- R-br - DINF UFPR

Problema om o heatmap
by Michelle Bau Graczyk 07 Jul '15

07 Jul '15

Boa tarde, Estou usando a função heatmap para fazer um grafico da correlação entre 30 empresas. Porém a diagonal toda da matriz é 1, e a cor que aparece não é branco para todas elas. Alguém saberia me dizer o por quê disso? Abaixo segue o código. Muito obrigada, Michelle > if (!require("gplots")) { + install.packages("gplots", dependencies = TRUE) + library(gplots) + } > if (!require("RColorBrewer")) { + install.packages("RColorBrewer", dependencies = TRUE) + library(RColorBrewer) + } > library(gplots) > library(RColorBrewer) > > > file<-read.table("/Users/bau/Análise20%/MatrizCorrelaçãoHoraFixaAn20%2Verificação.txt", head=TRUE) > > matriz<-as.matrix(file) > matriz V1 V2 V3 V4 V5 V6 V7 V8 1 1.000000 -0.1488000 -0.120220 -0.278740 0.812920 -0.153150 -0.246640 -0.0706680 2 -0.148800 1.0000000 -0.094092 -0.291490 -0.026490 -0.084461 -0.274460 -0.0053051 3 -0.120220 -0.0940920 1.000000 -0.038117 -0.156290 0.443590 0.555750 -0.0185260 4 -0.278740 -0.2914900 -0.038117 1.000000 -0.186330 -0.316690 -0.233550 -0.1683500 5 0.812920 -0.0264900 -0.156290 -0.186330 1.000000 -0.179180 -0.240810 -0.0821580 6 -0.153150 -0.0844610 0.443590 -0.316690 -0.179180 1.000000 0.314870 -0.0805790 7 -0.246640 -0.2744600 0.555750 -0.233550 -0.240810 0.314870 1.000000 -0.1081200 8 -0.070668 -0.0053051 -0.018526 -0.168350 -0.082158 -0.080579 -0.108120 1.0000000 9 -0.103610 -0.2866200 -0.138530 -0.415740 -0.240890 -0.147270 -0.217480 0.1628300 10 -0.049682 -0.0473140 -0.051863 -0.214470 -0.060698 -0.118840 -0.111480 0.9682600 11 -0.263810 -0.2668200 -0.218920 -0.481630 -0.244870 -0.240020 -0.111070 -0.1727900 12 -0.188570 -0.0335670 0.602170 -0.189760 -0.223400 0.375510 0.474240 -0.1309300 13 -0.241810 -0.1810300 0.313570 -0.352580 -0.243430 0.235260 0.197230 -0.1601100 14 -0.236110 -0.1327000 0.221720 -0.417150 -0.283360 -0.026711 0.061281 0.2914000 15 -0.196730 -0.2440000 -0.180820 -0.472170 -0.120510 -0.266970 -0.263940 0.4074900 16 -0.242250 -0.2702000 -0.176820 -0.406400 -0.234990 -0.210460 0.025799 -0.1415800 17 -0.210830 -0.2452300 -0.194290 -0.340790 -0.188320 -0.318860 -0.244580 -0.0325100 18 -0.205970 -0.2793200 -0.158450 -0.395590 -0.103040 -0.040617 -0.165250 -0.0957780 19 -0.174340 -0.1529100 0.581590 -0.197270 -0.170600 0.362750 0.411190 -0.0440840 20 -0.236400 -0.3040200 -0.259570 -0.432960 -0.277750 -0.257810 -0.498010 -0.2060400 21 0.627290 -0.1816700 -0.148760 -0.334340 0.625360 -0.200010 -0.211250 -0.0982320 22 0.646400 -0.2604900 -0.107130 -0.347920 0.598150 -0.246790 -0.177750 -0.1006800 23 -0.166960 -0.3303900 -0.170460 -0.480110 -0.134900 -0.297750 -0.256080 0.0181360 24 -0.175720 -0.2457900 -0.334160 -0.475940 -0.279300 -0.476930 -0.122630 -0.1589900 25 -0.239010 -0.2516100 -0.261780 -0.358940 -0.243110 -0.330530 -0.418030 -0.0720400 26 -0.072637 -0.1991100 -0.108510 -0.306400 -0.122220 -0.110840 -0.035140 -0.0188130 27 -0.239730 0.0208830 -0.317810 -0.562200 -0.224260 -0.350740 -0.357450 -0.2385000 28 -0.081665 -0.0172600 -0.057269 -0.187130 -0.089078 -0.092451 -0.107760 0.9782200 29 -0.287560 -0.4044900 -0.222730 -0.402910 -0.246270 -0.374840 -0.170290 -0.2050000 30 -0.240640 -0.2494600 -0.161820 -0.363650 -0.301390 -0.335640 -0.221850 -0.0917310 V9 V10 V11 V12 V13 V14 V15 V16 1 -0.103610 -0.049682 -0.2638100 -0.188570 -0.241810 -0.236110 -0.19673 -0.242250 2 -0.286620 -0.047314 -0.2668200 -0.033567 -0.181030 -0.132700 -0.24400 -0.270200 3 -0.138530 -0.051863 -0.2189200 0.602170 0.313570 0.221720 -0.18082 -0.176820 4 -0.415740 -0.214470 -0.4816300 -0.189760 -0.352580 -0.417150 -0.47217 -0.406400 5 -0.240890 -0.060698 -0.2448700 -0.223400 -0.243430 -0.283360 -0.12051 -0.234990 6 -0.147270 -0.118840 -0.2400200 0.375510 0.235260 -0.026711 -0.26697 -0.210460 7 -0.217480 -0.111480 -0.1110700 0.474240 0.197230 0.061281 -0.26394 0.025799 8 0.162830 0.968260 -0.1727900 -0.130930 -0.160110 0.291400 0.40749 -0.141580 9 1.000000 0.111420 -0.3292500 -0.117090 -0.183380 -0.138610 0.10657 -0.297930 10 0.111420 1.000000 -0.1616400 -0.158130 -0.193640 0.249040 0.38221 -0.167030 11 -0.329250 -0.161640 1.0000000 -0.365690 -0.437690 -0.460970 -0.19613 0.173440 12 -0.117090 -0.158130 -0.3656900 1.000000 0.262660 0.152760 -0.28939 -0.286680 13 -0.183380 -0.193640 -0.4376900 0.262660 1.000000 -0.036207 -0.27265 -0.217780 14 -0.138610 0.249040 -0.4609700 0.152760 -0.036207 1.000000 -0.17618 -0.350990 15 0.106570 0.382210 -0.1961300 -0.289390 -0.272650 -0.176180 1.00000 -0.329490 16 -0.297930 -0.167030 0.1734400 -0.286680 -0.217780 -0.350990 -0.32949 1.000000 17 -0.142130 -0.041754 -0.3445100 -0.241300 -0.370250 -0.241910 -0.12044 -0.399280 18 -0.240860 -0.132840 -0.2431700 -0.205090 -0.395380 -0.246830 -0.26935 -0.405670 19 -0.133520 -0.045900 -0.2048300 0.445090 0.349490 0.098674 -0.12891 -0.145070 20 -0.284450 -0.268370 -0.4866800 -0.490160 -0.413300 -0.534260 -0.39506 -0.440230 21 -0.215960 -0.084613 -0.2693500 -0.224280 -0.053839 -0.298130 -0.19650 -0.249920 22 -0.290980 -0.088546 -0.2989100 -0.280310 -0.335690 -0.178300 -0.27805 -0.286220 23 -0.431420 0.024286 -0.3099400 -0.297010 -0.458870 -0.393310 -0.18978 -0.149720 24 -0.461750 -0.174440 -0.2290000 -0.263640 -0.384700 -0.321700 -0.37221 -0.111130 25 -0.277500 -0.117370 -0.3217100 -0.435670 -0.297100 -0.336510 -0.30911 -0.126820 26 0.028362 -0.038184 -0.0044301 -0.051589 -0.238220 -0.292680 -0.20221 0.068210 27 -0.297810 -0.279020 -0.6358500 -0.315320 -0.461570 -0.565570 -0.50525 -0.525960 28 0.138330 0.964190 -0.1637700 -0.135670 -0.175530 0.290640 0.40377 -0.175950 29 -0.377810 -0.226910 -0.0314590 -0.325840 -0.322050 -0.389640 -0.42031 -0.045736 30 -0.274010 -0.103120 -0.4103000 -0.299110 -0.285560 -0.338200 -0.48234 -0.446340 V17 V18 V19 V20 V21 V22 V23 V24 1 -0.210830 -0.205970 -0.174340 -0.23640 0.627290 0.646400 -0.166960 -0.175720 2 -0.245230 -0.279320 -0.152910 -0.30402 -0.181670 -0.260490 -0.330390 -0.245790 3 -0.194290 -0.158450 0.581590 -0.25957 -0.148760 -0.107130 -0.170460 -0.334160 4 -0.340790 -0.395590 -0.197270 -0.43296 -0.334340 -0.347920 -0.480110 -0.475940 5 -0.188320 -0.103040 -0.170600 -0.27775 0.625360 0.598150 -0.134900 -0.279300 6 -0.318860 -0.040617 0.362750 -0.25781 -0.200010 -0.246790 -0.297750 -0.476930 7 -0.244580 -0.165250 0.411190 -0.49801 -0.211250 -0.177750 -0.256080 -0.122630 8 -0.032510 -0.095778 -0.044084 -0.20604 -0.098232 -0.100680 0.018136 -0.158990 9 -0.142130 -0.240860 -0.133520 -0.28445 -0.215960 -0.290980 -0.431420 -0.461750 10 -0.041754 -0.132840 -0.045900 -0.26837 -0.084613 -0.088546 0.024286 -0.174440 11 -0.344510 -0.243170 -0.204830 -0.48668 -0.269350 -0.298910 -0.309940 -0.229000 12 -0.241300 -0.205090 0.445090 -0.49016 -0.224280 -0.280310 -0.297010 -0.263640 13 -0.370250 -0.395380 0.349490 -0.41330 -0.053839 -0.335690 -0.458870 -0.384700 14 -0.241910 -0.246830 0.098674 -0.53426 -0.298130 -0.178300 -0.393310 -0.321700 15 -0.120440 -0.269350 -0.128910 -0.39506 -0.196500 -0.278050 -0.189780 -0.372210 16 -0.399280 -0.405670 -0.145070 -0.44023 -0.249920 -0.286220 -0.149720 -0.111130 17 1.000000 -0.338590 -0.225910 -0.45329 -0.212720 -0.258960 -0.327150 -0.220570 18 -0.338590 1.000000 -0.123500 -0.35347 -0.206230 -0.234200 -0.321910 -0.225490 19 -0.225910 -0.123500 1.000000 -0.30228 -0.180950 -0.237280 -0.269610 -0.332320 20 -0.453290 -0.353470 -0.302280 1.00000 -0.160310 -0.443100 -0.498960 -0.604740 21 -0.212720 -0.206230 -0.180950 -0.16031 1.000000 0.394940 -0.220940 -0.175960 22 -0.258960 -0.234200 -0.237280 -0.44310 0.394940 1.000000 -0.191920 -0.295690 23 -0.327150 -0.321910 -0.269610 -0.49896 -0.220940 -0.191920 1.000000 -0.140490 24 -0.220570 -0.225490 -0.332320 -0.60474 -0.175960 -0.295690 -0.140490 1.000000 25 -0.357960 -0.439870 -0.245740 -0.45062 -0.296380 -0.284950 -0.336660 -0.372750 26 -0.099695 -0.289810 -0.190800 -0.16041 -0.071261 -0.219200 -0.111650 -0.023106 27 -0.516980 -0.148320 -0.330300 -0.57538 -0.288440 -0.420560 -0.667640 -0.552860 28 -0.029953 -0.068158 -0.037025 -0.21447 -0.102620 -0.114390 -0.020426 -0.182240 29 -0.386590 -0.372130 -0.114870 -0.59123 -0.328560 -0.407050 -0.379740 -0.086991 30 -0.296050 -0.491150 -0.252440 -0.20588 -0.176020 -0.156980 -0.549450 -0.447000 V25 V26 V27 V28 V29 V30 1 -0.23901 -0.0726370 -0.239730 -0.081665 -0.287560 -0.240640 2 -0.25161 -0.1991100 0.020883 -0.017260 -0.404490 -0.249460 3 -0.26178 -0.1085100 -0.317810 -0.057269 -0.222730 -0.161820 4 -0.35894 -0.3064000 -0.562200 -0.187130 -0.402910 -0.363650 5 -0.24311 -0.1222200 -0.224260 -0.089078 -0.246270 -0.301390 6 -0.33053 -0.1108400 -0.350740 -0.092451 -0.374840 -0.335640 7 -0.41803 -0.0351400 -0.357450 -0.107760 -0.170290 -0.221850 8 -0.07204 -0.0188130 -0.238500 0.978220 -0.205000 -0.091731 9 -0.27750 0.0283620 -0.297810 0.138330 -0.377810 -0.274010 10 -0.11737 -0.0381840 -0.279020 0.964190 -0.226910 -0.103120 11 -0.32171 -0.0044301 -0.635850 -0.163770 -0.031459 -0.410300 12 -0.43567 -0.0515890 -0.315320 -0.135670 -0.325840 -0.299110 13 -0.29710 -0.2382200 -0.461570 -0.175530 -0.322050 -0.285560 14 -0.33651 -0.2926800 -0.565570 0.290640 -0.389640 -0.338200 15 -0.30911 -0.2022100 -0.505250 0.403770 -0.420310 -0.482340 16 -0.12682 0.0682100 -0.525960 -0.175950 -0.045736 -0.446340 17 -0.35796 -0.0996950 -0.516980 -0.029953 -0.386590 -0.296050 18 -0.43987 -0.2898100 -0.148320 -0.068158 -0.372130 -0.491150 19 -0.24574 -0.1908000 -0.330300 -0.037025 -0.114870 -0.252440 20 -0.45062 -0.1604100 -0.575380 -0.214470 -0.591230 -0.205880 21 -0.29638 -0.0712610 -0.288440 -0.102620 -0.328560 -0.176020 22 -0.28495 -0.2192000 -0.420560 -0.114390 -0.407050 -0.156980 23 -0.33666 -0.1116500 -0.667640 -0.020426 -0.379740 -0.549450 24 -0.37275 -0.0231060 -0.552860 -0.182240 -0.086991 -0.447000 25 1.00000 -0.3001800 -0.582360 -0.103130 -0.591400 -0.361260 26 -0.30018 1.0000000 -0.324240 -0.051578 -0.085934 -0.274650 27 -0.58236 -0.3242400 1.000000 -0.236760 -0.719200 -0.605090 28 -0.10313 -0.0515780 -0.236760 1.000000 -0.215050 -0.104520 29 -0.59140 -0.0859340 -0.719200 -0.215050 1.000000 -0.539620 30 -0.36126 -0.2746500 -0.605090 -0.104520 -0.539620 1.000000 > rownames(matriz)<-c("AA","AIG","AXP","BA","CAT","C","DD","DIS","GE","GM","HD","HON","HPQ","IBM","INTC","JNJ","JPM","KO","MCD","MMM","MO","MRK","MSFT","PFE","PG","SBC","UTX","VZ","WMT","XOM") > colnames(matriz)<-c("AA","AIG","AXP","BA","CAT","C","DD","DIS","GE","GM","HD","HON","HPQ","IBM","INTC","JNJ","JPM","KO","MCD","MMM","MO","MRK","MSFT","PFE","PG","SBC","UTX","VZ","WMT","XOM") > > > my_palette <- colorRampPalette(c( "dark blue", "violet","white"))(n = 299) > png("/Users/bau/Grafico de calor/HeatMapCorrViolet2.jpeg", + width = 5*300, + height = 5*300, + res = 300, + pointsize = 8) > > heatmap(matriz,Rowv=NA,Colv=NA,col=my_palette,scale="column",margins=c(5,10),main="Correlação_HoraFixa_2") > dev.off() [image: Imagem inline 1]

