 11125.8361 143 -16931.1971 -8106.4987 144 14997.3736 -16931.1971 145 2198.9890 14997.3736 146 39502.9928 2198.9890 147 43051.4033 39502.9928 148 -4817.7910 43051.4033 149 6435.5723 -4817.7910 150 -28699.0322 6435.5723 151 -10679.8927 -28699.0322 152 4385.7227 -10679.8927 153 -28039.3189 4385.7227 154 17164.6107 -28039.3189 155 55289.9091 17164.6107 156 -12261.0164 55289.9091 157 -5215.9449 -12261.0164 158 11290.5062 -5215.9449 159 3793.5401 11290.5062 160 420.4312 3793.5401 161 73620.7835 420.4312 162 -1752.6275 73620.7835 163 4019.6375 -1752.6275 164 -7587.2635 4019.6375 165 -28805.2236 -7587.2635 166 -12311.8735 -28805.2236 167 36982.0155 -12311.8735 168 -12367.1304 36982.0155 169 21495.5623 -12367.1304 170 18419.8762 21495.5623 171 7825.2999 18419.8762 172 -5995.6953 7825.2999 173 -8603.9883 -5995.6953 174 40270.3008 -8603.9883 175 -18049.4439 40270.3008 176 32256.9294 -18049.4439 177 -13005.0135 32256.9294 178 17330.8976 -13005.0135 179 -14810.1425 17330.8976 180 13584.8672 -14810.1425 181 20984.0797 13584.8672 182 -431.7885 20984.0797 183 -994.0575 -431.7885 184 -24765.8282 -994.0575 185 -1295.9074 -24765.8282 186 -6654.2363 -1295.9074 187 -5043.8278 -6654.2363 188 -16077.4466 -5043.8278 189 9258.4208 -16077.4466 190 15119.6484 9258.4208 191 -10774.1520 15119.6484 192 -8934.8591 -10774.1520 193 2121.5667 -8934.8591 194 -8264.2032 2121.5667 195 -7917.8856 -8264.2032 196 -18966.9202 -7917.8856 197 35120.5115 -18966.9202 198 23800.2303 35120.5115 199 9051.9530 23800.2303 200 -13215.7748 9051.9530 201 -11634.9953 -13215.7748 202 -11234.3333 -11634.9953 203 -7415.8176 -11234.3333 204 -11778.4050 -7415.8176 205 -624.0760 -11778.4050 206 -16640.8484 -624.0760 207 -12865.8780 -16640.8484 208 -13922.6018 -12865.8780 209 -26995.6566 -13922.6018 210 -9710.0516 -26995.6566 211 -5739.0140 -9710.0516 212 -7907.6823 -5739.0140 213 -18563.2938 -7907.6823 214 15041.1489 -18563.2938 215 -27675.5181 15041.1489 216 -5594.9331 -27675.5181 217 15343.8139 -5594.9331 218 -10075.8307 15343.8139 219 -13717.0228 -10075.8307 220 -12943.5592 -13717.0228 221 1624.6165 -12943.5592 222 -11428.5285 1624.6165 223 -7668.6328 -11428.5285 224 -13748.6370 -7668.6328 225 -8115.7808 -13748.6370 226 21963.7684 -8115.7808 227 1665.3971 21963.7684 228 -7418.0801 1665.3971 229 23783.7742 -7418.0801 230 -16006.1555 23783.7742 231 -8859.0221 -16006.1555 232 16518.8231 -8859.0221 233 -3414.1060 16518.8231 234 3337.0243 -3414.1060 235 -9424.7060 3337.0243 236 -8149.2745 -9424.7060 237 -2725.6733 -8149.2745 238 -11746.4190 -2725.6733 239 -6358.2602 -11746.4190 240 6137.1041 -6358.2602 241 -18368.8762 6137.1041 242 -10159.4289 -18368.8762 243 -3705.4948 -10159.4289 244 -1642.4992 -3705.4948 245 6816.0711 -1642.4992 246 6432.0329 6816.0711 247 -2214.3959 6432.0329 248 11936.3708 -2214.3959 249 14634.2483 11936.3708 250 -5936.6328 14634.2483 251 -191.5769 -5936.6328 252 -300.0636 -191.5769 253 -11013.1463 -300.0636 254 -16179.7892 -11013.1463 255 -3663.2342 -16179.7892 256 5532.7331 -3663.2342 257 -3903.2209 5532.7331 258 -13312.7877 -3903.2209 259 -4443.7948 -13312.7877 260 -3036.2596 -4443.7948 261 -19189.9023 -3036.2596 262 -6403.8339 -19189.9023 263 -9078.5646 -6403.8339 264 6577.3492 -9078.5646 265 -4350.3663 6577.3492 266 -14826.9037 -4350.3663 267 10759.5266 -14826.9037 268 -21561.9828 10759.5266 269 14366.4880 -21561.9828 270 -7838.0745 14366.4880 271 -6635.4529 -7838.0745 272 -2185.2316 -6635.4529 273 -6435.6119 -2185.2316 274 -978.2647 -6435.6119 275 3355.6115 -978.2647 276 17175.2129 3355.6115 277 -2746.2752 17175.2129 278 -14921.8672 -2746.2752 279 -16508.2266 -14921.8672 280 -10712.3400 -16508.2266 281 59531.6633 -10712.3400 282 12498.5185 59531.6633 283 -2262.0722 12498.5185 284 -12530.6906 -2262.0722 285 18450.8878 -12530.6906 286 -13648.0040 18450.8878 287 -9609.0665 -13648.0040 288 -10321.8695 -9609.0665 289 NA -10321.8695 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 8853.3032 20606.6700 [2,] 13548.9448 8853.3032 [3,] -5662.8812 13548.9448 [4,] -4112.0629 -5662.8812 [5,] 24988.6534 -4112.0629 [6,] -3450.0412 24988.6534 [7,] 10427.7506 -3450.0412 [8,] -12708.0686 10427.7506 [9,] 24020.2051 -12708.0686 [10,] -5586.1063 24020.2051 [11,] -27599.8993 -5586.1063 [12,] -20767.3593 -27599.8993 [13,] 2472.2145 -20767.3593 [14,] -13194.6443 2472.2145 [15,] 802.3371 -13194.6443 [16,] -34910.3750 802.3371 [17,] 27406.0727 -34910.3750 [18,] 25750.0111 27406.0727 [19,] 24940.2796 25750.0111 [20,] 27397.1925 24940.2796 [21,] -20671.4852 27397.1925 [22,] -23347.8590 -20671.4852 [23,] -2788.1571 -23347.8590 [24,] 9295.7695 -2788.1571 [25,] -31233.4199 9295.7695 [26,] -13200.2304 -31233.4199 [27,] 5209.8933 -13200.2304 [28,] -27332.1512 5209.8933 [29,] -19134.4638 -27332.1512 [30,] -1260.8898 -19134.4638 [31,] -12343.0801 -1260.8898 [32,] 5402.7953 -12343.0801 [33,] -30696.0282 5402.7953 [34,] 16438.4116 -30696.0282 [35,] -25821.3139 16438.4116 [36,] -8495.6540 -25821.3139 [37,] 1579.4586 -8495.6540 [38,] -32734.4100 1579.4586 [39,] -1594.0264 -32734.4100 [40,] -10760.4657 -1594.0264 [41,] -13532.0257 -10760.4657 [42,] -10791.5972 -13532.0257 [43,] -29505.4596 -10791.5972 [44,] -22917.1027 -29505.4596 [45,] -7821.7574 -22917.1027 [46,] -24928.8268 -7821.7574 [47,] -2231.1012 -24928.8268 [48,] -6152.8130 -2231.1012 [49,] 37926.1410 -6152.8130 [50,] 23035.7061 37926.1410 [51,] -8666.0738 23035.7061 [52,] -8156.4506 -8666.0738 [53,] 40401.5298 -8156.4506 [54,] -12861.8224 40401.5298 [55,] -13894.2464 -12861.8224 [56,] -4312.6660 -13894.2464 [57,] 16996.7835 -4312.6660 [58,] 1380.6229 16996.7835 [59,] 774.8861 1380.6229 [60,] -13914.3634 774.8861 [61,] 17635.1242 -13914.3634 [62,] 31845.5028 17635.1242 [63,] -13274.2202 31845.5028 [64,] 5293.5433 -13274.2202 [65,] -21925.2613 5293.5433 [66,] -5436.6021 -21925.2613 [67,] 20670.4893 -5436.6021 [68,] 22961.6629 20670.4893 [69,] -9630.5558 22961.6629 [70,] -5436.4281 -9630.5558 [71,] -9331.7734 -5436.4281 [72,] -18241.7854 -9331.7734 [73,] 32911.7892 -18241.7854 [74,] -19703.0636 32911.7892 [75,] 