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(146455 + ,1 + ,95556 + ,114468 + ,127 + ,128 + ,84944 + ,4 + ,54565 + ,88594 + ,90 + ,89 + ,113337 + ,9 + ,63016 + ,74151 + ,68 + ,68 + ,128655 + ,2 + ,79774 + ,77921 + ,111 + ,108 + ,74398 + ,1 + ,31258 + ,53212 + ,51 + ,51 + ,35523 + ,2 + ,52491 + ,34956 + ,33 + ,33 + ,293403 + ,0 + ,91256 + ,149703 + ,123 + ,119 + ,32750 + ,0 + ,22807 + ,6853 + ,5 + ,5 + ,106539 + ,5 + ,77411 + ,58907 + ,63 + ,63 + ,130539 + ,0 + ,48821 + ,67067 + ,66 + ,66 + ,154991 + ,0 + ,52295 + ,110563 + ,99 + ,98 + ,126683 + ,7 + ,63262 + ,58126 + ,72 + ,71 + ,100672 + ,6 + ,50466 + ,57113 + ,55 + ,55 + ,179562 + ,3 + ,62932 + ,77993 + ,116 + ,116 + ,125971 + ,4 + ,38439 + ,68091 + ,71 + ,71 + ,234509 + ,0 + ,70817 + ,124676 + ,125 + ,120 + ,158980 + ,4 + ,105965 + ,109522 + ,123 + ,122 + ,184217 + ,3 + ,73795 + ,75865 + ,74 + ,74 + ,107342 + ,0 + ,82043 + ,79746 + ,116 + ,111 + ,141371 + ,5 + ,74349 + ,77844 + ,117 + ,103 + ,154730 + ,0 + ,82204 + ,98681 + ,98 + ,98 + ,264020 + ,1 + ,55709 + ,105531 + ,101 + ,100 + ,90938 + ,3 + ,37137 + ,51428 + ,43 + ,42 + ,101324 + ,5 + ,70780 + ,65703 + ,103 + ,100 + ,130232 + ,0 + ,55027 + ,72562 + ,107 + ,105 + ,137793 + ,0 + ,56699 + ,81728 + ,77 + ,77 + ,161678 + ,4 + ,65911 + ,95580 + ,87 + ,83 + ,151503 + ,0 + ,56316 + ,98278 + ,99 + ,98 + ,105324 + ,0 + ,26982 + ,46629 + ,46 + ,46 + ,175914 + ,0 + ,54628 + ,115189 + ,96 + ,95 + ,181853 + ,3 + ,96750 + ,124865 + ,92 + ,91 + ,114928 + ,4 + ,53009 + ,59392 + ,96 + ,91 + ,190410 + ,1 + ,64664 + ,127818 + ,96 + ,94 + ,61499 + ,4 + ,36990 + ,17821 + ,15 + ,15 + ,223004 + ,1 + ,85224 + ,154076 + ,147 + ,137 + ,167131 + ,0 + ,37048 + ,64881 + ,56 + ,56 + ,233482 + ,0 + ,59635 + ,136506 + ,81 + ,78 + ,121185 + ,2 + ,42051 + ,66524 + ,69 + ,68 + ,78776 + ,1 + ,26998 + ,45988 + ,34 + ,34 + ,188967 + ,2 + ,63717 + ,107445 + ,98 + ,94 + ,199512 + ,8 + ,55071 + ,102772 + ,82 + ,82 + ,102531 + ,5 + ,40001 + ,46657 + ,64 + ,63 + ,118958 + ,3 + ,54506 + ,97563 + ,61 + ,58 + ,68948 + ,4 + ,35838 + ,36663 + ,45 + ,43 + ,93125 + ,1 + ,50838 + ,55369 + ,37 + ,36 + ,277108 + ,2 + ,86997 + ,77921 + ,64 + ,64 + ,78800 + ,2 + ,33032 + ,56968 + ,21 + ,21 + ,157250 + ,0 + ,61704 + ,77519 + ,104 + ,104 + ,210554 + ,6 + ,117986 + ,129805 + ,126 + ,124 + ,127324 + ,3 + ,56733 + ,72761 + ,104 + ,101 + ,114397 + ,0 + ,55064 + ,81278 + ,87 + ,85 + ,24188 + ,0 + ,5950 + ,15049 + ,7 + ,7 + ,246209 + ,6 + ,84607 + ,113935 + ,130 + ,124 + ,65029 + ,5 + ,32551 + ,25109 + ,21 + ,21 + ,98030 + ,3 + ,31701 + ,45824 + ,35 + ,35 + ,173587 + ,1 + ,71170 + ,89644 + ,97 + ,95 + ,172684 + ,5 + ,101773 + ,109011 + ,103 + ,102 + ,191381 + ,5 + ,101653 + ,134245 + ,210 + ,212 + ,191276 + ,0 + ,81493 + ,136692 + ,151 + ,141 + ,134043 + ,9 + ,55901 + ,50741 + ,57 + ,54 + ,233406 + ,6 + ,109104 + ,149510 + ,117 + ,117 + ,195304 + ,6 + ,114425 + ,147888 + ,152 + ,145 + ,127619 + ,5 + ,36311 + ,54987 + ,52 + ,50 + ,162810 + ,6 + ,70027 + ,74467 + ,83 + ,80 + ,129100 + ,2 + ,73713 + ,100033 + ,87 + ,87 + ,108715 + ,0 + ,40671 + ,85505 + ,80 + ,78 + ,106469 + ,3 + ,89041 + ,62426 + ,88 + ,86 + ,142069 + ,8 + ,57231 + ,82932 + ,83 + ,82 + ,143937 + ,2 + ,78792 + ,79169 + ,140 + ,139 + ,84256 + ,5 + ,59155 + ,65469 + ,76 + ,75 + ,118807 + ,11 + ,55827 + ,63572 + ,70 + ,70 + ,69471 + ,6 + ,22618 + ,23824 + ,26 + ,25 + ,122433 + ,5 + ,58425 + ,73831 + ,66 + ,66 + ,131122 + ,1 + ,65724 + ,63551 + ,89 + ,89 + ,94763 + ,0 + ,56979 + ,56756 + ,100 + ,99 + ,188780 + ,3 + ,72369 + ,81399 + ,98 + ,98 + ,191467 + ,3 + ,79194 + ,117881 + ,109 + ,104 + ,105615 + ,6 + ,202316 + ,70711 + ,51 + ,48 + ,89318 + ,1 + ,44970 + ,50495 + ,82 + ,81 + ,107335 + ,0 + ,49319 + ,53845 + ,65 + ,64 + ,98599 + ,1 + ,36252 + ,51390 + ,46 + ,44 + ,260646 + ,0 + ,75741 + ,104953 + ,104 + ,104 + ,131876 + ,5 + ,38417 + ,65983 + ,36 + ,36 + ,119291 + ,2 + ,64102 + ,76839 + ,123 + ,120 + ,80953 + ,0 + ,56622 + ,55792 + ,59 + ,58 + ,99768 + ,0 + ,15430 + ,25155 + ,27 + ,27 + ,84572 + ,5 + ,72571 + ,55291 + ,84 + ,84 + ,202373 + ,1 + ,67271 + ,84279 + ,61 + ,56 + ,166790 + ,0 + ,43460 + ,99692 + ,46 + ,46 + ,99946 + ,1 + ,99501 + ,59633 + ,125 + ,119 + ,116900 + ,1 + ,28340 + ,63249 + ,58 + ,57 + ,142146 + ,2 + ,76013 + ,82928 + ,152 + ,139 + ,99246 + ,4 + ,37361 + ,50000 + ,52 + ,51 + ,156833 + ,1 + ,48204 + ,69455 + ,85 + ,85 + ,175078 + ,4 + ,76168 + ,84068 + ,95 + ,91 + ,130533 + ,0 + ,85168 + ,76195 + ,78 + ,79 + ,142339 + ,2 + ,125410 + ,114634 + ,144 + ,142 + ,176789 + ,0 + ,123328 + ,139357 + ,149 + ,149 + ,181379 + ,7 + ,83038 + ,110044 + ,101 + ,96 + ,228548 + ,7 + ,120087 + ,155118 + ,205 + ,198 + ,142141 + ,6 + ,91939 + ,83061 + ,61 + ,61 + ,167845 + ,0 + ,103646 + ,127122 + ,145 + ,145 + ,103012 + ,0 + ,29467 + ,45653 + ,28 + ,26 + ,43287 + ,4 + ,43750 + ,19630 + ,49 + ,49 + ,125366 + ,4 + ,34497 + ,67229 + ,68 + ,68 + ,118372 + ,0 + ,66477 + ,86060 + ,142 + ,145 + ,135171 + ,0 + ,71181 + ,88003 + ,82 + ,82 + ,175568 + ,0 + ,74482 + ,95815 + ,105 + ,102 + ,74112 + ,0 + ,174949 + ,85499 + ,52 + ,52 + ,88817 + ,0 + ,46765 + ,27220 + ,56 + ,56 + ,164767 + ,4 + ,90257 + ,109882 + ,81 + ,80 + ,141933 + ,0 + ,51370 + ,72579 + ,100 + ,99 + ,22938 + ,0 + ,1168 + ,5841 + ,11 + ,11 + ,115199 + ,0 + ,51360 + ,68369 + ,87 + ,87 + ,61857 + ,4 + ,25162 + ,24610 + ,31 + ,28 + ,91185 + ,0 + ,21067 + ,30995 + ,67 + ,67 + ,213765 + ,1 + ,58233 + ,150662 + ,150 + ,150 + ,21054 + ,0 + ,855 + ,6622 + ,4 + ,4 + ,167105 + ,5 + ,85903 + ,93694 + ,75 + ,71 + ,31414 + ,0 + ,14116 + ,13155 + ,39 + ,39 + ,178863 + ,1 + ,57637 + ,111908 + ,88 + ,87 + ,126681 + ,7 + ,94137 + ,57550 + ,67 + ,66 + ,64320 + ,5 + ,62147 + ,16356 + ,24 + ,23 + ,67746 + ,2 + ,62832 + ,40174 + ,58 + ,56 + ,38214 + ,0 + ,8773 + ,13983 + ,16 + ,16 + ,90961 + ,1 + ,63785 + ,52316 + ,49 + ,49 + ,181510 + ,0 + ,65196 + ,99585 + ,109 + ,108 + ,116775 + ,0 + ,73087 + ,86271 + ,124 + ,112 + ,223914 + ,2 + ,72631 + ,131012 + ,115 + ,110 + ,185139 + ,0 + ,86281 + ,130274 + ,128 + ,126 + ,242879 + ,2 + ,162365 + ,159051 + ,159 + ,155 + ,139144 + ,0 + ,56530 + ,76506 + ,75 + ,75 + ,75812 + ,0 + ,35606 + ,49145 + ,30 + ,30 + ,178218 + ,4 + ,70111 + ,66398 + ,83 + ,78 + ,246834 + ,4 + ,92046 + ,127546 + ,135 + ,135 + ,50999 + ,8 + ,63989 + ,6802 + ,8 + ,8 + ,223842 + ,0 + ,104911 + ,99509 + ,115 + ,114 + ,93577 + ,4 + ,43448 + ,43106 + ,60 + ,60 + ,155383 + ,0 + ,60029 + ,108303 + ,99 + ,99 + ,111664 + ,1 + ,38650 + ,64167 + ,98 + ,98 + ,75426 + ,0 + ,47261 + ,8579 + ,36 + ,33 + ,243551 + ,9 + ,73586 + ,97811 + ,93 + ,93 + ,136548 + ,0 + ,83042 + ,84365 + ,158 + ,157 + ,173260 + ,3 + ,37238 + ,10901 + ,16 + ,15 + ,185039 + ,7 + ,63958 + ,91346 + ,100 + ,98 + ,67507 + ,5 + ,78956 + ,33660 + ,49 + ,49 + ,139350 + ,2 + ,99518 + ,93634 + ,89 + ,88 + ,172964 + ,1 + ,111436 + ,109348 + ,153 + ,151 + ,0 + ,9 + ,0 + ,0 + ,0 + ,0 + ,14688 + ,0 + ,6023 + ,7953 + ,5 + ,5 + ,98 + ,0 + ,0 + ,0 + ,0 + ,0 + ,455 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,128066 + ,2 + ,42564 + ,63538 + ,80 + ,80 + ,176460 + ,1 + ,38885 + ,108281 + ,122 + ,122 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,203 + ,0 + ,0 + ,0 + ,0 + ,0 + ,7199 + ,0 + ,1644 + ,4245 + ,6 + ,6 + ,46660 + ,0 + ,6179 + ,21509 + ,13 + ,13 + ,17547 + ,0 + ,3926 + ,7670 + ,3 + ,3 + ,73567 + ,0 + ,23238 + ,10641 + ,18 + ,18 + ,969 + ,0 + ,0 + ,0 + ,0 + ,0 + ,101060 + ,2 + ,49288 + ,41243 + ,49 + ,48) + ,dim=c(6 + ,164) + ,dimnames=list(c('TotalTime' + ,'Shared' + ,'Caracters' + ,'Writing' + ,'Hyperlink' + ,'Blogs') + ,1:164)) > y <- array(NA,dim=c(6,164),dimnames=list(c('TotalTime','Shared','Caracters','Writing','Hyperlink','Blogs'),1:164)) > 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 = '1' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Prof. Dr. P. Wessa > #To cite this work: AUTHOR(S), (YEAR), 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: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > 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 TotalTime Shared Caracters Writing Hyperlink Blogs 1 146455 1 95556 114468 127 128 2 84944 4 54565 88594 90 89 3 113337 9 63016 74151 68 68 4 128655 2 79774 77921 111 108 5 74398 1 31258 53212 51 51 6 35523 2 52491 34956 33 33 7 293403 0 91256 149703 123 119 8 32750 0 22807 6853 5 5 9 106539 5 77411 58907 63 63 10 130539 0 48821 67067 66 66 11 154991 0 52295 110563 99 98 12 126683 7 63262 58126 72 71 13 100672 6 50466 57113 55 55 14 179562 3 62932 77993 116 116 15 125971 4 38439 68091 71 71 16 234509 0 70817 124676 125 120 17 158980 4 105965 109522 123 122 18 184217 3 73795 75865 74 74 19 107342 0 82043 79746 116 111 20 141371 5 74349 77844 117 103 21 154730 0 82204 98681 98 98 22 264020 1 55709 105531 101 100 23 90938 3 37137 51428 43 42 24 101324 5 70780 65703 103 100 25 130232 0 55027 72562 107 105 26 137793 0 56699 81728 77 77 27 161678 4 65911 95580 87 83 28 151503 0 56316 98278 99 98 29 105324 0 26982 46629 46 46 30 175914 0 54628 115189 96 95 31 181853 3 96750 124865 92 91 32 114928 4 53009 59392 96 91 33 190410 1 64664 127818 96 94 34 61499 4 36990 17821 15 15 35 223004 1 85224 154076 147 137 36 167131 0 37048 64881 56 56 37 233482 0 59635 136506 81 78 38 121185 2 42051 66524 69 68 39 78776 1 26998 45988 34 34 40 188967 2 63717 107445 98 94 41 199512 8 55071 102772 82 82 42 102531 5 40001 46657 64 63 43 118958 3 54506 97563 61 58 44 68948 4 35838 36663 45 43 45 93125 1 50838 55369 37 36 46 277108 2 86997 77921 64 64 47 78800 2 33032 56968 21 21 48 157250 0 61704 77519 104 104 49 210554 6 117986 129805 126 124 50 127324 3 56733 72761 104 101 51 114397 0 55064 81278 87 85 52 24188 0 5950 15049 7 7 53 246209 6 84607 113935 130 124 54 65029 5 32551 25109 21 21 55 98030 3 31701 45824 35 35 56 173587 1 71170 89644 97 95 57 172684 5 101773 109011 103 102 58 191381 5 101653 134245 210 212 59 191276 0 