This message is in MIME format. The first part should be readable text, while the remaining parts are likely unreadable without MIME-aware tools. Send mail to mime@docserver.cac.washington.edu for more info. --1133331701-635408861-993124011=:10449 Content-Type: TEXT/PLAIN; charset=US-ASCII I'm not sure if the warning messages Warning messages: 1: variable 67 is not a factor in: model.frame.default(Terms, newdata, na.action = act, xlev = attr(object, 2: variable 70 is not a factor in: model.frame.default(Terms, newdata, na.action = act, xlev = attr(object, 3: variable 71 is not a factor in: model.frame.default(Terms, newdata, na.action = act, xlev = attr(object, reported by model.frame.default (thru predict.rpart) are correct in the following situation: R> library(rpart) R> querschnittMar01 <- read.table("querschnittMar01.csv", header=T, sep=";") R> y <- querschnittMar01$diagnose R> design <- querschnittMar01[, c("msd","ag","at","myas","an","ai","eag","eat", "eas","ean","eai","abrg","abrt","abrs","abrn","abri","hic","mhcg", "mhct","mhcs","mhcn","mhci","phcg","phct","phcs","phcn","phci", "hvc","vbsg","vbst","vbss","vbsn","vbsi","vasg","vast","vass", "vasn","vasi","vbrg","vbrt","vbrs","vbrn","vbri","varg","vart", "vars","varn","vari","mdg","mdt","mds","mdn","mdi","tmg","tmt", "tms","tmn","tmi","mr","rnf","mdic","emd","mv", "rh","alfah","alfav","sex","patalter","flimmer","familie", "blutdruck","groesse","gewicht","bmi")] R> tree <- rpart(y ~ ., data=design) R> predict.rpart(tree, design) where "sex", "blutdruck" and "familie" are factors. The warnings are given from the following lines in model.frame.default: if(length(xlev) > 0) { for(nm in names(xlev)) if(!is.null(xl <- xlev[[nm]])) { xi <- data[[nm]] if(is.null(nxl <- levels(xi))) warning(paste("variable", nm, "is not a factor")) where Browse[1]> xlev $"67" [1] "M" "W" <- variable "sex" $"70" [1] "Ja" "Nein" <- variable "familie" $"71" [1] "Hypertonie" "Hypotonie" "Normal" <- variable "blutdruck" Browse[1]> nm [1] "67" and Browse[1]> data[[nm]] NULL BUT Browse[1]> data[,67] [1] W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W [38] W W W W W W W W W W W W W W W W W W M M M M M M M M M M M M M M M M M M M [75] M M M M M M M M M M M M