17191.4151 -19703.0636 [76,] 14829.6387 17191.4151 [77,] -13401.6875 14829.6387 [78,] -9662.8019 -13401.6875 [79,] -19345.8019 -9662.8019 [80,] 7923.1776 -19345.8019 [81,] -11977.8580 7923.1776 [82,] -9607.9941 -11977.8580 [83,] -1341.1615 -9607.9941 [84,] 154512.0012 -1341.1615 [85,] -10946.3559 154512.0012 [86,] -8439.5122 -10946.3559 [87,] -11673.6568 -8439.5122 [88,] -943.0085 -11673.6568 [89,] -21598.7632 -943.0085 [90,] 7796.7200 -21598.7632 [91,] 25965.4436 7796.7200 [92,] -22379.4844 25965.4436 [93,] -6048.0030 -22379.4844 [94,] -18458.4292 -6048.0030 [95,] 2633.3284 -18458.4292 [96,] -32124.4080 2633.3284 [97,] 11852.7060 -32124.4080 [98,] -15200.3143 11852.7060 [99,] 12180.7928 -15200.3143 [100,] 4546.0645 12180.7928 [101,] -23991.6873 4546.0645 [102,] -1865.4953 -23991.6873 [103,] 26593.9269 -1865.4953 [104,] 34506.0981 26593.9269 [105,] 46325.9881 34506.0981 [106,] -20985.0337 46325.9881 [107,] -7093.5209 -20985.0337 [108,] 29864.3047 -7093.5209 [109,] -11194.2678 29864.3047 [110,] 28024.3460 -11194.2678 [111,] -5782.6883 28024.3460 [112,] 6371.7421 -5782.6883 [113,] -10475.8579 6371.7421 [114,] -15803.9587 -10475.8579 [115,] -23008.7979 -15803.9587 [116,] -8279.1343 -23008.7979 [117,] -16363.4606 -8279.1343 [118,] 119747.3696 -16363.4606 [119,] 4570.8074 119747.3696 [120,] -19511.9610 4570.8074 [121,] -10116.3010 -19511.9610 [122,] -13499.6214 -10116.3010 [123,] 92451.2510 -13499.6214 [124,] 25984.6436 92451.2510 [125,] -5228.9006 25984.6436 [126,] 11398.3289 -5228.9006 [127,] -9074.6456 11398.3289 [128,] 9126.3918 -9074.6456 [129,] -2331.7806 9126.3918 [130,] 1258.3971 -2331.7806 [131,] -15095.5205 1258.3971 [132,] 2794.9567 -15095.5205 [133,] -22808.6606 2794.9567 [134,] -15130.3909 -22808.6606 [135,] -1716.8660 -15130.3909 [136,] -2765.6196 -1716.8660 [137,] 39155.5489 -2765.6196 [138,] 26362.6384 39155.5489 [139,] 209.5180 26362.6384 [140,] -9913.8848 209.5180 [141,] 11125.8361 -9913.8848 [142,] -8106.4987 11125.8361 [143,] -16931.1971 -8106.4987 [144,] 14997.3736 -16931.1971 [145,] 2198.9890 14997.3736 [146,] 39502.9928 2198.9890 [147,] 43051.4033 39502.9928 [148,] -4817.7910 43051.4033 [149,] 6435.5723 -4817.7910 [150,] -28699.0322 6435.5723 [151,] -10679.8927 -28699.0322 [152,] 4385.7227 -10679.8927 [153,] -28039.3189 4385.7227 [154,] 17164.6107 -28039.3189 [155,] 55289.9091 17164.6107 [156,] -12261.0164 55289.9091 [157,] -5215.9449 -12261.0164 [158,] 11290.5062 -5215.9449 [159,] 3793.5401 11290.5062 [160,] 420.4312 3793.5401 [161,] 73620.7835 420.4312 [162,] -1752.6275 73620.7835 [163,] 4019.6375 -1752.6275 [164,] -7587.2635 4019.6375 [165,] -28805.2236 -7587.2635 [166,] -12311.8735 -28805.2236 [167,] 36982.0155 -12311.8735 [168,] -12367.1304 36982.0155 [169,] 21495.5623 -12367.1304 [170,] 18419.8762 21495.5623 [171,] 7825.2999 18419.8762 [172,] -5995.6953 7825.2999 [173,] -8603.9883 -5995.6953 [174,] 40270.3008 -8603.9883 [175,] -18049.4439 40270.3008 [176,] 32256.9294 -18049.4439 [177,] -13005.0135 32256.9294 [178,] 17330.8976 -13005.0135 [179,] -14810.1425 17330.8976 [180,] 13584.8672 -14810.1425 [181,] 20984.0797 13584.8672 [182,] -431.7885 20984.0797 [183,] -994.0575 -431.7885 [184,] -24765.8282 -994.0575 [185,] -1295.9074 -24765.8282 [186,] -6654.2363 -1295.9074 [187,] -5043.8278 -6654.2363 [188,] -16077.4466 -5043.8278 [189,] 9258.4208 -16077.4466 [190,] 15119.6484 9258.4208 [191,] -10774.1520 15119.6484 [192,] -8934.8591 -10774.1520 [193,] 2121.5667 -8934.8591 [194,] -8264.2032 2121.5667 [195,] -7917.8856 -8264.2032 [196,] -18966.9202 -7917.8856 [197,] 35120.5115 -18966.9202 [198,] 23800.2303 35120.5115 [199,] 9051.9530 23800.2303 [200,] -13215.7748 9051.9530 [201,] -11634.9953 -13215.7748 [202,] -11234.3333 -11634.9953 [203,] -7415.8176 -11234.3333 [204,] -11778.4050 -7415.8176 [205,] -624.0760 -11778.4050 [206,] -16640.8484 -624.0760 [207,] -12865.8780 -16640.8484 [208,] -13922.6018 -12865.8780 [209,] -26995.6566 -13922.6018 [210,] -9710.0516 -26995.6566 [211,] -5739.0140 -9710.0516 [212,] -7907.6823 -5739.0140 [213,] -18563.2938 -7907.6823 [214,] 15041.1489 -18563.2938 [215,] -27675.5181 15041.1489 [216,] -5594.9331 -27675.5181 [217,] 15343.8139 -5594.9331 [218,] -10075.8307 15343.8139 [219,] -13717.0228 -10075.8307 [220,] -12943.5592 -13717.0228 [221,] 1624.6165 -12943.5592 [222,] -11428.5285 1624.6165 [223,] -7668.6328 -11428.5285 [224,] -13748.6370 -7668.6328 [225,] -8115.7808 -13748.6370 [226,] 21963.7684 -8115.7808 [227,] 1665.3971 21963.7684 [228,] -7418.0801 1665.3971 [229,] 23783.7742 -7418.0801 [230,] -16006.1555 23783.7742 [231,] -8859.0221 -16006.1555 [232,] 16518.8231 -8859.0221 [233,] -3414.1060 16518.8231 [234,] 3337.0243 -3414.1060 [235,] -9424.7060 3337.0243 [236,] -8149.2745 -9424.7060 [237,] -2725.6733 -8149.2745 [238,] -11746.4190 -2725.6733 [239,] -6358.2602 -11746.4190 [240,] 6137.1041 -6358.2602 [241,] -18368.8762 6137.1041 [242,] -10159.4289 -18368.8762 [243,] -3705.4948 -10159.4289 [244,] -1642.4992 -3705.4948 [245,] 6816.0711 -1642.4992 [246,] 6432.0329 6816.0711 [247,] -2214.3959 6432.0329 [248,] 11936.3708 -2214.3959 [249,] 14634.2483 11936.3708 [250,] -5936.6328 14634.2483 [251,] -191.5769 -5936.6328 [252,] -300.0636 -191.5769 [253,] -11013.1463 -300.0636 [254,] -16179.7892 -11013.1463 [255,] -3663.2342 -16179.7892 [256,] 5532.7331 -3663.2342 [257,] -3903.2209 5532.7331 [258,] -13312.7877 -3903.2209 [259,] -4443.7948 -13312.7877 [260,] -3036.2596 -4443.7948 [261,] -19189.9023 -3036.2596 [262,] -6403.8339 -19189.9023 [263,] -9078.5646 -6403.8339 [264,] 6577.3492 -9078.5646 [265,] -4350.3663 6577.3492 [266,] -14826.9037 -4350.3663 [267,] 10759.5266 -14826.9037 [268,] -21561.9828 10759.5266 [269,] 14366.4880 -21561.9828 [270,] -7838.0745 14366.4880 [271,] -6635.4529 -7838.0745 [272,] -2185.2316 -6635.4529 [273,] -6435.6119 -2185.2316 [274,] -978.2647 -6435.6119 [275,] 3355.6115 -978.2647 [276,] 17175.2129 3355.6115 [277,] -2746.2752 17175.2129 [278,] -14921.8672 -2746.2752 [279,] -16508.2266 -14921.8672 [280,] -10712.3400 -16508.2266 [281,] 