2 1

legend.krige
by Hélio Gallo Rocha 07 Jul '15

07 Jul '15

Caros Listeiros, Estou tentando melhorar a visualização de um mapa de krigagem. Uma delas é ao plotar a legenda. Utilizei scale.vals para que os valores representados na legenda fossem os mesmos indicados pelo contorno ( contour). A dificuldade é fazer com que os valores fiquem justamente na divisa das cores, pois ficam sempre deslocados. Quem puder e tiver paciência para dar uma olhada https://drive.google.com/file/d/0ByCL48wb7T7Wek5Ud0g4bkgtWTQ/view?usp=shari… Agradeço desde já -- Hélio Gallo Rocha IFSULDEMINAS - Câmpus Muzambinho

1 0

Salvar grafico em jpeg
by Michelle Bau Graczyk 06 Jul '15

06 Jul '15

Bom dia, Estou com problemas em salvar gráficos em jpeg quando crio um laço. Ele não salva e não mostra mensagem alguma ou não salva e mostra uma mensagem quartz off screen. Quando uso o mesmo código para fazer apenas um gráfico e salvar ele não dá erro nenhum. Alguém, por favor, poderia me ajudar? Segue o código e os dados. library(gplots) library(RColorBrewer) require(lattice) for(i in 1:2){ file<-read.table(paste0("/Users/bau/Análise20%/MatrizCorrelaçãoHoraFixaAn20%",i,".txt"), head=TRUE) matriz<-as.matrix(file) rownames(matriz)<-c("AA","AIG","AXP","BA","CAT","C","DD","DIS","GE","GM","HD","HON","HPQ","IBM","INTC","JNJ","JPM","KO","MCD","MMM","MO","MRK","MSFT","PFE","PG","SBC","UTX","VZ","WMT","XOM") colnames(matriz)<-c("AA","AIG","AXP","BA","CAT","C","DD","DIS","GE","GM","HD","HON","HPQ","IBM","INTC","JNJ","JPM","KO","MCD","MMM","MO","MRK","MSFT","PFE","PG","SBC","UTX","VZ","WMT","XOM") matriz[1:5,] jpeg(filename = paste0("/Users/bau/Grafico de calor/HeatMapAZUL",i,".jpeg"), width = 480, height = 480, units = "px", pointsize = 12, quality = 75, bg = "white", res = NA) my_palette <- colorRampPalette(c( "dark blue", "violet","white"))(n = 299) png(paste0("/Users/bau/Grafico de calor/HeatMapAZUL",i,".png"), width = 5*300, height = 5*300, res = 300, pointsize = 8) levelplot(matriz, scale=list(x=list(rot=90)),at=seq( -1, 1, length=31), col.regions = my_palette,main= paste0("Correlação_HoraFixa_",i), xlab=NULL, ylab=NULL,pretty=FALSE) dev.off() } > file<-read.table("/Users/bau/Análise20%/MatrizCorrelaçãoHoraFixaAn20%1.txt", head=TRUE) > show(file) V1 V2 V3 V4 V5 V6 1 1.000000000 -0.013426078 -0.21285630 -0.09171000 -0.6231314 -0.20886277 2 -0.013426078 1.000000000 -0.19101532 -0.09269047 -0.3905452 -0.18698576 3 -0.212856304 -0.191015317 1.00000000 0.84406152 -0.3083666 0.97823817 4 -0.091709997 -0.092690470 0.84406152 1.00000000 -0.2213573 0.87796366 5 -0.623131438 -0.390545243 -0.30836662 -0.22135729 1.0000000 -0.31312560 6 -0.208862775 -0.186985764 0.97823817 0.87796366 -0.3131256 1.00000000 7 -0.504637041 -0.448676694 -0.25215668 -0.27538157 -0.5137430 -0.25444848 8 -0.467185960 -0.362268879 -0.30468949 -0.25907553 -0.5013547 -0.29230720 9 -0.497699689 -0.161087276 -0.37263674 -0.33835600 -0.6198943 -0.33038672 10 -0.524100951 -0.211592387 -0.30362088 -0.26835124 -0.5762579 -0.30552595 11 0.399221938 0.005904671 -0.24978163 -0.13225681 -0.5387313 -0.25498370 12 -0.197839618 -0.175675403 0.86442154 0.94829960 -0.2778112 0.87784476 13 -0.148276625 -0.293532154 0.24093457 -0.17666540 -0.4479914 0.21317377 14 -0.497814407 -0.111138707 -0.28168585 -0.20663433 -0.2801427 -0.23085704 15 -0.157977692 -0.149024426 0.86660398 0.95972443 -0.2446824 0.89157375 16 0.033288026 -0.356618173 -0.21621336 -0.19274479 -0.5635006 -0.20005142 17 -0.147716160 -0.207117938 0.97197757 0.85486085 -0.3239776 0.96789390 18 -0.045839759 -0.103767464 -0.18429365 -0.10376845 -0.4948730 -0.15166138 19 -0.212427688 -0.172610761 0.83109732 0.93752003 -0.2855651 0.85884265 20 0.495325219 0.220846605 -0.19408500 -0.05542756 -0.5081988 -0.18529317 21 -0.129377709 -0.189529548 0.83420407 0.93311687 -0.2571025 0.86614155 22 -0.279039235 -0.183975458 0.65615423 0.76146699 -0.2503563 0.68106200 23 0.009671092 -0.049383458 -0.04157648 0.06853473 -0.4408066 