R version 3.0.3 (2014-03-06) -- "Warm Puppy" Copyright (C) 2014 The R Foundation for Statistical Computing Platform: i686-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('GTM' + ,232.21 + ,49.04 + ,21.38 + ,68 + ,77.34 + ,49.87 + ,7.88 + ,12.86 + ,3.70 + ,77.34 + ,59.18 + ,16.81 + ,1.420 + ,0.14 + ,0.44 + ,0.82 + ,0.9 + ,0.87 + ,0.66 + ,0.81 + ,0.83 + ,0.77 + ,95.36 + ,4.64 + ,47.3 + ,48.06 + ,41.04 + ,4.16 + ,36.88 + ,'PRO' + ,46.99 + ,14.60 + ,15.24 + ,58 + ,44.45 + ,38.10 + ,3.17 + ,22.86 + ,4.44 + ,44.45 + ,34.29 + ,9.52 + ,86 + ,0.02 + ,0.49 + ,0.74 + ,0.82 + ,0.4 + ,0.59 + ,0.75 + ,0.73 + ,0.69 + ,96.65 + ,3.35 + ,51.85 + ,44.8 + ,43.42 + ,6.37 + ,37.05 + ,'SAC' + ,153.15 + ,29.68 + ,15.79 + ,21 + ,36.95 + ,10.10 + ,1.58 + ,13.89 + ,3.79 + ,36.95 + ,29.68 + ,6.63 + ,590 + ,0.36 + ,0.48 + ,0.76 + ,0.86 + ,0.83 + ,0.6 + ,0.75 + ,0.88 + ,0.75 + ,97.01 + ,2.99 + ,48.35 + ,48.66 + ,61.43 + ,10.69 + ,50.74 + ,'CHM' + ,76.40 + ,11.39 + ,7.43 + ,14 + ,35.81 + ,9.41 + ,0.83 + ,5.45 + ,1.32 + ,35.81 + ,26.40 + ,9.24 + ,325 + ,0.78 + ,0.56 + ,0.7 + ,0.79 + ,0.5 + ,0.43 + ,0.67 + ,0.78 + ,0.63 + ,97.42 + ,2.58 + ,55.68 + ,41.74 + ,68.27 + ,18.59 + ,49.68 + ,'ESC' + ,301.06 + ,35.59 + ,26.33 + ,98 + ,73.88 + ,70.75 + ,8.11 + ,28.47 + ,3.99 + ,73.88 + ,59.64 + ,12.10 + ,156 + ,0.07 + ,0.49 + ,0.72 + ,0.81 + ,0.5 + ,0.46 + ,0.8 + ,0.74 + ,0.67 + ,94.67 + ,5.33 + ,38.57 + ,56.1 + ,47.93 + ,3.75 + ,44.18 + ,'SRO' + ,80.60 + ,19.72 + ,20.29 + ,82 + ,67.84 + ,56.83 + ,4.64 + ,24.64 + ,8.70 + ,67.84 + ,55.67 + ,11.89 + ,109 + ,0.03 + ,0.52 + ,0.71 + ,0.8 + ,0.4 + ,0.49 + ,0.65 + ,0.56 + ,0.56 + ,96.22 + ,3.78 + ,55.42 + ,40.8 + ,58.41 + ,11.34 + ,47.07 + ,'SOL' + ,11.61 + ,5.57 + ,0.93 + ,9 + ,18.35 + ,3.72 + ,0.00 + ,7.66 + ,1.16 + ,18.35 + ,13.47 + ,4.88 + ,369 + ,0.96 + ,0.54 + ,0.61 + ,0.65 + ,0.53 + ,0.41 + ,0.69 + ,0.69 + ,0.6 + ,97.13 + ,2.87 + ,45.41 + ,51.72 + ,81.24 + ,24.02 + ,57.22 + ,'TOT' + ,21.37 + ,4.44 + ,0.63 + ,8 + ,15.87 + ,0.85 + ,0.42 + ,9.10 + ,3.17 + ,15.87 + ,10.58 + ,4.44 + ,439 + ,0.97 + ,0.54 + ,0.61 + ,0.68 + ,0.47 + ,0.41 + ,0.51 + ,0.59 + ,0.5 + ,94.18 + ,5.82 + ,58.74 + ,35.44 + ,76.15 + ,24.74 + ,51.41 + ,'QUT' + ,100.46 + ,30.67 + ,9.47 + ,27 + ,34.83 + ,17.54 + ,1.77 + ,10.35 + ,2.65 + ,34.83 + ,25.87 + ,8.08 + ,372 + ,0.52 + ,0.53 + ,0.7 + ,0.8 + ,0.59 + ,0.51 + ,0.83 + ,0.72 + ,0.69 + ,95.62 + ,4.38 + ,59.43 + ,36.19 + ,66.5 + ,15.42 + ,51.08 + ,'SUC' + ,105.26 + ,26.94 + ,9.95 + ,31 + ,36.68 + ,17.20 + ,2.28 + ,17.20 + ,2.69 + ,36.68 + ,29.01 + ,7.25 + ,202 + ,0.23 + ,0.53 + ,0.65 + ,0.73 + ,0.41 + ,0.39 + ,0.71 + ,0.77 + ,0.62 + ,96.63 + ,3.37 + ,31.4 + ,65.23 + ,73.07 + ,24.07 + ,49 + ,'RET' + ,86.14 + ,24.09 + ,5.94 + ,36 + ,37.62 + ,23.10 + ,1.32 + ,18.15 + ,2.97 + ,37.62 + ,28.71 + ,7.59 + ,178 + ,0.15 + ,0.54 + ,0.69 + ,0.77 + ,0.39 + ,0.4 + ,0.62 + ,0.74 + ,0.59 + ,95.21 + ,4.79 + ,42.09 + ,53.12 + ,60.5 + ,13.38 + ,47.12 + ,'SMA' + ,22.80 + ,6.26 + ,4.70 + ,16 + ,12.72 + ,10.67 + ,0.29 + ,6.85 + ,0.88 + ,12.72 + ,9.88 + ,2.64 + ,288 + ,0.3 + ,0.56 + ,0.66 + ,0.72 + ,0.27 + ,0.39 + ,0.59 + ,0.69 + ,0.56 + ,96.78 + ,3.22 + ,64.41 + ,32.37 + ,65.08 + ,15.15 + ,49.93 + ,'HUE' + ,48.07 + ,7.48 + ,4.35 + ,6 + ,13.12 + ,3.82 + ,0.26 + ,3.65 + ,0.26 + ,13.12 + ,10.00 + ,2.09 + ,156 + ,0.57 + ,0.57 + ,0.57 + ,0.65 + ,0.29 + ,0.4 + ,0.57 + ,0.7 + ,0.56 + ,97.05 + ,2.95 + ,69.43 + ,27.62 + ,55.68 + ,9.57 + ,46.11 + ,'QUI' + ,23.44 + ,5.44 + ,2.09 + ,6 + ,14.44 + ,2.30 + ,0.31 + ,5.55 + ,1.05 + ,14.44 + ,9.00 + ,4.81 + ,131 + ,0.89 + ,0.58 + ,0.53 + ,0.58 + ,0.31 + ,0.42 + ,0.45 + ,0.66 + ,0.51 + ,97.07 + ,2.93 + ,59.57 + ,37.5 + ,66.47 + ,16.15 + ,50.32 + ,'BVP' + ,39.47 + ,21.97 + ,6.33 + ,19 + ,23.09 + ,7.45 + ,1.49 + ,16.38 + ,1.86 + ,23.09 + ,16.38 + ,5.59 + ,25 + ,0.56 + ,0.54 + ,0.63 + ,0.69 + ,0.31 + ,0.55 + ,0.56 + ,0.68 + ,0.59 + ,96.33 + ,3.67 + ,59.92 + ,36.41 + ,62.39 + ,22.36 + ,40.03 + ,'AVP' + ,33.84 + ,11.52 + ,6.97 + ,13 + ,14.47 + ,7.41 + ,0.45 + ,7.32 + ,1.25 + ,14.47 + ,11.25 + ,2.86 + ,371 + ,0.9 + ,0.58 + ,0.56 + ,0.6 + ,0.23 + ,0.24 + ,0.29 + ,0.42 + ,0.32 + ,94.46 + ,5.54 + ,50.45 + ,44.01 + ,77.2 + ,30.2 + ,47 + ,'PET' + ,51.40 + ,7.00 + ,11.30 + ,59 + ,25.30 + ,41.54 + ,3.66 + ,17.35 + ,2.71 + ,25.30 + ,21.48 + ,3.66 + ,17 + ,0.32 + ,0.59 + ,0.66 + ,0.75 + ,0.31 + ,0.36 + ,0.54 + ,0.43 + ,0.44 + ,97.88 + ,2.12 + ,53.12 + ,44.76 + ,62.7 + ,15.54 + ,47.16 + ,'IZA' + ,103.71 + ,12.66 + ,20.69 + ,80 + ,49.18 + ,59.16 + ,6.82 + ,17.28 + ,3.41 + ,49.18 + ,38.95 + ,9.49 + ,55 + ,0.27 + ,0.52 + ,0.68 + ,0.78 + ,0.36 + ,0.55 + ,0.72 + ,0.64 + ,0.63 + ,96.88 + ,3.12 + ,49.92 + ,46.96 + ,58.38 + ,24.63 + ,33.75 + ,'ZAC' + ,64.15 + ,8.13 + ,42.46 + ,93 + ,67.76 + ,66.41 + ,7.68 + ,23.49 + ,5.87 + ,67.76 + ,50.60 + ,14.91 + ,82 + ,0.01 + ,0.48 + ,0.68 + ,0.79 + ,0.43 + ,0.59 + ,0.69 + ,0.76 + ,0.68 + ,97.58 + ,2.42 + ,41.76 + ,55.82 + ,61.48 + ,24.96 + ,36.52 + ,'CHQ' + ,75.00 + ,11.41 + ,29.89 + ,96 + ,58.15 + ,58.70 + ,6.25 + ,38.32 + ,7.34 + ,58.15 + ,45.38 + ,11.14 + ,153 + ,0.07 + ,0.54 + ,0.63 + ,0.72 + ,0.27 + ,0.5 + ,0.57 + ,0.64 + ,0.57 + ,97.93 + ,2.07 + ,47.66 + ,50.27 + ,66.01 + ,22.03 + ,33.98 + ,'JAL' + ,12.42 + ,11.14 + ,12.42 + ,54 + ,35.02 + ,33.11 + ,4.78 + ,18.15 + ,5.09 + ,35.02 + ,28.97 + ,5.09 + ,154 + ,0.00001 + ,0.55 + ,0.65 + ,0.76 + ,0.33 + ,0.46 + ,0.51 + ,0.62 + ,0.53 + ,97.9 + ,2.1 + ,42.62 + ,55.28 + ,73.43 + ,18.88 + ,54.55 + ,'JUT' + ,34.77 + ,11.74 + ,6.22 + ,61 + ,46.29 + ,42.83 + ,7.37 + ,14.05 + ,2.30 + ,46.29 + ,36.38 + ,9.67 + ,131 + ,0.03 + ,0.5 + ,0.69 + ,0.77 + ,0.32 + ,0.5 + ,0.69 + ,0.62 + ,0.6 + ,97.51 + ,2.49 + ,52.56 + ,44.95 + ,48.92 + ,14.31 + ,34.61) + ,dim=c(30 + ,22) + ,dimnames=list(c('DEP' + ,'Delitos' + ,'Capturas_Delitos' + ,'Armas_robadas' + ,'Homicidios' + ,'OtrasMuertes' + ,'HArmaFuego_M' + ,'HArmaFuego_F' + ,'HNoArmaFuegoM' + ,'HNoArmaFuegoF' + ,'OtrasMuertesT' + ,'OtrasMuertesH' + ,'OtrasMuertesM' + ,'DensidadPoblación' + ,'Etnicidad' + ,'Juventud' + ,'Escolaridad' + ,'Alfabetismo' + ,'Urbanidad' + ,'IH' + ,'ICV' + ,'ISP' + ,'IBH' + ,'Ocupados' + ,'Desocupados' + ,'Subocupados' + ,'OcupadosPlenos' + ,'PobrezaTotal' + ,'PobrezaExtrema' + ,'PobrezaNoExtrema') + ,1:22)) > y <- array(NA,dim=c(30,22),dimnames=list(c('DEP','Delitos','Capturas_Delitos','Armas_robadas','Homicidios','OtrasMuertes','HArmaFuego_M','HArmaFuego_F','HNoArmaFuegoM','HNoArmaFuegoF','OtrasMuertesT','OtrasMuertesH','OtrasMuertesM','DensidadPoblación','Etnicidad','Juventud','Escolaridad','Alfabetismo','Urbanidad','IH','ICV','ISP','IBH','Ocupados','Desocupados','Subocupados','OcupadosPlenos','PobrezaTotal','PobrezaExtrema','PobrezaNoExtrema'),1:22)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } There were 22 warnings (use warnings() to see them) > par1 = '4' > par1 <- '4' > #'GNU S' R Code compiled by R2WASP v. 1.2.291 () > #Author: root > #To cite this work: Wessa P., 2012, Factor Analysis (v1.0.2) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_factor_analysis.wasp/ > #Source of accompanying publication: > # > library(psych) > par1 <- as.numeric(par1) > x <- t(x) > nrows <- length(x[,1]) > ncols <- length(x[1,]) > y <- array(as.double(x[1:nrows,2:ncols]),dim=c(nrows,ncols-1)) > colnames(y) <- colnames(x)[2:ncols] > rownames(y) <- x[,1] > y Delitos Capturas_Delitos Armas_robadas Homicidios OtrasMuertes HArmaFuego_M GTM 232.21 49.04 21.38 68 77.34 49.87 PRO 46.99 14.60 15.24 58 44.45 38.10 SAC 153.15 29.68 15.79 21 36.95 10.10 CHM 76.40 11.39 7.43 14 35.81 9.41 ESC 301.06 35.59 26.33 98 73.88 70.75 SRO 80.60 19.72 20.29 82 67.84 56.83 SOL 11.61 5.57 0.93 9 18.35 3.72 TOT 21.37 4.44 0.63 8 15.87 0.85 QUT 100.46 30.67 9.47 27 34.83 17.54 SUC 105.26 26.94 9.95 31 36.68 17.20 RET 86.14 24.09 5.94 36 37.62 23.10 SMA 22.80 6.26 4.70 16 12.72 10.67 HUE 48.07 7.48 4.35 6 13.12 3.82 QUI 23.44 5.44 2.09 6 14.44 2.30 BVP 39.47 21.97 6.33 19 23.09 7.45 AVP 33.84 11.52 6.97 13 14.47 7.41 PET 51.40 7.00 11.30 59 25.30 41.54 IZA 103.71 12.66 20.69 80 49.18 59.16 ZAC 64.15 8.13 42.46 93 67.76 66.41 CHQ 75.00 11.41 29.89 96 58.15 58.70 JAL 12.42 11.14 12.42 54 35.02 33.11 JUT 34.77 11.74 6.22 61 46.29 42.83 HArmaFuego_F HNoArmaFuegoM HNoArmaFuegoF OtrasMuertesT OtrasMuertesH GTM 7.88 12.86 3.70 77.34 59.18 PRO 3.17 22.86 4.44 44.45 34.29 SAC 1.58 13.89 3.79 36.95 29.68 CHM 0.83 5.45 1.32 35.81 26.40 ESC 8.11 28.47 3.99 73.88 59.64 SRO 4.64 24.64 8.70 67.84 55.67 SOL 0.00 7.66 1.16 18.35 13.47 TOT 0.42 9.10 3.17 15.87 10.58 QUT 1.77 10.35 2.65 34.83 25.87 SUC 2.28 17.20 2.69 36.68 29.01 RET 1.32 18.15 2.97 37.62 28.71 SMA 0.29 6.85 0.88 12.72 9.88 HUE 0.26 3.65 0.26 13.12 10.00 QUI 0.31 5.55 1.05 14.44 9.00 BVP 1.49 16.38 1.86 23.09 16.38 AVP 0.45 7.32 1.25 14.47 11.25 PET 3.66 17.35 2.71 25.30 21.48 IZA 6.82 17.28 3.41 49.18 38.95 ZAC 7.68 23.49 5.87 67.76 50.60 CHQ 6.25 38.32 7.34 58.15 45.38 JAL 4.78 18.15 5.09 35.02 28.97 JUT 7.37 14.05 2.30 46.29 36.38 OtrasMuertesM DensidadPoblaci\363n Etnicidad Juventud Escolaridad GTM 16.81 1.42 0.14000 0.44 0.82 PRO 9.52 86.00 0.02000 0.49 0.74 SAC 6.63 590.00 0.36000 0.48 0.76 CHM 9.24 325.00 0.78000 0.56 0.70 ESC 12.10 156.00 0.07000 0.49 0.72 SRO 11.89 109.00 0.03000 0.52 0.71 SOL 4.88 369.00 0.96000 0.54 0.61 TOT 4.44 439.00 0.97000 0.54 0.61 QUT 8.08 372.00 0.52000 0.53 0.70 SUC 7.25 202.00 0.23000 0.53 0.65 RET 7.59 178.00 0.15000 0.54 0.69 SMA 2.64 288.00 0.30000 0.56 0.66 HUE 2.09 156.00 0.57000 0.57 0.57 QUI 4.81 131.00 0.89000 0.58 0.53 BVP 5.59 25.00 0.56000 0.54 0.63 