81493 136692 151 141 60 134043 9 55901 50741 57 54 61 233406 6 109104 149510 117 117 62 195304 6 114425 147888 152 145 63 127619 5 36311 54987 52 50 64 162810 6 70027 74467 83 80 65 129100 2 73713 100033 87 87 66 108715 0 40671 85505 80 78 67 106469 3 89041 62426 88 86 68 142069 8 57231 82932 83 82 69 143937 2 78792 79169 140 139 70 84256 5 59155 65469 76 75 71 118807 11 55827 63572 70 70 72 69471 6 22618 23824 26 25 73 122433 5 58425 73831 66 66 74 131122 1 65724 63551 89 89 75 94763 0 56979 56756 100 99 76 188780 3 72369 81399 98 98 77 191467 3 79194 117881 109 104 78 105615 6 202316 70711 51 48 79 89318 1 44970 50495 82 81 80 107335 0 49319 53845 65 64 81 98599 1 36252 51390 46 44 82 260646 0 75741 104953 104 104 83 131876 5 38417 65983 36 36 84 119291 2 64102 76839 123 120 85 80953 0 56622 55792 59 58 86 99768 0 15430 25155 27 27 87 84572 5 72571 55291 84 84 88 202373 1 67271 84279 61 56 89 166790 0 43460 99692 46 46 90 99946 1 99501 59633 125 119 91 116900 1 28340 63249 58 57 92 142146 2 76013 82928 152 139 93 99246 4 37361 50000 52 51 94 156833 1 48204 69455 85 85 95 175078 4 76168 84068 95 91 96 130533 0 85168 76195 78 79 97 142339 2 125410 114634 144 142 98 176789 0 123328 139357 149 149 99 181379 7 83038 110044 101 96 100 228548 7 120087 155118 205 198 101 142141 6 91939 83061 61 61 102 167845 0 103646 127122 145 145 103 103012 0 29467 45653 28 26 104 43287 4 43750 19630 49 49 105 125366 4 34497 67229 68 68 106 118372 0 66477 86060 142 145 107 135171 0 71181 88003 82 82 108 175568 0 74482 95815 105 102 109 74112 0 174949 85499 52 52 110 88817 0 46765 27220 56 56 111 164767 4 90257 109882 81 80 112 141933 0 51370 72579 100 99 113 22938 0 1168 5841 11 11 114 115199 0 51360 68369 87 87 115 61857 4 25162 24610 31 28 116 91185 0 21067 30995 67 67 117 213765 1 58233 150662 150 150 118 21054 0 855 6622 4 4 119 167105 5 85903 93694 75 71 120 31414 0 14116 13155 39 39 121 178863 1 57637 111908 88 87 122 126681 7 94137 57550 67 66 123 64320 5 62147 16356 24 23 124 67746 2 62832 40174 58 56 125 38214 0 8773 13983 16 16 126 90961 1 63785 52316 49 49 127 181510 0 65196 99585 109 108 128 116775 0 73087 86271 124 112 129 223914 2 72631 131012 115 110 130 185139 0 86281 130274 128 126 131 242879 2 162365 159051 159 155 132 139144 0 56530 76506 75 75 133 75812 0 35606 49145 30 30 134 178218 4 70111 66398 83 78 135 246834 4 92046 127546 135 135 136 50999 8 63989 6802 8 8 137 223842 0 104911 99509 115 114 138 93577 4 43448 43106 60 60 139 155383 0 60029 108303 99 99 140 111664 1 38650 64167 98 98 141 75426 0 47261 8579 36 33 142 243551 9 73586 97811 93 93 143 136548 0 83042 84365 158 157 144 173260 3 37238 10901 16 15 145 185039 7 63958 91346 100 98 146 67507 5 78956 33660 49 49 147 139350 2 99518 93634 89 88 148 172964 1 111436 109348 153 151 149 0 9 0 0 0 0 150 14688 0 6023 7953 5 5 151 98 0 0 0 0 0 152 455 0 0 0 0 0 153 0 1 0 0 0 0 154 0 0 0 0 0 0 155 128066 2 42564 63538 80 80 156 176460 1 38885 108281 122 122 157 0 0 0 0 0 0 158 203 0 0 0 0 0 159 7199 0 1644 4245 6 6 160 46660 0 6179 21509 13 13 161 17547 0 3926 7670 3 3 162 73567 0 23238 10641 18 18 163 969 0 0 0 0 0 164 101060 2 49288 41243 49 48 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Shared Caracters Writing Hyperlink Blogs 2.454e+04 1.893e+03 -8.151e-02 1.442e+00 1.979e+02 -1.989e+02 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -70627 -20432 -4341 11637 143536 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 2.454e+04 5.501e+03 4.462 1.54e-05 *** Shared 1.893e+03 9.705e+02 1.951 0.0528 . Caracters -8.151e-02 1.121e-01 -0.727 0.4683 Writing 1.442e+00 1.273e-01 11.335 < 2e-16 *** Hyperlink 1.979e+02 1.037e+03 0.191 0.8488 Blogs -1.989e+02 1.058e+03 -0.188 0.8511 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 30920 on 158 degrees of freedom Multiple R-squared: 0.7734, Adjusted R-squared: 0.7662 F-statistic: 107.9 on 5 and 158 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,] 0.58760707 8.247859e-01 4.123929e-01 [2,] 0.61210237 7.757953e-01 3.878976e-01 [3,] 0.48227045 9.645409e-01 5.177296e-01 [4,] 0.57374991 8.525002e-01 4.262501e-01 [5,] 0.47857713 9.571543e-01 5.214229e-01 [6,] 0.84247297 3.150541e-01 1.575270e-01 [7,] 0.79796662 4.040668e-01 2.020334e-01 [8,] 0.73426017 5.314797e-01 2.657398e-01 [9,] 0.68111194 6.377761e-01 3.188881e-01 [10,] 0.84578691 3.084262e-01 1.542131e-01 [11,] 0.88165091 2.366982e-01 1.183491e-01 [12,] 0.84484179 3.103164e-01 1.551582e-01 [13,] 0.79791833 4.041633e-01 2.020817e-01 [14,] 0.95828163 8.343674e-02 4.171837e-02 [15,] 0.94129173 1.174165e-01 5.870827e-02 [16,] 0.92150403 1.569919e-01 7.849597e-02 [17,] 0.89442241 2.111552e-01 1.055776e-01 [18,] 0.86189273 2.762145e-01 1.381073e-01 [19,] 0.82545343 3.490931e-01 1.745466e-01 [20,] 0.79859863 4.028027e-01 2.014014e-01 [21,] 0.76304964 4.739007e-01 2.369504e-01 [22,] 0.74426551 5.114690e-01 2.557345e-01 [23,] 0.71456739 5.708652e-01 