0.02434647 24 -0.114448903 -0.208502214 -0.25585583 -0.23975124 -0.5945710 -0.24042452 25 0.048300316 -0.050097188 0.82957327 0.95202128 -0.3010931 0.85659214 26 0.012219368 -0.255398346 -0.22028193 -0.20041563 -0.5335980 -0.20681233 27 0.089591597 0.064944658 -0.23856813 -0.08203396 -0.2550432 -0.21823074 28 -0.010193547 -0.260272495 -0.26536430 -0.19707519 -0.2196310 -0.23685789 29 0.257565480 0.155269068 -0.21697827 -0.07923628 -0.3889618 -0.19754306 30 0.122909786 -0.029950799 0.27500640 -0.07517171 -0.2770390 0.24016887 V7 V8 V9 V10 V11 V12 V13 1 -0.5046370 -0.4671860 -0.4976997 -0.5241010 3.992219e-01 -0.19783962 -0.1482766 2 -0.4486767 -0.3622689 -0.1610873 -0.2115924 5.904671e-03 -0.17567540 -0.2935322 3 -0.2521567 -0.3046895 -0.3726367 -0.3036209 -2.497816e-01 0.86442154 0.2409346 4 -0.2753816 -0.2590755 -0.3383560 -0.2683512 -1.322568e-01 0.94829960 -0.1766654 5 -0.5137430 -0.5013547 -0.6198943 -0.5762579 -5.387313e-01 -0.27781123 -0.4479914 6 -0.2544485 -0.2923072 -0.3303867 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0.15526907 -0.02995080 3 -0.23856813 -0.26536430 -0.21697827 0.27500640 4 -0.08203396 -0.19707519 -0.07923628 -0.07517171 5 -0.25504318 -0.21963101 -0.38896184 -0.27703901 6 -0.21823074 -0.23685789 -0.19754306 0.24016887 7 -0.40577431 -0.53559930 -0.34047029 -0.31228959 8 -0.42420522 -0.49514330 -0.51434521 -0.33663030 9 -0.55826844 -0.48949338 -0.38999084 -0.45053721 10 -0.41754979 -0.46481806 -0.45306342 -0.38931940 11 0.07514731 -0.06898829 0.14961950 0.06318255 12 -0.20531502 -0.23715318 -0.18721488 -0.13574861 13 -0.36469841 -0.13123625 -0.30971805 0.73592985 14 -0.24973099 -0.28371225 -0.44201145 -0.27645874 15 -0.17158152 -0.20221546 -0.13952450 -0.10875617 16 -0.41671510 0.16439014 -0.45351557 -0.04471142 17 -0.24691242 -0.19148725 -0.21848464 0.27019707 18 0.11090423 -0.43481448 0.10432716 -0.08632261 19 -0.23768820 -0.25152639 -0.20555802 -0.15581103 20 0.22033866 0.10439147 0.35752458 0.16307280 21 -0.22801837 -0.14745436 -0.19062429 -0.11619095 22 -0.27674657 -0.26775282 -0.34762731 -0.14332761 23 0.10694303 -0.02482201 0.07146488 0.06641018 24 -0.47297675 -0.03472561 -0.51940836 -0.17748601 25 -0.05642694 -0.09708505 -0.02788688 -0.02678411 26 -0.50517628 0.23412068 -0.46386362 -0.16582858 27 1.00000000 -0.24918184 0.37038916 0.04787473 28 -0.24918184 1.00000000 -0.36524071 -0.03518287 29 0.37038916 -0.36524071 1.00000000 0.05381014 30 0.04787473 -0.03518287 0.05381014 1.00000000 > file<-read.table("/Users/bau/Análise20%/MatrizCorrelaçãoHoraFixaAn20%2.txt", head=TRUE) > show(file) V1 V2 V3 V4 V5 V6 1 1.00000000 -0.148802897 -0.12022223 -0.27874441 0.81291519 -0.15314707 2 -0.14880290 1.000000000 -0.09409226 -0.29149169 -0.02648969 -0.08446126 3 -0.12022223 -0.094092262 1.00000000 -0.03811741 -0.15628940 0.44359269 4 -0.27874441 -0.291491692 -0.03811741 1.00000000 -0.18632625 -0.31669284 5 0.81291519 -0.026489690 -0.15628940 -0.18632625 1.00000000 -0.17918216 6 -0.15314707 -0.084461261 0.44359269 -0.31669284 -0.17918216 1.00000000 7 -0.24663544 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-0.018526128 -0.13852525 -0.05186325 -0.218921558 0.60216765 4 -0.23355268 -0.168345186 -0.41574205 -0.21446877 -0.481631938 -0.18976420 5 -0.24080820 -0.082158370 -0.24089018 -0.06069763 -0.244869878 -0.22340217 6 0.31486965 -0.080579019 -0.14727476 -0.11883671 -0.240018076 0.37550527 7 1.00000000 -0.108117711 -0.21747541 -0.11147706 -0.111072125 0.47424013 8 -0.10811771 1.000000000 0.16282881 0.96826237 -0.172786106 -0.13093180 9 -0.21747541 0.162828814 1.00000000 0.11141679 -0.329245225 -0.11708512 10 -0.11147706 0.968262371 0.11141679 1.00000000 -0.161644877 -0.15813273 11 -0.11107213 -0.172786106 -0.32924523 -0.16164488 1.000000000 -0.36569256 12 0.47424013 -0.130931805 -0.11708512 -0.15813273 -0.365692565 1.00000000 13 0.19722655 -0.160114242 -0.18338189 -0.19364346 -0.437691539 0.26266479 14 0.06128069 0.291396851 -0.13861471 0.24903670 -0.460966365 0.15276400 15 -0.26394085 0.407490719 0.10656953 0.38221296 -0.196127153 -0.28939473 16 0.02579863 -0.141584291 -0.29792794 -0.16702746 0.173436426 -0.28668500 17 -0.24457624 -0.032509553 -0.14213354 -0.04175404 -0.344507418 -0.24130339 18 -0.16524670 -0.095777875 -0.24086288 -0.13284008 -0.243171626 -0.20508840 19 0.41119310 -0.044084381 -0.13351615 -0.04590011 -0.204831234 0.44509275 20 -0.49800997 -0.206044074 -0.28445130 -0.26836924 -0.486683909 -0.49016395 21 -0.21125269 -0.098231939 -0.21596254 -0.08461270 -0.269347019 -0.22427553 22 -0.17775218 -0.100680159 -0.29098218 -0.08854590 -0.298909457 -0.28030716 23 -0.25608478 0.018135847 -0.43142227 0.02428580 -0.309940112 -0.29700599 24 -0.12263087 -0.158990465 -0.46174646 -0.17444194 -0.229003371 -0.26364499 25 -0.41803360 -0.072039588 -0.27749502 -0.11736600 -0.321707398 -0.43566677 26 -0.03514025 -0.018813181 0.02836178 -0.03818359 -0.004430114 -0.05158853 27 -0.35744763 -0.238496806 -0.29780862 -0.27901641 -0.635851068 -0.31531707 28 -0.10775754 0.978222774 0.13832863 0.96418680 -0.163768019 -0.13566979 29 -0.17028847 -0.204997655 -0.37780755 -0.22690994 -0.031458750 -0.32584427 30 -0.22184621 -0.091731035 -0.27400955 -0.10312034 -0.410299744 -0.29910598 V13 V14 V15 V16 V17 V18 V19 1 -0.24180551 -0.23610878 -0.1967282 -0.24225031 -0.21083189 -0.20596594 -0.17433828 2 -0.18102524 -0.13269887 -0.2439951 -0.27020364 -0.24523431 -0.27931752 -0.15291382 3 0.31357110 0.22171660 -0.1808179 -0.17681696 -0.19428859 -0.15845109 0.58159345 4 -0.35257546 -0.41715093 -0.4721732 -0.40640368 -0.34079396 -0.39558607 -0.19726939 5 -0.24343062 -0.28336114 -0.1205062 -0.23499450 -0.18832384 -0.10304093 -0.17059660 6 0.23525711 -0.02671104 -0.2669707 -0.21046189 -0.31886018 -0.04061684 0.36274947 7 0.19722655 0.06128069 -0.2639408 0.02579863 -0.24457624 -0.16524670 0.41119310 8 -0.16011424 0.29139685 0.4074907 -0.14158429 -0.03250955 -0.09577788 -0.04408438 9 -0.18338189 -0.13861471 0.1065695 -0.29792794 -0.14213354 -0.24086288 -0.13351615 10 -0.19364346 0.24903670 0.3822130 -0.16702746 -0.04175404 -0.13284008 -0.04590011 11 -0.43769154 -0.46096637 -0.1961272 0.17343643 -0.34450742 -0.24317163 -0.20483123 12 0.26266479 0.15276400 -0.2893947 -0.28668500 -0.24130339 -0.20508840 0.44509275 13 1.00000000 -0.03620744 -0.2726522 -0.21777660 -0.37025211 -0.39537844 0.34949092 14 -0.03620744 1.00000000 -0.1761751 -0.35098931 -0.24191413 -0.24683341 0.09867383 15 -0.27265224 -0.17617505 1.0000000 -0.32948521 -0.12044246 -0.26934847 -0.12890807 16 -0.21777660 -0.35098931 -0.3294852 1.00000000 -0.39928295 -0.40567215 -0.14507227 17 -0.37025211 -0.24191413 -0.1204425 -0.39928295 1.00000000 -0.33859072 -0.22590803 18 -0.39537844 -0.24683341 -0.2693485 -0.40567215 -0.33859072 1.00000000 -0.12349581 19 0.34949092 0.09867383 -0.1289081 -0.14507227 -0.22590803 -0.12349581 1.00000000 20 -0.41329686 -0.53426239 -0.3950604 -0.44023018 -0.45328676 -0.35346697 -0.30228469 21 -0.05383935 -0.29813229 -0.1965026 -0.24992044 -0.21272499 -0.20622737 -0.18094793 22 -0.33569375 -0.17830326 -0.2780501 -0.28622185 -0.25896306 -0.23420240 -0.23728301 23 -0.45887289 -0.39331122 -0.1897815 -0.14971863 -0.32715093 -0.32191285 -0.26960818 24 -0.38470376 -0.32169620 -0.3722094 -0.11113094 -0.22057358 -0.22548697 -0.33231501 25 -0.29710022 -0.33650812 -0.3091107 -0.12681911 -0.35795815 -0.43986760 -0.24573947 26 -0.23821696 -0.29267547 -0.2022070 0.06820963 -0.09969466 -0.28980539 -0.19080374 27 -0.46157443 -0.56557322 -0.5052536 -0.52595881 -0.51698055 -0.14831746 -0.33029722 28 -0.17553399 0.29063723 0.4037707 -0.17594595 -0.02995276 -0.06815830 -0.03702463 29 -0.32204504 -0.38963846 -0.4203058 -0.04573567 -0.38658959 -0.37212845 -0.11486707 30 -0.28556026 -0.33820289 -0.4823419 -0.44634143 -0.29604837 -0.49115267 -0.25244406 V20 V21 V22 V23 V24 V25 V26 1 -0.2364000 0.62729054 0.6464021 -0.16696302 -0.17572026 -0.23901217 -0.072636529 2 -0.3040231 -0.18167018 -0.2604907 -0.33038946 -0.24579003 -0.25161154 -0.199105473 3 -0.2595721 -0.14875756 -0.1071279 -0.17045972 -0.33416166 -0.26178381 -0.108510806 4 -0.4329635 -0.33433731 -0.3479210 -0.48010819 -0.47593906 -0.35894334 -0.306395637 5 -0.2777518 0.62535646 0.5981461 -0.13490094 -0.27930048 -0.24311055 -0.122215250 6 -0.2578149 -0.20001058 -0.2467946 -0.29774747 -0.47692840 -0.33052669 -0.110836651 7 -0.4980100 -0.21125269 -0.1777522 -0.25608478 -0.12263087 -0.41803360 -0.035140253 8 -0.2060441 -0.09823194 -0.1006802 0.01813585 -0.15899046 -0.07203959 -0.018813181 9 -0.2844513 -0.21596254 -0.2909822 -0.43142227 -0.46174646 -0.27749502 0.028361782 10 -0.2683692 -0.08461270 -0.0885459 0.02428580 -0.17444194 -0.11736600 -0.038183594 11 -0.4866839 -0.26934702 -0.2989095 -0.30994011 -0.22900337 -0.32170740 -0.004430114 12 -0.4901639 -0.22427553 -0.2803072 -0.29700599 -0.26364499 -0.43566677 -0.051588530 13 -0.4132969 -0.05383935 -0.3356937 -0.45887289 -0.38470376 -0.29710022 -0.238216957 14 -0.5342624 -0.29813229 -0.1783033 -0.39331122 -0.32169620 -0.33650812 -0.292675472 15 -0.3950604 -0.19650260 -0.2780501 -0.18978146 -0.37220940 -0.30911074 -0.202206974 16 -0.4402302 -0.24992044 -0.2862218 -0.14971863 -0.11113094 -0.12681911 0.068209633 17 -0.4532868 -0.21272499 -0.2589631 -0.32715093 -0.22057358 -0.35795815 -0.099694655 18 -0.3534670 -0.20622737 -0.2342024 -0.32191285 -0.22548697 -0.43986760 -0.289805392 19 -0.3022847 -0.18094793 -0.2372830 -0.26960818 -0.33231501 -0.24573947 -0.190803741 20 1.0000000 -0.16030914 -0.4431029 -0.49896363 -0.60474230 -0.45062087 -0.160412252 21 -0.1603091 1.00000000 0.3949372 -0.22093728 -0.17595649 -0.29637709 -0.071261480 22 -0.4431029 0.39493723 1.0000000 -0.19191603 -0.29568944 -0.28494691 -0.219197015 23 -0.4989636 -0.22093728 -0.1919160 1.00000000 -0.14049366 -0.33665607 -0.111651776 24 -0.6047423 -0.17595649 -0.2956894 -0.14049366 1.00000000 -0.37274908 -0.023105895 25 -0.4506209 -0.29637709 -0.2849469 -0.33665607 -0.37274908 1.00000000 -0.300176452 26 -0.1604123 -0.07126148 -0.2191970 -0.11165178 -0.02310590 -0.30017645 1.000000000 27 -0.5753831 -0.28844491 -0.4205560 -0.66764036 -0.55285753 -0.58236100 -0.324238501 28 -0.2144654 -0.10262187 -0.1143893 -0.02042606 -0.18223594 -0.10313373 -0.051578049 29 -0.5912338 -0.32856190 -0.4070485 -0.37974096 -0.08699138 -0.59139630 -0.085933586 30 -0.2058809 -0.17602279 -0.1569804 -0.54944644 -0.44700052 -0.36125601 -0.274653736 V27 V28 V29 V30 1 -0.23972558 -0.08166544 -0.28756105 -0.24063924 2 0.02088273 -0.01726043 -0.40449427 -0.24945999 3 -0.31781076 -0.05726889 -0.22273056 -0.16182331 4 -0.56220331 -0.18713444 -0.40290796 -0.36365438 5 -0.22425857 -0.08907762 -0.24626614 -0.30139490 6 -0.35074206 -0.09245104 -0.37484128 -0.33564494 7 -0.35744763 -0.10775754 -0.17028847 -0.22184621 8 -0.23849681 0.97822277 -0.20499765 -0.09173103 9 -0.29780862 0.13832863 -0.37780755 -0.27400955 10 -0.27901641 0.96418680 -0.22690994 -0.10312034 11 -0.63585107 -0.16376802 -0.03145875 -0.41029974 12 -0.31531707 -0.13566979 -0.32584427 -0.29910598 13 -0.46157443 -0.17553399 -0.32204504 -0.28556026 14 -0.56557322 0.29063723 -0.38963846 -0.33820289 15 -0.50525365 0.40377075 -0.42030579 -0.48234193 16 -0.52595881 -0.17594595 -0.04573567 -0.44634143 17 -0.51698055 -0.02995276 -0.38658959 -0.29604837 18 -0.14831746 -0.06815830 -0.37212845 -0.49115267 19 -0.33029722 -0.03702463 -0.11486707 -0.25244406 20 -0.57538312 -0.21446539 -0.59123378 -0.20588088 21 -0.28844491 -0.10262187 -0.32856190 -0.17602279 22 -0.42055596 -0.11438930 -0.40704848 -0.15698038 23 -0.66764036 -0.02042606 -0.37974096 -0.54944644 24 -0.55285753 -0.18223594 -0.08699138 -0.44700052 25 -0.58236100 -0.10313373 -0.59139630 -0.36125601 26 -0.32423850 -0.05157805 -0.08593359 -0.27465374 27 1.00000000 -0.23675539 -0.71920429 -0.60508621 28 -0.23675539 1.00000000 -0.21504839 -0.10451766 29 -0.71920429 -0.21504839 1.00000000 -0.53962323 30 -0.60508621 -0.10451766 -0.53962323 1.00000000