AVP 2.86 371.00 0.90000 0.58 0.56 PET 3.66 17.00 0.32000 0.59 0.66 IZA 9.49 55.00 0.27000 0.52 0.68 ZAC 14.91 82.00 0.01000 0.48 0.68 CHQ 11.14 153.00 0.07000 0.54 0.63 JAL 5.09 154.00 0.00001 0.55 0.65 JUT 9.67 131.00 0.03000 0.50 0.69 Alfabetismo Urbanidad IH ICV ISP IBH Ocupados Desocupados Subocupados GTM 0.90 0.87 0.66 0.81 0.83 0.77 95.36 4.64 47.30 PRO 0.82 0.40 0.59 0.75 0.73 0.69 96.65 3.35 51.85 SAC 0.86 0.83 0.60 0.75 0.88 0.75 97.01 2.99 48.35 CHM 0.79 0.50 0.43 0.67 0.78 0.63 97.42 2.58 55.68 ESC 0.81 0.50 0.46 0.80 0.74 0.67 94.67 5.33 38.57 SRO 0.80 0.40 0.49 0.65 0.56 0.56 96.22 3.78 55.42 SOL 0.65 0.53 0.41 0.69 0.69 0.60 97.13 2.87 45.41 TOT 0.68 0.47 0.41 0.51 0.59 0.50 94.18 5.82 58.74 QUT 0.80 0.59 0.51 0.83 0.72 0.69 95.62 4.38 59.43 SUC 0.73 0.41 0.39 0.71 0.77 0.62 96.63 3.37 31.40 RET 0.77 0.39 0.40 0.62 0.74 0.59 95.21 4.79 42.09 SMA 0.72 0.27 0.39 0.59 0.69 0.56 96.78 3.22 64.41 HUE 0.65 0.29 0.40 0.57 0.70 0.56 97.05 2.95 69.43 QUI 0.58 0.31 0.42 0.45 0.66 0.51 97.07 2.93 59.57 BVP 0.69 0.31 0.55 0.56 0.68 0.59 96.33 3.67 59.92 AVP 0.60 0.23 0.24 0.29 0.42 0.32 94.46 5.54 50.45 PET 0.75 0.31 0.36 0.54 0.43 0.44 97.88 2.12 53.12 IZA 0.78 0.36 0.55 0.72 0.64 0.63 96.88 3.12 49.92 ZAC 0.79 0.43 0.59 0.69 0.76 0.68 97.58 2.42 41.76 CHQ 0.72 0.27 0.50 0.57 0.64 0.57 97.93 2.07 47.66 JAL 0.76 0.33 0.46 0.51 0.62 0.53 97.90 2.10 42.62 JUT 0.77 0.32 0.50 0.69 0.62 0.60 97.51 2.49 52.56 OcupadosPlenos PobrezaTotal PobrezaExtrema PobrezaNoExtrema GTM 48.06 41.04 4.16 36.88 PRO 44.80 43.42 6.37 37.05 SAC 48.66 61.43 10.69 50.74 CHM 41.74 68.27 18.59 49.68 ESC 56.10 47.93 3.75 44.18 SRO 40.80 58.41 11.34 47.07 SOL 51.72 81.24 24.02 57.22 TOT 35.44 76.15 24.74 51.41 QUT 36.19 66.50 15.42 51.08 SUC 65.23 73.07 24.07 49.00 RET 53.12 60.50 13.38 47.12 SMA 32.37 65.08 15.15 49.93 HUE 27.62 55.68 9.57 46.11 QUI 37.50 66.47 16.15 50.32 BVP 36.41 62.39 22.36 40.03 AVP 44.01 77.20 30.20 47.00 PET 44.76 62.70 15.54 47.16 IZA 46.96 58.38 24.63 33.75 ZAC 55.82 61.48 24.96 36.52 CHQ 50.27 66.01 22.03 33.98 JAL 55.28 73.43 18.88 54.55 JUT 44.95 48.92 14.31 34.61 > fit <- principal(y, nfactors=par1, rotate='varimax') Loading required package: GPArotation The determinant of the smoothed correlation was zero. This means the objective function is not defined for the null model either. The Chi square is thus based upon observed