M M M M M M W W W W W W W W W W W W W W W W W W W [112] W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W W M [149] M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M M Levels: M W works as expected. The data is attached as querschnittMar01.csv.gz Torsten --1133331701-635408861-993124011=:10449 Content-Type: APPLICATION/x-gunzip; name="querschnittMar01.csv.gz" Content-Transfer-Encoding: BASE64 Content-ID: <Pine.LNX.4.21.0106211346510.10449@artemis.imbe.med.uni-erlangen.de> Content-Description: Content-Disposition: attachment; filename="querschnittMar01.csv.gz" H4sICPqzMTsAA3F1ZXJzY2huaXR0TWFyMDEuY3N2AJW9y7IrR5IdOtdXwM4c 2+KdmYaRRrp2TdUDTTQ+XcVm0VRklRXZvOr79crwx1oeiQTbVN0G4mBjYyPT w1/Ll7t/+/7vP/76w0+/fXt9+/nXv5yP33+cD/Lv//j+63z+y3z46Xz4QX72 g/zwB/nZD/LDH+Sn3//1nz/qf37T//yq//lF/zPf8tef/jw/969//lH/85v+ 51f9zy/6n/nGf+hb/qFv+Ye+5R/6ln/oW/76+/ys3//11x/1P7/pf37V//yi /5lv/P27vuW7vuW7vuW7vuW7vkW/+u/61X/Xr/67fvXf9av//l3f8l3f8l3f 8l3f8l3e8vNf5LL+Ilf1F7mov8g1/WX+9Leff5TH3+TxV3n8RR7ld/95Pvzz l387H//8t/Mr/va/9VPkhv3w8xTMz7/PH/7v+fAf8+H/n7/x13lz//Zv3/2/ 8z2//jDf9I/vv33/228/zM/9t7/99PPP+uz7zz/97acfzmf/+rd//+0v//z3 P/+v8/mP//z7D7/+Ol/98Yf/76c//3X+6X+Vr/WXn77/+Mvfzx/9l2/l/Od/ //Z61PyV86t8lfJKX7WfD30/H8YxH9Irf5Vt/qD5T8uYz+r50Hb/5/kB6SvN h5xej/PFPB+zPDZ5TE1eSa/n+bzMxyyvlCavdHlPttfPPzw/qyb9wPMn88uk gmfzb6bkfzNV/HR+1dTwT7xlG/6s4JPLfN82nw151vSC5dKf+GbyXUudj12/ 3/yovdmlffv2sq8sH5fkl4q8Uf+cvLEXudbXM3/tr2//89vrvKf5qx2vb//y w0/z0PzL3//58/e/fXvlUV+P876e70tj5O317Rf9yX/5VocLbPva9lNgIqE2 r3hMQexDn52fO79J6/5Q5GG++UgQ4nxLnr+W6/xqVQW2yVXJK/mQx2ZXMi9c LqLKT9Mur1d7/bzC+T26fGrBR3cXWKbARC67C1FvWsdru79FpKEnakq3ztfK vDh5TY7HcczDWfSqn/Ltny6BvNs3e9p5OKp9eRFYkRuxQWDnd3nYKa56D86r L1/nOdhPqU2BnXctz6/y7f/9forh//mPf/z9t7//MhUvnyfoMfpUoHbk822U WC67iayNqSf9awy9glNGZcq4zmf51eY/z+/Y5t+YKpcPfah6PkW0+rDpWx5y d1U0DxdEirrUwg3IfG4auLnmHvNZxj9Fr0VFVJWoY92fjQ4hiwQrFAA6Jr+r 0hc7cbjKteHmpfZw3xO1P8mxS/MmVFGd84Vv/+1v3//9z3//+fs3fNeiX0kV 9GFnphQ7mqfozsvvX0lFN2/mFMybrp0/OL/qeZPbqCPqWpnG8X+cgit5qnr+ Ona3gV3ugRx5MY4J15b8HojCiWLKnVTj2Ggc9XLl0uugsOwGyFXlbmZUb8nT NU5uah/+N1VfjlWHGgRHhcv4aV1fK/551DXaBvUBDc92NZjUr0TjWN1cnodU LrDuZhxhg8xcVDux8urUtfM3x9f5av3qIrA2b+x5d6FrP/zTle38qo/TRp/y Hb2d6kORjWQiq6feTg3b5O9OKYif6vBYYjz0dBa/Xy370Qq+JanwYOhM1zaK