2.854326e-01 [24,] 0.66124195 6.775161e-01 3.387581e-01 [25,] 0.63537042 7.292592e-01 3.646296e-01 [26,] 0.60068390 7.986322e-01 3.993161e-01 [27,] 0.58823027 8.235395e-01 4.117697e-01 [28,] 0.65788611 6.842278e-01 3.421139e-01 [29,] 0.61177463 7.764507e-01 3.882254e-01 [30,] 0.55671361 8.865728e-01 4.432864e-01 [31,] 0.51430879 9.713824e-01 4.856912e-01 [32,] 0.46343736 9.268747e-01 5.365626e-01 [33,] 0.43423321 8.684664e-01 5.657668e-01 [34,] 0.38344158 7.668832e-01 6.165584e-01 [35,] 0.44623280 8.924656e-01 5.537672e-01 [36,] 0.39913960 7.982792e-01 6.008604e-01 [37,] 0.34955082 6.991016e-01 6.504492e-01 [38,] 0.98155544 3.688912e-02 1.844456e-02 [39,] 0.98022023 3.955954e-02 1.977977e-02 [40,] 0.97676555 4.646889e-02 2.323445e-02 [41,] 0.96941075 6.117849e-02 3.058925e-02 [42,] 0.95987662 8.024676e-02 4.012338e-02 [43,] 0.95604043 8.791914e-02 4.395957e-02 [44,] 0.94799876 1.040025e-01 5.200124e-02 [45,] 0.96760154 6.479692e-02 3.239846e-02 [46,] 0.95818821 8.362358e-02 4.181179e-02 [47,] 0.94707035 1.058593e-01 5.292965e-02 [48,] 0.93901558 1.219688e-01 6.098442e-02 [49,] 0.92716957 1.456609e-01 7.283043e-02 [50,] 0.92391499 1.521700e-01 7.608501e-02 [51,] 0.91843929 1.631214e-01 8.156071e-02 [52,] 0.91374406 1.725119e-01 8.625594e-02 [53,] 0.89690799 2.061840e-01 1.030920e-01 [54,] 0.91835577 1.632885e-01 8.164423e-02 [55,] 0.90675989 1.864802e-01 9.324011e-02 [56,] 0.89911708 2.017658e-01 1.008829e-01 [57,] 0.90882028 1.823594e-01 9.117972e-02 [58,] 0.91338229 1.732354e-01 8.661771e-02 [59,] 0.89594326 2.081135e-01 1.040567e-01 [60,] 0.87695935 2.460813e-01 1.230407e-01 [61,] 0.85323779 2.935244e-01 1.467622e-01 [62,] 0.86786548 2.642690e-01 1.321345e-01 [63,] 0.84938596 3.012281e-01 1.506140e-01 [64,] 0.82205028 3.558994e-01 1.779497e-01 [65,] 0.79778534 4.044293e-01 2.022147e-01 [66,] 0.77403933 4.519213e-01 2.259607e-01 [67,] 0.74013880 5.197224e-01 2.598612e-01 [68,] 0.78052298 4.389540e-01 2.194770e-01 [69,] 0.74626818 5.074636e-01 2.537318e-01 [70,] 0.72986764 5.402647e-01 2.701324e-01 [71,] 0.69252301 6.149540e-01 3.074770e-01 [72,] 0.65417949 6.916410e-01 3.458205e-01 [73,] 0.61075505 7.784899e-01 3.892449e-01 [74,] 0.87192782 2.561444e-01 1.280722e-01 [75,] 0.84720514 3.055897e-01 1.527949e-01 [76,] 0.82633925 3.473215e-01 1.736608e-01 [77,] 0.80841855 3.831629e-01 1.915815e-01 [78,] 0.82962654 3.407469e-01 1.703735e-01 [79,] 0.82000822 3.599836e-01 1.799918e-01 [80,] 0.89265986 2.146803e-01 1.073401e-01 [81,] 0.87393635 2.521273e-01 1.260636e-01 [82,] 0.85051037 2.989793e-01 1.494896e-01 [83,] 0.82252512 3.549498e-01 1.774749e-01 [84,] 0.79556544 4.088691e-01 2.044346e-01 [85,] 0.76158989 4.768202e-01 2.384101e-01 [86,] 0.77060853 4.587829e-01 2.293915e-01 [87,] 0.75887666 4.822467e-01 2.411233e-01 [88,] 0.72517775 5.496445e-01 2.748223e-01 [89,] 0.76182085 4.763583e-01 2.381792e-01 [90,] 0.77533098 4.493380e-01 2.246690e-01 [91,] 0.74642452 5.071510e-01 2.535755e-01 [92,] 0.78787455 4.242509e-01 2.121255e-01 [93,] 0.75446552 4.910690e-01 2.455345e-01 [94,] 0.75591905 4.881619e-01 2.440810e-01 [95,] 0.73850500 5.229900e-01 2.614950e-01 [96,] 0.72286947 5.542611e-01 2.771305e-01 [97,] 0.68175874 6.364825e-01 3.182413e-01 [98,] 0.69788622 6.042276e-01 3.021138e-01 [99,] 0.65694576 6.861085e-01 3.430542e-01 [100,] 0.62903224 7.419355e-01 3.709678e-01 [101,] 0.75163503 4.967299e-01 2.483650e-01 [102,] 0.73422261 5.315548e-01 2.657774e-01 [103,] 0.71622027 5.675595e-01 2.837797e-01 [104,] 0.68366362 6.326728e-01 3.163364e-01 [105,] 0.64406243 7.118751e-01 3.559376e-01 [106,] 0.59686925 8.062615e-01 4.031307e-01 [107,] 0.54821886 9.035623e-01 4.517811e-01 [108,] 0.53290859 9.341828e-01 4.670914e-01 [109,] 0.50557494 9.888501e-01 4.944251e-01 [110,] 0.46232250 9.246450e-01 5.376775e-01 [111,] 0.41494971 8.298994e-01 5.850503e-01 [112,] 0.36924189 7.384838e-01 6.307581e-01 [113,] 0.32084457 6.416891e-01 6.791554e-01 [114,] 0.29123856 5.824771e-01 7.087614e-01 [115,] 0.25131268 5.026254e-01 7.486873e-01 [116,] 0.23126347 4.625269e-01 7.687365e-01 [117,] 0.19439036 3.887807e-01 8.056096e-01 [118,] 0.16418087 3.283617e-01 8.358191e-01 [119,] 0.14352878 2.870576e-01 8.564712e-01 [120,] 0.17263725 3.452745e-01 8.273628e-01 [121,] 0.14039874 2.807975e-01 8.596013e-01 [122,] 0.12972019 2.594404e-01 8.702798e-01 [123,] 0.21609895 4.321979e-01 7.839011e-01 [124,] 0.17703743 3.540749e-01 8.229626e-01 [125,] 0.15196863 3.039373e-01 8.480314e-01 [126,] 0.14416095 2.883219e-01 8.558390e-01 [127,] 0.13844886 2.768977e-01 8.615511e-01 [128,] 0.11727889 2.345578e-01 8.827211e-01 [129,] 0.15948218 3.189644e-01 8.405178e-01 [130,] 0.12305519 2.461104e-01 8.769448e-01 [131,] 0.09732996 1.946599e-01 9.026700e-01 [132,] 0.07437717 1.487543e-01 9.256228e-01 [133,] 0.05857503 1.171501e-01 9.414250e-01 [134,] 0.13578921 2.715784e-01 8.642108e-01 [135,] 0.10276765 2.055353e-01 8.972324e-01 [136,] 0.98367073 3.265853e-02 1.632927e-02 [137,] 0.99090199 1.819602e-02 9.098010e-03 [138,] 0.99147321 1.705358e-02 8.526788e-03 [139,] 0.99997028 5.943623e-05 2.971811e-05 [140,] 0.99998876 2.248771e-05 1.124386e-05 [141,] 0.99999252 1.495965e-05 7.479827e-06 [142,] 0.99999471 1.058476e-05 5.292380e-06 [143,] 0.99996850 6.299007e-05 3.149504e-05 [144,] 0.99981959 3.608251e-04 1.804125e-04 [145,] 0.99999068 1.864032e-05 9.320161e-06 [146,] 0.99987729 2.454272e-04 1.227136e-04 [147,] 0.99937018 1.259645e-03 6.298226e-04 > postscript(file="/var/wessaorg/rcomp/tmp/1p0si1321541513.