59531.6633 -10712.3400 [282,] 12498.5185 59531.6633 [283,] -2262.0722 12498.5185 [284,] -12530.6906 -2262.0722 [285,] 18450.8878 -12530.6906 [286,] -13648.0040 18450.8878 [287,] -9609.0665 -13648.0040 [288,] -10321.8695 -9609.0665 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 8853.3032 20606.6700 2 13548.9448 8853.3032 3 -5662.8812 13548.9448 4 -4112.0629 -5662.8812 5 24988.6534 -4112.0629 6 -3450.0412 24988.6534 7 10427.7506 -3450.0412 8 -12708.0686 10427.7506 9 24020.2051 -12708.0686 10 -5586.1063 24020.2051 11 -27599.8993 -5586.1063 12 -20767.3593 -27599.8993 13 2472.2145 -20767.3593 14 -13194.6443 2472.2145 15 802.3371 -13194.6443 16 -34910.3750 802.3371 17 27406.0727 -34910.3750 18 25750.0111 27406.0727 19 24940.2796 25750.0111 20 27397.1925 24940.2796 21 -20671.4852 27397.1925 22 -23347.8590 -20671.4852 23 -2788.1571 -23347.8590 24 9295.7695 -2788.1571 25 -31233.4199 9295.7695 26 -13200.2304 -31233.4199 27 5209.8933 -13200.2304 28 -27332.1512 5209.8933 29 -19134.4638 -27332.1512 30 -1260.8898 -19134.4638 31 -12343.0801 -1260.8898 32 5402.7953 -12343.0801 33 -30696.0282 5402.7953 34 16438.4116 -30696.0282 35 -25821.3139 16438.4116 36 -8495.6540 -25821.3139 37 1579.4586 -8495.6540 38 -32734.4100 1579.4586 39 -1594.0264 -32734.4100 40 -10760.4657 -1594.0264 41 -13532.0257 -10760.4657 42 -10791.5972 -13532.0257 43 -29505.4596 -10791.5972 44 -22917.1027 -29505.4596 45 -7821.7574 -22917.1027 46 -24928.8268 -7821.7574 47 -2231.1012 -24928.8268 48 -6152.8130 -2231.1012 49 37926.1410 -6152.8130 50 23035.7061 37926.1410 51 -8666.0738 23035.7061 52 -8156.4506 -8666.0738 53 40401.5298 -8156.4506 54 -12861.8224 40401.5298 55 -13894.2464 -12861.8224 56 -4312.6660 -13894.2464 57 16996.7835 -4312.6660 58 1380.6229 16996.7835 59 774.8861 1380.6229 60 -13914.3634 774.8861 61 17635.1242 -13914.3634 62 31845.5028 17635.1242 63 -13274.2202 31845.5028 64 5293.5433 -13274.2202 65 -21925.2613 5293.5433 66 -5436.6021 -21925.2613 67 20670.4893 -5436.6021 68 22961.6629 20670.4893 69 -9630.5558 22961.6629 70 -5436.4281 -9630.5558 71 -9331.7734 -5436.4281 72 -18241.7854 -9331.7734 73 32911.7892 -18241.7854 74 -19703.0636 32911.7892 75 17191.4151 -19703.0636 76 14829.6387 17191.4151 77 -13401.6875 14829.6387 78 -9662.8019 -13401.6875 79 -19345.8019 -9662.8019 80 7923.1776 -19345.8019 81 -11977.8580 7923.1776 82 -9607.9941 -11977.8580 83 -1341.1615 -9607.9941 84 154512.0012 -1341.1615 85 -10946.3559 154512.0012 86 -8439.5122 -10946.3559 87 -11673.6568 -8439.5122 88 -943.0085 -11673.6568 89 -21598.7632 -943.0085 90 7796.7200 -21598.7632 91 25965.4436 7796.7200 92 -22379.4844 25965.4436 93 -6048.0030 -22379.4844 94 -18458.4292 -6048.0030 95 2633.3284 -18458.4292 96 -32124.4080 2633.3284 97 11852.7060 -32124.4080 98 -15200.3143 11852.7060 99 12180.7928 -15200.3143 100 4546.0645 12180.7928 101 -23991.6873 4546.0645 102 -1865.4953 -23991.6873 103 26593.9269 -1865.4953 104 34506.0981 26593.9269 105 46325.9881 34506.0981 106 -20985.0337 46325.9881 107 -7093.5209 -20985.0337 108 