Y9G1cEuye7in3Um1NdChIJ4GXaMrq6vqpfeHClnKhejVdJy4DRfXVS+esBfy nZo819fl+GzdTqaITL+A2WJcSDEL/ZBrUn+2fQ0V2bzj58F517HznWOGF3mc 5jAHgXWzjWVTm6fy2iEv+K9t9+sqiAAKrxXH2COAh39tlZddZQlS200uDziN I0hNvkJ1bQjRBO3gJ9sYtCstb+n4lmoq8fHiMnmtckrPQ474Q299rSYA/34q r2rxh4jKhU5Rj5e79NNYnDZRfmdTeVW94+/yOm3oqVf1lFcZ5x8M3qy5TaxT ZU8tKy4ria4kuNi26Qhh6sV2dImpxKKLgxVvADtZk9mAB2IREYyqloaQZunF NehNMCUcOMBygw/YXI0XEiwPbSLFNJ+JlRaRZBhQiTj7Gn+owOabj/lsl5Bi /saR9dJVtR5wYIXHSo7Hoea+qcA0fG4v2ES/TL8T5/d6njdSnqrAZvzR7wS2 WfhR6xkxRoFVV7D6JS5wl0Aqv6IbbjDzpeJmyTE9oGAVR9wMFtWpBRXa7EIu CobnOJdyu+UU0DMGAdUbBYMwru4LWiYXovIqbimyKZPd6rH5T5t8y5qCgsn3 a6p4XY/0Q9y5KtjACSkW4HvQYZ66TPcljkwD/LaZD7tTsDPIPz1YSn1mAFQw eLA6v2bR8yaaItG1fH95tlN7cLoLjIvePPqQ6LtiAOKHlo68hBztYCJToOgZ DvMisLymW4kOCJnhxSJu8H7ZzICdN/lDmsIkv66+B/unzkiPm3xLca672o5i Aus4uTUIbLxCwvNsX/pRFNjpqd4EJvH9DDnSdrqwGN8fNIjHVM/jcAUTMy65 ZO+es2gaDdmICZCIUlQtnPjDo9hkwa2ZvKh4gxk0lIrRB5PzhI/m51/+mf18 B1WDfeRbBl7TsF/0V06knI7Dr1p+2mtIyPwMPUXrn3bBFiSagonNLTyuQcH0 tGpaps5M5SXJYLMgcZHWPs3h0XI+lZjSas3z5zL/bFEf33BtmzksD/YlCBHX heMvGliQMSULlB8eyWrwUQ4CHikHb9Atr2as7wmb/bmGU6uKPKBZn+JACQYS 41aIsENwGSmdfOgm4Z5oTPfr2tQeFtrxcoSwQ2L6PQYc8meLhUc4iXrMow+X D1FxHZosXcQl4aF4r1RPexitYTXtymNGGsXEML/zMATG4I5NflD9oZraWeAo +ignLieKKwdx9UVQjOfT1bmZi5P4+3D7pJlwgbjopahdMI6KgwzoGfOPYxUX bKoczYFDqtBcpUs1S5AoQBHXoaHvFlMwc51PDwrlGxXHRc5wY5/4lKZgktue JvFOXNN5lVpyi+lX3lxch2pXhVTEA2/mxrJCHWr9RD7Fb+cGc5+BH+QgIg2S ygjaddjjE8KsfJ54KCtULOEkhGcXOBHRRuFP+/JQmT0S3tr9yAl2Jadylwc1 gDFvrsybJdveh53Kb4Q4GM6nIK7NvNyzf0mIqBBHzwqF3aZfm+TLe8o9RhvV w/km+ZeF82I2QjgvdhLxlagggeHD4lXP2DZVUA1fH8kAwzwIdyioaGH7xtdT RIDMT+YQ1xCWKpfgJi8PO2xi6biRTPcThIg4ad9dTHLBGtg7Sg0/bD7Wkw4P 57PBiRKjyVk3dSyAOBRMnblc+5rKY9FGn/BfuhPY+f5tGsS9lL0u4eHuGrbP 71/0/Gl4KG5KnslBGH5EG6IqMYNyMBVVP8LZpRHcg4Z1uwbiU0fQsIBJyQ2R wKYiRswAHxSdosBWTEq/x443wyBWxpf0t4fr1UZMSv6ZqVUpPAcK7OFGsfwr A5E0gzggMM1Hp4adUfj8mcbzfSbMp/V9Dw/P+3SI/tR9WwKODBCxfEn6pnmW 6IscmAMPBUcU4Ve58fb+gMjXEv1wOu0xIgiZz4tnL3QH78FFhtTS8o2uuMZH RIoPq4PUoOZ4AWmp4dsPi+Sf5kO3akCTxvPEWfwSPJMEBveQhHmi9iKwtibM C4x4mi81i1ttdYthR0meNfcvAUlEQKpRqLdosAakLeNMh1yZKavd1GdaUrEl DtzDjQhJmN2mgpvCdO8quQtkX1ahfQofG2EpXs3qMCsw5RKTMPn2zb2tH6px mDEJMOJBoXkYDFtyCm1GHOdDodDqe9jhJZZej3RqfAjqPUosx0w6ioZKYool WN/NY+VZXHERWoZiyRnxoso0LVveheqE1vFyrGI2hlIR6khejDLfKPmRakLF