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2p42e1321541513.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/3wj5j1321541513.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/40iwh1321541513.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5yvkz1321541513.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 = 164 Frequency = 1 1 2 3 4 5 6 -36981.82969 -70627.21007 -30002.35686 -6055.78394 -26195.64210 -38917.77386 7 8 9 10 11 12 59685.56871 185.94015 -6069.20370 13300.19294 -24871.75090 10071.16315 13 14 15 16 17 18 -13446.31477 42082.71315 -1160.06435 35029.03561 -22556.15737 50650.75553 19 20 21 22 23 24 -26422.16536 -1533.23439 -5357.52711 89802.52379 -10596.91669 -22184.37431 25 26 27 28 29 30 5215.96320 59.46288 -3645.06573 -10311.36258 15765.98766 -10434.39672 31 32 33 34 35 36 -20703.50375 563.07058 -15429.51351 6706.26807 -20575.86543 52075.73825 37 38 39 40 41 42 16380.03305 194.74951 -11761.56643 10148.25482 16147.84411 4345.57126 43 44 45 46 47 48 -48088.76737 -13485.25747 -9196.87306 143535.68589 -28990.39118 26022.75923 49 50 51 52 53 54 -3242.52836 -3722.34253 -23208.50231 -21570.55058 51791.84111 -2525.69495 55 56 57 58 59 60 4326.41244 23343.27970 -10370.24527 -27378.35029 -25634.80124 23283.95406 61 62 63 64 65 66 -9149.41449 -45835.29120 16906.19295 24685.05187 -37427.82139 -36168.01931 67 68 69 70 71 72 -6853.05224 -12698.58085 7772.77894 -39491.65126 -13643.53023 872.81027 73 74 75 76 77 78 -13247.10815 18462.25048 -7102.50350 47138.94595 -3225.02589 -16340.59556 79 80 81 82 83 84 -6406.64664 9009.09180 637.80582 90990.53733 5855.37005 -15124.53707 85 86 87 88 89 90 -19592.07734 40224.71090 -23193.79729 58917.55205 2033.94115 -5466.26227 91 92 93 94 95 96 1398.63200 -2041.73624 -2095.29767 34224.83278 27204.62671 3301.12882 97 98 99 100 101 102 -41376.91018 -38568.81157 -9277.02263 -24399.20816 -6019.60787 -31472.68582 103 104 105 106 107 108 14648.59324 -13530.09975 -845.99466 -24151.52145 -10428.47811 18395.41275 109 110 111 112 113 114 -59446.96118 28878.29268 -18610.87777 16786.24040 -9924.18306 -3689.92204 115 116 117 118 119 120 -4273.43895 23717.24754 -25098.48202 -12967.25895 4226.57706 -10914.88061 121 122 123 124 125 126 -4408.88356 13411.78089 11607.76170 -13751.38132 -5767.77195 -5690.77489 127 128 129 130 131 132 18544.19268 -28515.54784 11645.52926 -20555.61772 -2277.07150 8927.21166 133 134 135 136 137 138 -16688.26144 55128.25767 38375.24645 6720.64763 64229.17024 2883.09832 139 140 141 142 143 144 -20390.45991 -4082.22846 41799.91914 66969.65619 -2959.85581 130164.88076 145 146 147 148 149 150 20394.48804 -8571.48326 -16040.93679 -2363.67727 -41584.24952 -20830.90566 151 152 153 154 155 156 -24444.98567 -24087.98567 -26436.45943 -24542.98567 11634.65098 -2875.74055 157 158 159 160 161 162 -24542.98567 -24339.98567 -23327.21687 -8392.17326 -17736.62574 35587.03667 163 164 -23573.98567 17106.49372 > postscript(file="/var/wessaorg/rcomp/tmp/6h7d91321541513.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 = 164 Frequency = 1 lag(myerror, k = 1) myerror 0 -36981.82969 NA 1 -70627.21007 -36981.82969 2 -30002.35686 -70627.21007 3 -6055.78394 -30002.35686 4 -26195.64210 -6055.78394 5 -38917.77386 -26195.64210 6 59685.56871 -38917.77386 7 185.94015 59685.56871 8 -6069.20370 185.94015 9 13300.19294 -6069.20370 10 -24871.75090 13300.19294 11 10071.16315 -24871.75090 12 -13446.31477 10071.16315 13 42082.71315 -13446.31477 14 -1160.06435 42082.71315 15 35029.03561 -1160.06435 16 -22556.15737 35029.03561 17 50650.75553 -22556.15737 18 -26422.16536 50650.75553 19 -1533.23439 -26422.16536 20 -5357.52711 -1533.23439 21 89802.52379 -5357.52711 22 -10596.91669 89802.52379 23 -22184.37431 -10596.91669 24 5215.96320 -22184.37431 25 59.46288 5215.96320 26 -3645.06573 59.46288 27 -10311.36258 -3645.06573 28 15765.98766 -10311.36258 29 -10434.39672 15765.98766 30 -20703.50375 -10434.39672 31 563.07058 -20703.50375 32 -15429.51351 563.07058 33 6706.26807 -15429.51351 34 -20575.86543 6706.26807 35 52075.73825 -20575.86543 36 16380.03305 52075.73825 37 194.74951 16380.03305 38 -11761.56643 194.74951 39 10148.25482 -11761.56643 40 16147.84411 10148.25482 41 4345.57126 16147.84411 42 -48088.76737 4345.57126 43 -13485.25747 -48088.76737 44 -9196.87306 -13485.25747 45 143535.68589 -9196.87306 46 -28990.39118 143535.68589 47 