correlations. In factor.stats, the correlation matrix is singular, an approximation is used In factor.scores, the correlation matrix is singular, an approximation is used I was unable to calculate the factor score weights, factor loadings used instead Warning messages: 1: In log(det(m.inv.r)) : NaNs produced 2: In cor.smooth(r) : Matrix was not positive definite, smoothing was done 3: In cor.smooth(r) : Matrix was not positive definite, smoothing was done > fit Principal Components Analysis Call: principal(r = y, nfactors = par1, rotate = "varimax") Standardized loadings (pattern matrix) based upon correlation matrix RC1 RC2 RC3 RC4 h2 u2 Delitos 0.38 0.61 0.51 0.09 0.79 0.212 Capturas_Delitos 0.22 0.70 0.51 0.07 0.80 0.200 Armas_robadas 0.82 0.25 -0.08 0.21 0.79 0.213 Homicidios 0.97 0.13 -0.03 0.08 0.97 0.029 OtrasMuertes 0.83 0.48 0.14 0.12 0.96 0.039 HArmaFuego_M 0.96 0.15 0.00 0.04 0.95 0.050 HArmaFuego_F 0.90 0.25 -0.01 0.03 0.88 0.125 HNoArmaFuegoM 0.84 0.03 -0.04 0.25 0.78 0.224 HNoArmaFuegoF 0.76 0.10 -0.04 0.25 0.65 0.351 OtrasMuertesT 0.83 0.48 0.14 0.12 0.96 0.039 OtrasMuertesH 0.84 0.46 0.14 0.13 0.96 0.038 OtrasMuertesM 0.73 0.55 0.10 0.09 0.84 0.158 DensidadPoblaci\363n -0.67 0.12 0.16 0.39 0.65 0.354 Etnicidad -0.79 -0.30 0.18 0.01 0.75 0.253 Juventud -0.45 -0.78 -0.15 -0.07 0.84 0.159 Escolaridad 0.39 0.81 0.12 -0.01 0.83 0.173 Alfabetismo 0.45 0.78 0.03 0.02 0.82 0.178 Urbanidad -0.11 0.87 0.24 0.19 0.86 0.145 IH 0.41 0.74 -0.21 -0.16 0.79 0.209 ICV 0.24 0.87 -0.03 0.03 0.81 0.187 ISP -0.11 0.87 -0.12 0.12 0.80 0.202 IBH 0.18 0.95 -0.12 0.01 0.94 0.055 Ocupados 0.13 -0.02 -0.96 0.01 0.94 0.055 Desocupados -0.13 0.02 0.96 -0.01 0.94 0.055 Subocupados -0.42 -0.18 -0.10 -0.79 0.85 0.152 OcupadosPlenos 0.43 0.18 -0.02 0.79 0.85 0.154 PobrezaTotal -0.53 -0.51 -0.10 0.59 0.91 0.094 PobrezaExtrema -0.18 -0.60 -0.17 0.48 0.64 0.355 PobrezaNoExtrema -0.73 -0.10 0.08 0.35 0.67 0.330 RC1 RC2 RC3 RC4 SS loadings 10.64 8.41 2.73 2.43 Proportion Var 0.37 0.29 0.09 0.08 Cumulative Var 0.37 0.66 0.75 0.83 Proportion Explained 0.44 0.35 0.11 0.10 Cumulative Proportion 0.44 0.79 0.90 1.00 Test of the hypothesis that 4 components are sufficient. The degrees of freedom for the null model are 406 and the objective function was 255.53 The degrees of freedom for the model are 296 and the objective function was NaN The total