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Problemas com polygrid
by Arlindo Fabrício Corrêia 06 Jul '15

06 Jul '15

Boa tarde a todos, Pergunto se há alguma alteração na ferramenta "*polygrid* {geoR}" ou seria um problema que ocorre apenas em minha máquina. Já venho utilizando esta função há um tempo e atualmente estou com problemas para limitar um grid por meio de bordas utilizando o pacote. Pergunto também se é um problema do pacote ou a rotina deve ser alterada. Tentei gerar uma nova "borda" por meio dos comandos *SpatialPoints, SpatialPolygon* como apresentado no erro, porém, sem sucesso. Há uma outra solução aparente? Já fiz muitas tentativas e procurei exaustivamente e ainda não cheguei a uma solução. A seguir encaminho as linhas com o próprio exemplo da ferramenta. > #Examples> #> poly <- matrix(c(.2, .8, .7, .1, .2, .1, .2, .7, .7, .1), ncol=2)> plot(0:1, 0:1, type="n")> lines(poly)> poly.in <- polygrid(seq(0,1,l=11), seq(0,1,l=11), poly, vec=TRUE)Erro em (function (classes, fdef, mtable) : unable to find an inherited method for function ‘overlay’ for signature ‘"SpatialPoints"’> points(poly.in$xy)Erro em points(poly.in$xy) : objeto 'poly.in' não encontrado > Agradeço pela atenção. -- Arlindo Fabrício Corrêia Engenheiro Agrônomo Doutorando em Agronomia - UNIOESTE - Mal. Cdo. Rondon/PR

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[off] z-score
by Rodolfo Timoteo da Silva 05 Jul '15

05 Jul '15

Pessoas, permitam-me fazer um flashback aproveitando o "expertise" em estatística da lista. Estou fazendo uma revisão em estatística, e só para confirmar em relação ao exercício da figura em anexo. x = 28 média = 24 desvio-padrão = 1.6 z = (28 - 24) / 1.6 z = 2.5 Assim, a proporção para ser maior que 28mpg seria, pela tabela da distribuição normal, (1 - 0.9938 = 0.0062 ou 0.62%). Correções são muito bem vindas. Antecipadamente P.S.: é possível calcular usando somente [1 - pnorm(28,24,1.6)] ou tem outro comando? -- --- Zhu

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Função LOGIT
by Ricardo Gallo 05 Jul '15

05 Jul '15

Boa noite galera, Estou precisando de uma ajuda, estou com umas funções "logit" para distribuição binomial (0 e 1) usando GLM, e gostaria de aplicar a máxima verossimilhança no lugar. Segue o comando usado: mod1<-glm(XF ~ X1, data = dados, family = binomial(link="logit"))summary(mod1)exp(coef(mod1)) Acho que é algo simples, mas não estou conseguindo. Vlw - Ricardo Gallo - Engenheiro Florestal Doutorando em Ciência Florestal - UFV(31) 8213 5170 (claro)

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Modelo Periódico Gama Autorregressivo
by Victor Eduardo 04 Jul '15

04 Jul '15

Pessoal, alguém aqui chegou a trabalhar com modelos gama autorregressivo no R? Tenho algumas dúvidas na minha programação. Alguém conhece algum fórum ou material que tenha discussão sobre esse assunto no R? Atenciosamente, Victor Eduardo

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Transpor linhas em colunas
by Alexandre Loures 04 Jul '15

04 Jul '15

Bom dia! Tenho uma base em que há 1.241 ID's (FORMATO CHARACTER) sendo que cada ID repete 1.980 vezes. Por exemplo, ANO ID PREÇO 1989 0101 8 1990 0101 7 1991 0101 15 1989 0102 9 1990 0102 8 1991 0102 2 1989 0103 3 1990 0103 10 1991 0103 11 1989 0104 6 1990 0104 1 1991 0104 11 . . . Porém gostaria de transformar cada uma dessas ID's em colunas e que assumissem os valores da variável PREÇO. ANO ID_0101 ID_0102 ID_0103 ID_0104 ... 1989 8 9 3 6 1990 7 8 10 1 1991 15 2 11 11 Alguém poderia me ajudar? Desde já muito obrigado! -- *Alexandre Rodrigues Loures*

2 2

Ajuda com Kaplan-Meier
by "Ary Serpa Neto" 04 Jul '15

04 Jul '15

2 1

Beamer e RMarkdown
by David Feitosa 04 Jul '15

04 Jul '15

Caros, boa tarde. Estou criando um documento e gostaria de usar RMarkdown no lugar do LaTex convencional. Tentei o abaixo seguindo as orientações do site e de alguns blogs. Deparei-me com dois "problemas": O 1º que consistia em gerar uma lista de segundo nível, consegui contornar adicionando mais dois espaços na indentação, pois a documentação dizia para usar apenas 2, mas só resolvi com 4. O 2º consiste em gerar a lista com os tópicos de cada slide. Quando escolho gerar apenas o documento como PDF, é gerado o sumário, mas quando mudo para o BEAMER, é gerado um slide em branco. Alguém teria ideia de como resolver? Segue o "código". Eu comento/descomento a linha do "pdf_document" e "beamer_presentation" para mudar o formato de documento final. Gostaria de usar a do beamer: --- title: "Título" author: "David Feitosa" output: # pdf_document: beamer_presentation: toc: true header-includes: - \usepackage[brazil]{babel} colortheme: "dolphin" --- # R Markdown 1 - A - B - C # R Markdown 2 - A - B - C # R Markdown 3 - A - B - C # R Markdown 4 - A - B - C # R Markdown 5 - A - B - C # R Markdown 6 - A - B - C Meu ambiente: R version 3.2.1 (2015-06-18) -- "World-Famous Astronaut" Platform: x86_64-w64-mingw32/x64 (64-bit) RStudio Version 0.99.442 knitr 1.10.5 pdfTeX, Version 3.14159265-2.6-1.40.15 (MiKTeX 2.9 64-bit) pandoc 1.14.0.1 Compiled with texmath 0.8.2, highlighting-kate 0.6. Atenciosamente, David Feitosa (\_(\ (=°;°) (("")("")

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