26022.75923 -28990.39118 48 -3242.52836 26022.75923 49 -3722.34253 -3242.52836 50 -23208.50231 -3722.34253 51 -21570.55058 -23208.50231 52 51791.84111 -21570.55058 53 -2525.69495 51791.84111 54 4326.41244 -2525.69495 55 23343.27970 4326.41244 56 -10370.24527 23343.27970 57 -27378.35029 -10370.24527 58 -25634.80124 -27378.35029 59 23283.95406 -25634.80124 60 -9149.41449 23283.95406 61 -45835.29120 -9149.41449 62 16906.19295 -45835.29120 63 24685.05187 16906.19295 64 -37427.82139 24685.05187 65 -36168.01931 -37427.82139 66 -6853.05224 -36168.01931 67 -12698.58085 -6853.05224 68 7772.77894 -12698.58085 69 -39491.65126 7772.77894 70 -13643.53023 -39491.65126 71 872.81027 -13643.53023 72 -13247.10815 872.81027 73 18462.25048 -13247.10815 74 -7102.50350 18462.25048 75 47138.94595 -7102.50350 76 -3225.02589 47138.94595 77 -16340.59556 -3225.02589 78 -6406.64664 -16340.59556 79 9009.09180 -6406.64664 80 637.80582 9009.09180 81 90990.53733 637.80582 82 5855.37005 90990.53733 83 -15124.53707 5855.37005 84 -19592.07734 -15124.53707 85 40224.71090 -19592.07734 86 -23193.79729 40224.71090 87 58917.55205 -23193.79729 88 2033.94115 58917.55205 89 -5466.26227 2033.94115 90 1398.63200 -5466.26227 91 -2041.73624 1398.63200 92 -2095.29767 -2041.73624 93 34224.83278 -2095.29767 94 27204.62671 34224.83278 95 3301.12882 27204.62671 96 -41376.91018 3301.12882 97 -38568.81157 -41376.91018 98 -9277.02263 -38568.81157 99 -24399.20816 -9277.02263 100 -6019.60787 -24399.20816 101 -31472.68582 -6019.60787 102 14648.59324 -31472.68582 103 -13530.09975 14648.59324 104 -845.99466 -13530.09975 105 -24151.52145 -845.99466 106 -10428.47811 -24151.52145 107 18395.41275 -10428.47811 108 -59446.96118 18395.41275 109 28878.29268 -59446.96118 110 -18610.87777 28878.29268 111 16786.24040 -18610.87777 112 -9924.18306 16786.24040 113 -3689.92204 -9924.18306 114 -4273.43895 -3689.92204 115 23717.24754 -4273.43895 116 -25098.48202 23717.24754 117 -12967.25895 -25098.48202 118 4226.57706 -12967.25895 119 -10914.88061 4226.57706 120 -4408.88356 -10914.88061 121 13411.78089 -4408.88356 122 11607.76170 13411.78089 123 -13751.38132 11607.76170 124 -5767.77195 -13751.38132 125 -5690.77489 -5767.77195 126 18544.19268 -5690.77489 127 -28515.54784 18544.19268 128 11645.52926 -28515.54784 129 -20555.61772 11645.52926 130 -2277.07150 -20555.61772 131 8927.21166 -2277.07150 132 -16688.26144 8927.21166 133 55128.25767 -16688.26144 134 38375.24645 55128.25767 135 6720.64763 38375.24645 136 64229.17024 6720.64763 137 2883.09832 64229.17024 138 -20390.45991 2883.09832 139 -4082.22846 -20390.45991 140 41799.91914 -4082.22846 141 66969.65619 41799.91914 142 -2959.85581 66969.65619 143 130164.88076 -2959.85581 144 20394.48804 130164.88076 145 -8571.48326 20394.48804 146 -16040.93679 -8571.48326 147 -2363.67727 -16040.93679 148 -41584.24952 -2363.67727 149 -20830.90566 -41584.24952 150 -24444.98567 -20830.90566 151 -24087.98567 -24444.98567 152 -26436.45943 -24087.98567 153 -24542.98567 -26436.45943 154 11634.65098 -24542.98567 155 -2875.74055 11634.65098 156 -24542.98567 -2875.74055 157 -24339.98567 -24542.98567 158 -23327.21687 -24339.98567 159 -8392.17326 -23327.21687 160 -17736.62574 -8392.17326 161 35587.03667 -17736.62574 162 -23573.98567 35587.03667 163 17106.49372 -23573.98567 164 NA 17106.49372 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -70627.21007 -36981.82969 [2,] -30002.35686 -70627.21007 [3,] -6055.78394 -30002.35686 [4,] -26195.64210 -6055.78394 [5,] -38917.77386 -26195.64210 [6,] 59685.56871 -38917.77386 [7,] 185.94015 59685.56871 [8,] -6069.20370 185.94015 [9,] 13300.19294 -6069.20370 [10,] -24871.75090 13300.19294 [11,] 10071.16315 -24871.75090 [12,] -13446.31477 10071.16315 [13,] 42082.71315 -13446.31477 [14,] -1160.06435 42082.71315 [15,] 35029.03561 -1160.06435 [16,] -22556.15737 35029.03561 [17,] 50650.75553 -22556.15737 [18,] -26422.16536 50650.75553 [19,] -1533.23439 -26422.16536 [20,] -5357.52711 -1533.23439 [21,] 89802.52379 -5357.52711 [22,] -10596.91669 89802.52379 [23,] -22184.37431 -10596.91669 [24,] 5215.96320 -22184.37431 [25,] 59.46288 5215.96320 [26,] -3645.06573 59.46288 [27,] -10311.36258 -3645.06573 [28,] 15765.98766 -10311.36258 [29,] -10434.39672 15765.98766 [30,] -20703.50375 -10434.39672 [31,] 563.07058 -20703.50375 [32,] -15429.51351 563.07058 [33,] 6706.26807 -15429.51351 [34,] -20575.86543 6706.26807 [35,] 52075.73825 -20575.86543 [36,] 16380.03305 52075.73825 [37,] 194.74951 16380.03305 [38,] -11761.56643 194.74951 [39,] 10148.25482 -11761.56643 [40,] 16147.84411 10148.25482 [41,] 4345.57126 16147.84411 [42,] -48088.76737 4345.57126 [43,] -13485.25747 -48088.76737 [44,] -9196.87306 -13485.25747 [45,] 143535.68589 -9196.87306 [46,] -28990.39118 143535.68589 [47,] 26022.75923 -28990.39118 [48,] -3242.52836 26022.75923 [49,] -3722.34253 -3242.52836 [50,] -23208.50231 -3722.34253 [51,] -21570.55058 -23208.50231 [52,] 