29864.3047 -7093.5209 109 -11194.2678 29864.3047 110 28024.3460 -11194.2678 111 -5782.6883 28024.3460 112 6371.7421 -5782.6883 113 -10475.8579 6371.7421 114 -15803.9587 -10475.8579 115 -23008.7979 -15803.9587 116 -8279.1343 -23008.7979 117 -16363.4606 -8279.1343 118 119747.3696 -16363.4606 119 4570.8074 119747.3696 120 -19511.9610 4570.8074 121 -10116.3010 -19511.9610 122 -13499.6214 -10116.3010 123 92451.2510 -13499.6214 124 25984.6436 92451.2510 125 -5228.9006 25984.6436 126 11398.3289 -5228.9006 127 -9074.6456 11398.3289 128 9126.3918 -9074.6456 129 -2331.7806 9126.3918 130 1258.3971 -2331.7806 131 -15095.5205 1258.3971 132 2794.9567 -15095.5205 133 -22808.6606 2794.9567 134 -15130.3909 -22808.6606 135 -1716.8660 -15130.3909 136 -2765.6196 -1716.8660 137 39155.5489 -2765.6196 138 26362.6384 39155.5489 139 209.5180 26362.6384 140 -9913.8848 209.5180 141 11125.8361 -9913.8848 142 -8106.4987 11125.8361 143 -16931.1971 -8106.4987 144 14997.3736 -16931.1971 145 2198.9890 14997.3736 146 39502.9928 2198.9890 147 43051.4033 39502.9928 148 -4817.7910 43051.4033 149 6435.5723 -4817.7910 150 -28699.0322 6435.5723 151 -10679.8927 -28699.0322 152 4385.7227 -10679.8927 153 -28039.3189 4385.7227 154 17164.6107 -28039.3189 155 55289.9091 17164.6107 156 -12261.0164 55289.9091 157 -5215.9449 -12261.0164 158 11290.5062 -5215.9449 159 3793.5401 11290.5062 160 420.4312 3793.5401 161 73620.7835 420.4312 162 -1752.6275 73620.7835 163 4019.6375 -1752.6275 164 -7587.2635 4019.6375 165 -28805.2236 -7587.2635 166 -12311.8735 -28805.2236 167 36982.0155 -12311.8735 168 -12367.1304 36982.0155 169 21495.5623 -12367.1304 170 18419.8762 21495.5623 171 7825.2999 18419.8762 172 -5995.6953 7825.2999 173 -8603.9883 -5995.6953 174 40270.3008 -8603.9883 175 -18049.4439 40270.3008 176 32256.9294 -18049.4439 177 -13005.0135 32256.9294 178 17330.8976 -13005.0135 179 -14810.1425 17330.8976 180 13584.8672 -14810.1425 181 20984.0797 13584.8672 182 -431.7885 20984.0797 183 -994.0575 -431.7885 184 -24765.8282 -994.0575 185 -1295.9074 -24765.8282 186 -6654.2363 -1295.9074 187 -5043.8278 -6654.2363 188 -16077.4466 -5043.8278 189 9258.4208 -16077.4466 190 15119.6484 9258.4208 191 -10774.1520 15119.6484 192 -8934.8591 -10774.1520 193 2121.5667 -8934.8591 194 -8264.2032 2121.5667 195 -7917.8856 -8264.2032 196 -18966.9202 -7917.8856 197 35120.5115 -18966.9202 198 23800.2303 35120.5115 199 9051.9530 23800.2303 200 -13215.7748 9051.9530 201 -11634.9953 -13215.7748 202 -11234.3333 -11634.9953 203 -7415.8176 -11234.3333 204 -11778.4050 -7415.8176 205 -624.0760 -11778.4050 206 -16640.8484 -624.0760 207 -12865.8780 -16640.8484 208 -13922.6018 -12865.8780 209 -26995.6566 -13922.6018 210 -9710.0516 -26995.6566 211 -5739.0140 -9710.0516 212 -7907.6823 -5739.0140 213 -18563.2938 -7907.6823 214 15041.1489 -18563.2938 215 -27675.5181 15041.1489 216 -5594.9331 -27675.5181 217 15343.8139 -5594.9331 218 -10075.8307 15343.8139 219 -13717.0228 -10075.8307 220 -12943.5592 -13717.0228 221 1624.6165 -12943.5592 222 -11428.5285 1624.6165 223 -7668.6328 -11428.5285 224 -13748.6370 -7668.6328 225 -8115.7808 -13748.6370 226 21963.7684 -8115.7808 227 1665.3971 21963.7684 228 -7418.0801 1665.3971 229 23783.7742 -7418.0801 230 -16006.1555 23783.7742 231 -8859.0221 -16006.1555 232 16518.8231 -8859.0221 233 -3414.1060 16518.8231 234 3337.0243 -3414.1060 235 -9424.7060 3337.0243 236 -8149.2745 -9424.7060 237 -2725.6733 -8149.2745 238 -11746.4190 -2725.6733 239 -6358.2602 -11746.4190 240 6137.1041 -6358.2602 241 -18368.8762 6137.1041 242 -10159.4289 -18368.8762 243 -3705.4948 -10159.4289 244 -1642.4992 -3705.4948 245 6816.0711 -1642.4992 246 6432.0329 6816.0711 247 -2214.3959 6432.0329 248 11936.3708 -2214.3959 249 14634.2483 11936.3708 250 -5936.6328 14634.2483 251 -191.5769 -5936.6328 252 -300.0636 -191.5769 253 -11013.1463 -300.0636 254 -16179.7892 -11013.1463 255 -3663.2342 -16179.7892 256 5532.7331 -3663.2342 257 -3903.2209 5532.7331 258 -13312.7877 -3903.2209 259 -4443.7948 -13312.7877 260 -3036.2596 -4443.7948 261 -19189.9023 -3036.2596 262 -6403.8339 -19189.9023 263 -9078.5646 -6403.8339 264 6577.3492 -9078.5646 265 -4350.3663 6577.3492 266 -14826.9037 -4350.3663 267 10759.5266 -14826.9037 268 -21561.9828 10759.5266 269 14366.4880 -21561.9828 270 -7838.0745 14366.4880 271 -6635.4529 -7838.0745 272 -2185.2316 -6635.4529 273 -6435.6119 -2185.2316 274 -978.2647 -6435.6119 275 3355.6115 -978.2647 276 17175.2129 3355.6115 277 -2746.2752 17175.2129 278 -14921.8672 -2746.2752 279 -16508.2266 -14921.8672 280 -10712.3400 -16508.2266 281 59531.6633 -10712.3400 282 12498.5185 59531.6633 283 -2262.0722 12498.5185 284 -12530.6906 -2262.0722 285 18450.8878 -12530.6906 286 -13648.0040 18450.8878 287 -9609.0665 -13648.0040 288 -10321.8695 -9609.0665 > plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') > lines(lowess(z)) > abline(lm(z)) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/79bbw1324138735.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/8gwss1324138735.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/9muas1324138735.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/10jr211324138735.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + 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") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/11vfnq1324138735.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) + a<-table.element(a,mysum$coefficients[i,1]) + a<-table.element(a, round(mysum$coefficients[i,2],6)) + a<-table.element(a, round(mysum$coefficients[i,3],4)) + a<-table.element(a, round(mysum$coefficients[i,4],6)) + a<-table.element(a, round(mysum$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/1232311324138735.