number of observations was 22 with MLE Chi Square = NaN with prob < NaN Fit based upon off diagonal values = 0.99> fs <- factor.scores(y,fit) Warning messages: 1: In cor.smooth(r) : Matrix was not positive definite, smoothing was done 2: In factor.scores(y, fit) : The tenBerge based scoring could not invert the correlation matrix, regression scores found instead > fs $scores RC1 RC2 RC3 RC4 GTM 0.79717198 2.16933999 1.33619964 -0.8079013 PRO 0.55254043 0.72640602 -0.46967717 -1.1187535 SAC -1.13379575 2.13291417 -0.43963192 0.9229644 CHM -0.99727384 0.65754184 -0.73101845 0.1651311 ESC 1.38132389 0.63162688 2.11386095 0.3599889 SRO 1.33884348 -0.30053901 0.53745640 -0.3608614 SOL -1.45251834 0.06878949 -0.73745584 1.5265973 TOT -1.10617858 -0.75575521 1.50273893 0.1448349 QUT -0.85936217 0.99748623 0.59698233 -0.2234406 SUC -0.29263716 0.16349919 -0.06930186 2.1019490 RET -0.09838073 0.02295733 0.97549518 0.4521984 SMA -0.95092072 -0.22801954 -0.49517355 -1.0141602 HUE -0.97321252 -0.32821828 -0.50031620 -1.9962687 QUI -0.93154796 -0.85239189 -0.45421820 -0.7237083 BVP -0.33831892 -0.29283750 -0.09255040 -1.0378031 AVP -0.51096781 -2.26216926 1.98999776 0.5967670 PET 0.44381944 -1.21369317 -0.66218707 -0.4686699 IZA 0.97465580 -0.14076047 -0.37991360 -0.2601170 ZAC 1.52316895 0.20667123 -1.15815406 0.9600856 CHQ 1.67497142 -0.86269875 -0.97242617 0.6252796 JAL 0.27357770 -0.57176919 -1.12778956 1.1619031 JUT 0.68504141 0.03161988 -0.76291711 -1.0060152 $weights RC1 RC2 RC3 RC4 Delitos 0.023962486 0.062155237 0.1759031824 0.0262661603 Capturas_Delitos -0.017052245 0.057207298 0.1398708749 -0.0005961493 Armas_robadas 0.071372384 -0.023487078 -0.0231841333 0.0621967034 Homicidios 0.209730064 -0.060997850 -0.0120530243 0.0056512662 OtrasMuertes 0.063358882 0.007730604 0.0606798493 0.0248508945 HArmaFuego_M 0.060344353 -0.074196297 0.0002771604 -0.0311956442 HArmaFuego_F 0.071128734 -0.030727376 0.0050140961 -0.0345118866 HNoArmaFuegoM 0.091229495 -0.061669441 -0.0016625501 0.0741530256 HNoArmaFuegoF 0.073512096 -0.035278985 -0.0175051747 0.0661982991 OtrasMuertesT 0.119102361 0.039251400 0.0600410575 0.0318803201 OtrasMuertesH 0.043827658 -0.023378153 0.0460339830 0.0272615158 OtrasMuertesM 0.057287921 0.031073108 0.0173280659 0.0170787192 DensidadPoblaci\363n -0.111412185 0.065812363 0.0271240291 0.1851101654 Etnicidad -0.082184484 -0.014150834 0.0449729547 0.0078937376 Juventud -0.016403664 -0.084787789 -0.0001767532 -0.0143519832 Escolaridad -0.032828394 0.108936338 0.0105032794 -0.0299174070 Alfabetismo 0.016151054 0.089458542 -0.0420163850 0.0027734462 Urbanidad -0.090265745 0.150088506 0.0319428264 0.0834279026 IH -0.006718757 0.070195295 -0.0915173937 -0.0597430657 ICV -0.048987107 0.076217167 -0.0504283936 0.0113677792 ISP -0.103995035 0.103372006 -0.1211655731 0.0474722036 IBH -0.057661468 0.317302019 -0.1229054445 0.0015928905 Ocupados -0.008276851 0.052290374 -0.3687019848 0.0243689978 Desocupados 0.005322704 -0.049932468 0.3878039388 -0.0230131309 Subocupados -0.020167735 0.011095536 -0.0243611441 -0.3170622573 OcupadosPlenos 0.008796397 0.007072696 -0.0291510017 0.3278156828 PobrezaTotal -0.052508716 -0.049473654 -0.0188035423 0.2903041779 PobrezaExtrema 0.007804023 -0.060656054 -0.0540103568 0.1999980375 PobrezaNoExtrema -0.096009142 0.046653250 -0.0027090029 0.1633264888 $r.scores RC1 RC2 RC3 RC4 RC1 1.000000e+00 5.368054e-16 -1.149851e-15 1.528874e-15 RC2 5.098952e-16 1.000000e+00 -9.809461e-16 6.570265e-16 RC3 -1.180173e-15 -9.082821e-16 1.000000e+00 -1.942916e-16 RC4 1.335707e-15 6.256914e-16 -2.308661e-16 1.000000e+00 $R2 RC1 RC2 RC3 RC4 1 1 1 1 > postscript(file="/var/wessaorg/rcomp/tmp/13r4z1396551687.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > fa.diagram(fit) > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2ms151396551687.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(fs$scores,pch=20) > text(fs$scores,labels=rownames(y),pos=3) > dev.off() null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Rotated Factor Loadings',par1+1,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variables',1,TRUE) > for (i in 1:par1) { + a<-table.element(a,paste('Factor',i,sep=''),1,TRUE) + } > a<-table.row.end(a) > for (j in 1:length(fit$loadings[,1])) { + a<-table.row.start(a) + a<-table.element(a,rownames(fit$loadings)[j],header=TRUE) + for (i in 1:par1) { + a<-table.element(a,round(fit$loadings[j,i],3)) + } + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/33eo61396551687.tab") > > try(system("convert tmp/13r4z1396551687.ps tmp/13r4z1396551687.png",intern=TRUE)) character(0) > try(system("convert tmp/2ms151396551687.ps tmp/2ms151396551687.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.856 0.785 3.651