51791.84111 -21570.55058 [53,] -2525.69495 51791.84111 [54,] 4326.41244 -2525.69495 [55,] 23343.27970 4326.41244 [56,] -10370.24527 23343.27970 [57,] -27378.35029 -10370.24527 [58,] -25634.80124 -27378.35029 [59,] 23283.95406 -25634.80124 [60,] -9149.41449 23283.95406 [61,] -45835.29120 -9149.41449 [62,] 16906.19295 -45835.29120 [63,] 24685.05187 16906.19295 [64,] -37427.82139 24685.05187 [65,] -36168.01931 -37427.82139 [66,] -6853.05224 -36168.01931 [67,] -12698.58085 -6853.05224 [68,] 7772.77894 -12698.58085 [69,] -39491.65126 7772.77894 [70,] -13643.53023 -39491.65126 [71,] 872.81027 -13643.53023 [72,] -13247.10815 872.81027 [73,] 18462.25048 -13247.10815 [74,] -7102.50350 18462.25048 [75,] 47138.94595 -7102.50350 [76,] -3225.02589 47138.94595 [77,] -16340.59556 -3225.02589 [78,] -6406.64664 -16340.59556 [79,] 9009.09180 -6406.64664 [80,] 637.80582 9009.09180 [81,] 90990.53733 637.80582 [82,] 5855.37005 90990.53733 [83,] -15124.53707 5855.37005 [84,] -19592.07734 -15124.53707 [85,] 40224.71090 -19592.07734 [86,] -23193.79729 40224.71090 [87,] 58917.55205 -23193.79729 [88,] 2033.94115 58917.55205 [89,] -5466.26227 2033.94115 [90,] 1398.63200 -5466.26227 [91,] -2041.73624 1398.63200 [92,] -2095.29767 -2041.73624 [93,] 34224.83278 -2095.29767 [94,] 27204.62671 34224.83278 [95,] 3301.12882 27204.62671 [96,] -41376.91018 3301.12882 [97,] -38568.81157 -41376.91018 [98,] -9277.02263 -38568.81157 [99,] -24399.20816 -9277.02263 [100,] -6019.60787 -24399.20816 [101,] -31472.68582 -6019.60787 [102,] 14648.59324 -31472.68582 [103,] -13530.09975 14648.59324 [104,] -845.99466 -13530.09975 [105,] -24151.52145 -845.99466 [106,] -10428.47811 -24151.52145 [107,] 18395.41275 -10428.47811 [108,] -59446.96118 18395.41275 [109,] 28878.29268 -59446.96118 [110,] -18610.87777 28878.29268 [111,] 16786.24040 -18610.87777 [112,] -9924.18306 16786.24040 [113,] -3689.92204 -9924.18306 [114,] -4273.43895 -3689.92204 [115,] 23717.24754 -4273.43895 [116,] -25098.48202 23717.24754 [117,] -12967.25895 -25098.48202 [118,] 4226.57706 -12967.25895 [119,] -10914.88061 4226.57706 [120,] -4408.88356 -10914.88061 [121,] 13411.78089 -4408.88356 [122,] 11607.76170 13411.78089 [123,] -13751.38132 11607.76170 [124,] -5767.77195 -13751.38132 [125,] -5690.77489 -5767.77195 [126,] 18544.19268 -5690.77489 [127,] -28515.54784 18544.19268 [128,] 11645.52926 -28515.54784 [129,] -20555.61772 11645.52926 [130,] -2277.07150 -20555.61772 [131,] 8927.21166 -2277.07150 [132,] -16688.26144 8927.21166 [133,] 55128.25767 -16688.26144 [134,] 38375.24645 55128.25767 [135,] 6720.64763 38375.24645 [136,] 64229.17024 6720.64763 [137,] 2883.09832 64229.17024 [138,] -20390.45991 2883.09832 [139,] -4082.22846 -20390.45991 [140,] 41799.91914 -4082.22846 [141,] 66969.65619 41799.91914 [142,] -2959.85581 66969.65619 [143,] 130164.88076 -2959.85581 [144,] 20394.48804 130164.88076 [145,] -8571.48326 20394.48804 [146,] -16040.93679 -8571.48326 [147,] -2363.67727 -16040.93679 [148,] -41584.24952 -2363.67727 [149,] -20830.90566 -41584.24952 [150,] -24444.98567 -20830.90566 [151,] -24087.98567 -24444.98567 [152,] -26436.45943 -24087.98567 [153,] -24542.98567 -26436.45943 [154,] 11634.65098 -24542.98567 [155,] -2875.74055 11634.65098 [156,] -24542.98567 -2875.74055 [157,] -24339.98567 -24542.98567 [158,] -23327.21687 -24339.98567 [159,] -8392.17326 -23327.21687 [160,] -17736.62574 -8392.17326 [161,] 35587.03667 -17736.62574 [162,] -23573.98567 35587.03667 [163,] 17106.49372 -23573.98567 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -70627.21007 -36981.82969 2 -30002.35686 -70627.21007 3 -6055.78394 -30002.35686 4 -26195.64210 -6055.78394 5 -38917.77386 -26195.64210 6 59685.56871 -38917.77386 7 185.94015 59685.56871 8 -6069.20370 185.94015 9 13300.19294 -6069.20370 10 -24871.75090 13300.19294 11 10071.16315 -24871.75090 12 -13446.31477 10071.16315 13 42082.71315 -13446.31477 14 -1160.06435 42082.71315 15 35029.03561 -1160.06435 16 -22556.15737 35029.03561 17 50650.75553 -22556.15737 18 -26422.16536 50650.75553 19 -1533.23439 -26422.16536 20 -5357.52711 -1533.23439 21 89802.52379 -5357.52711 22 -10596.91669 89802.52379 23 -22184.37431 -10596.91669 24 5215.96320 -22184.37431 25 59.46288 5215.96320 26 -3645.06573 59.46288 27 -10311.36258 -3645.06573 28 15765.98766 -10311.36258 29 -10434.39672 15765.98766 30 -20703.50375 -10434.39672 31 563.07058 -20703.50375 32 -15429.51351 563.07058 33 6706.26807 -15429.51351 34 -20575.86543 6706.26807 35 52075.73825 -20575.86543 36 16380.03305 52075.73825 37 194.74951 16380.03305 38 -11761.56643 194.74951 39 10148.25482 -11761.56643 40 16147.84411 10148.25482 41 4345.57126 16147.84411 42 -48088.76737 4345.57126 43 -13485.25747 -48088.76737 44 -9196.87306 -13485.25747 45 143535.68589 -9196.87306 46 -28990.39118 143535.68589 47 26022.75923 -28990.39118 48 -3242.52836 26022.75923 49 -3722.34253 -3242.52836 50 -23208.50231 -3722.34253 51 -21570.55058 -23208.50231 52 51791.84111 -21570.55058 53 -2525.69495 51791.84111 54 4326.41244 -2525.69495 55 23343.27970 4326.41244 56 -10370.24527 23343.27970 57 -27378.35029 -10370.24527 58 -25634.80124 -27378.35029 59 23283.95406 -25634.80124 60 -9149.41449 23283.95406 61 -45835.29120 -9149.41449 62 16906.19295 -45835.29120 63 24685.05187 16906.19295 64 -37427.82139 24685.05187 65 -36168.01931 -37427.82139 66 -6853.05224 -36168.01931 67 -12698.58085 -6853.05224 68 7772.77894 -12698.58085 69 -39491.65126 7772.77894 70 -13643.53023 -39491.65126 71 872.81027 -13643.53023 72 -13247.10815 872.81027 73 18462.25048 -13247.10815 74 -7102.50350 18462.25048 75 47138.94595 -7102.50350 76 -3225.02589 47138.94595 77 -16340.59556 -3225.02589 78 -6406.64664 -16340.59556 79 9009.09180 -6406.64664 80 637.80582 9009.09180 81 90990.53733 637.80582 82 5855.37005 90990.53733 83 -15124.53707 5855.37005 84 -19592.07734 -15124.53707 85 40224.71090 -19592.07734 86 -23193.79729 40224.71090 87 58917.55205 -23193.79729 88 2033.94115 58917.55205 89 -5466.26227 2033.94115 90 1398.63200 -5466.26227 91 -2041.73624 1398.63200 92 -2095.29767 -2041.73624 93 34224.83278 -2095.29767 94 27204.62671 34224.83278 95 3301.12882 27204.62671 96 -41376.91018 3301.12882 97 -38568.81157 -41376.91018 98 -9277.02263 -38568.81157 99 -24399.20816 -9277.02263 100 -6019.60787 -24399.20816 101 -31472.68582 -6019.60787 102 14648.59324 -31472.68582 103 -13530.09975 14648.59324 104 -845.99466 -13530.09975 105 -24151.52145 -845.99466 106 -10428.47811 -24151.52145 107 18395.41275 -10428.47811 108 -59446.96118 18395.41275 109 28878.29268 -59446.96118 110 -18610.87777 28878.29268 111 16786.24040 -18610.87777 112 -9924.18306 16786.24040 113 -3689.92204 -9924.18306 114 -4273.43895 -3689.92204 115 23717.24754 -4273.43895 116 -25098.48202 23717.24754 117 -12967.25895 -25098.48202 118 4226.57706 -12967.25895 119 -10914.88061 4226.57706 120 -4408.88356 -10914.88061 121 13411.78089 -4408.88356 122 11607.76170 13411.78089 123 -13751.38132 11607.76170 124 -5767.77195 -13751.38132 125 -5690.77489 -5767.77195 126 18544.19268 -5690.77489 127 -28515.54784 18544.19268 128 11645.52926 -28515.54784 129 -20555.61772 11645.52926 130 -2277.07150 -20555.61772 131 8927.21166 -2277.07150 132 -16688.26144 8927.21166 133 55128.25767 -16688.26144 134 38375.24645 55128.25767 135 6720.64763 38375.24645 136 64229.17024 6720.64763 137 2883.09832 64229.17024 138 -20390.45991 2883.09832 139 -4082.22846 -20390.45991 140 41799.91914 -4082.22846 141 66969.65619 41799.91914 142 -2959.85581 66969.65619 143 130164.88076 -2959.85581 144 20394.48804 130164.88076 145 -8571.48326 20394.48804 146 -16040.93679 -8571.48326 147 -2363.67727 -16040.93679 148 -41584.24952 -2363.67727 149 -20830.90566 -41584.24952 150 -24444.98567 -20830.90566 151 -24087.98567 -24444.98567 152 -26436.45943 -24087.98567 153 -24542.98567 -26436.45943 154 11634.65098 -24542.98567 155 -2875.74055 11634.65098 156 -24542.98567 -2875.74055 157 -24339.98567 -24542.98567 158 -23327.21687 -24339.98567 159 -8392.17326 -23327.21687 160 -17736.62574 -8392.17326 161 35587.03667 -17736.62574 162 -23573.98567 35587.03667 163 17106.49372 -23573.98567 > 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/7opyy1321541513.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/8box01321541513.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/9ppje1321541513.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/10umsr1321541513.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/115ya61321541513.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/12g7nf1321541513.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/1328fk1321541513.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/14fsu41321541513.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/15it3t1321541513.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/16h0u61321541513.tab") + } > > try(system("convert tmp/1p0si1321541513.ps tmp/1p0si1321541513.png",intern=TRUE)) character(0) > try(system("convert tmp/2p42e1321541513.ps tmp/2p42e1321541513.png",intern=TRUE)) character(0) > try(system("convert tmp/3wj5j1321541513.ps tmp/3wj5j1321541513.png",intern=TRUE)) character(0) > try(system("convert tmp/40iwh1321541513.ps tmp/40iwh1321541513.png",intern=TRUE)) character(0) > try(system("convert tmp/5yvkz1321541513.ps tmp/5yvkz1321541513.png",intern=TRUE)) character(0) > try(system("convert tmp/6h7d91321541513.ps tmp/6h7d91321541513.png",intern=TRUE)) character(0) > try(system("convert tmp/7opyy1321541513.ps tmp/7opyy1321541513.png",intern=TRUE)) character(0) > try(system("convert tmp/8box01321541513.ps tmp/8box01321541513.png",intern=TRUE)) character(0) > try(system("convert tmp/9ppje1321541513.ps tmp/9ppje1321541513.png",intern=TRUE)) character(0) > try(system("convert tmp/10umsr1321541513.ps tmp/10umsr1321541513.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 5.092 0.568 5.730