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$r.squared)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'R-squared',1,TRUE) > a<-table.element(a, mysum$r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Adjusted R-squared',1,TRUE) > a<-table.element(a, mysum$adj.r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (value)',1,TRUE) > a<-table.element(a, mysum$fstatistic[1]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'p-value',1,TRUE) > a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3])) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Residual Standard Deviation',1,TRUE) > a<-table.element(a, mysum$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/13c7n31324138736.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/147skg1324138736.tab") > if (n > n25) { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'p-values',header=TRUE) + a<-table.element(a,'Alternative Hypothesis',3,header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'breakpoint index',header=TRUE) + a<-table.element(a,'greater',header=TRUE) + a<-table.element(a,'2-sided',header=TRUE) + a<-table.element(a,'less',header=TRUE) + a<-table.row.end(a) + for (mypoint in kp3:nmkm3) { + a<-table.row.start(a) + a<-table.element(a,mypoint,header=TRUE) + a<-table.element(a,gqarr[mypoint-kp3+1,1]) + a<-table.element(a,gqarr[mypoint-kp3+1,2]) + a<-table.element(a,gqarr[mypoint-kp3+1,3]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/154vck1324138736.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Description',header=TRUE) + a<-table.element(a,'# significant tests',header=TRUE) + a<-table.element(a,'% significant tests',header=TRUE) + a<-table.element(a,'OK/NOK',header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'1% type I error level',header=TRUE) + a<-table.element(a,numsignificant1) + a<-table.element(a,numsignificant1/numgqtests) + if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'5% type I error level',header=TRUE) + a<-table.element(a,numsignificant5) + a<-table.element(a,numsignificant5/numgqtests) + if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'10% type I error level',header=TRUE) + a<-table.element(a,numsignificant10) + a<-table.element(a,numsignificant10/numgqtests) + if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/16s4df1324138736.tab") + } > > try(system("convert tmp/1bq2i1324138735.ps tmp/1bq2i1324138735.png",intern=TRUE)) character(0) > try(system("convert tmp/25pga1324138735.ps tmp/25pga1324138735.png",intern=TRUE)) character(0) > try(system("convert tmp/3i4dm1324138735.ps tmp/3i4dm1324138735.png",intern=TRUE)) character(0) > try(system("convert tmp/4unec1324138735.ps tmp/4unec1324138735.png",intern=TRUE)) character(0) > try(system("convert tmp/5ya4l1324138735.ps tmp/5ya4l1324138735.png",intern=TRUE)) character(0) > try(system("convert tmp/6qz5h1324138735.ps tmp/6qz5h1324138735.png",intern=TRUE)) character(0) > try(system("convert tmp/79bbw1324138735.ps tmp/79bbw1324138735.png",intern=TRUE)) character(0) > try(system("convert tmp/8gwss1324138735.ps tmp/8gwss1324138735.png",intern=TRUE)) character(0) > try(system("convert tmp/9muas1324138735.ps tmp/9muas1324138735.png",intern=TRUE)) character(0) > try(system("convert tmp/10jr211324138735.ps tmp/10jr211324138735.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 8.053 0.666 8.783