jb4A9YQv88uBVqZpUJtCoHHg1gKZH0hWNJ9pwRCmECseZsA9SsxbKIq5f2XQ 214edmjOvakrg7jKu7i6aVffch7RJPbsOVidrraYs68uEI1xNz0ELhXU/zRX Q601I47WsEItt5ryGkOPw3z10/2ZZjfm2xIyTT30MFx6exv+ecEQ6cMoqTUH qzSYYvTgDreKh81tSt+CigTMrBDj3PMSJbJ+WmlBNWVuljKfL4wZJW4UV7rz YecHC3I7ai17DDqGVzCrxOdnWAKnJXi9BI2bZAQW/UX6QIfXq1QH8+7I6VMs dWW+Akd+waSyV5Es+DmAIRXgL44kpNsosdMPba6MCkAgC2NykJOLaTB97i93 UBYlJloHpCMeJZYaQV/LD5lybi/nSEx7UxWTysEc5pui86yD9UkCqHs9E+cg sR0oYp8aUfVq5bvvM1uWO3U+q3paNX7aIErgWIqbdjdgGtFXrzbr1QLUMMvn juoBZxblZmFotkwG5TmJ8LV4fEER8TAQ12dSDEBGCRELSASSTG7ZH8QZbBG0 Dg4ZOFX2NMWiDjHENcAcLF0qDWKe2volHxuijnxfa36c+ddp8UbfzncFgZmG 5TGvoVhsWCA0seoZ8b6EHiI5eDD9Ae5iNlrOw/UsOzSK54YuOqJIRKQFZBh/ rsMGEpsKJcaLvJheMGcGy6MyHKFJ3PwciuXoLDq3EBxFIgod035EnENPUkic O95oibO+PUSJ8/61D1HiNmthEiWmlkeUWUFtpU1bU6xumf0aNsM9ssWL4N1o Lo0UJgOkzVbCQ/5lYccRYkU/fU+EJgcNpUVnYGg08qGORW9CtfISdhD8YJET uR35Vcwdd1Cm5IIPS7SYehzBj1VDQQR4DGZR78FOs8jTp1epqlbVmUFoobby Ftrv0+7l0tNiGTfiv10YVodrt6LX4tl2pfl4HCjfgnUzQgnMdtxiINJY8ued l2SEt8DyMMMoGSHKwokYIePnT/XLkF0zxmf+TEWDCmtVYvcHOZrDMfeLtFBU EGArygzl1RSiTM9bzdhY/myA4lgVjbHHRyVrhbGHgI4JuZcCHmsoEohIRIFY 2eU96lQvAzwcxniEn0JgllG7/fFgUWwwgb+QbLEeRlnxKxD8XZO3zmgT5Vg5 iDvjLJCQhlZTKpVMQ9pgBHYPKTQVAxL2HizKG6tkYaZpdwJbaTi7oFRnDJFa LTHC35zW0Y/5LasBh02tRVYB7QIQ01oWP5ctuwNUAP/AWW1LmnUNubrBjRHz od4Ne91ZivBkgUAy/LVrOg3ClbyvgPyWdvwGBYm0TosVyc+m01n5zY6g/87W yKS0BVqplRaecAkGkxt4Omkdz+4J2fhUxJwp2YwXexvHAivu2WHFNr9JmQfH WW6WI0o05XWW3e+H5mW8OjoOfkETj0OMMV6keDqjyRy4OqK2kskXBOihtL0v fy5QB+j3bohwHc4vd7+5GQFXYyBlNhnfL0VAZocVOHoEPDJrPA66+RstLc2z xHLMlCxo2VTSSwadzYmlfdQUWVO7o8BFFKrqtam2yBeyAoTB9syqN1SjGyou ml8bvRshoonLS2FEgQNB085spbgSvOmOu1BITACx9wo0il/tuHkNGonPI3mR XmyjVSmwIFvQpk4EI3fYumO3S8OtdkfP4hjqEgjy92kaz8tuxsVR03ijZRP4 GPPe1562heyWXcuG/IGsVl1Lldk1qoHIpLUv8CzUIyAbDcFBXhLJh5uXxchU 2g5UW2JuxhQnXeN41vuv5LeP3A4Jden4yBrBNahrO/AQ8F+zc0ooHbAC22ZO WX0ZNXyzmPJBk60e+5RVIqFUEaU7gZ33qU+jl46+LWz73cH7XOepKYG1JMom iJtUcTqgI3FcGiha0manawG+GSEejPCXimU4hmZqIh63+edXeKAAO9/p2aX8 TMuJJKBRH3fIxVB4T6OB4IxIgUpMyIpH/k7G8eCDBbkU7Wd7ed2pSimzzYdB gX2M8JtUXOpptEYpEQ3uLrRJ8WDEKPGEfHPAGfvmX4mldooqcEoTtSwUnjWb XMgdHiUiEEEp0EN8jTuoR5Ghld6K0LR8n7RsMAc5/OsXWBSN84E9K8FNWfcG 3mcax0J4sfY3BlVjRuAUBc2lhaJ4OjQrQu8WfLyjVedt6Zv4pNraQgIGKWeo 15LoQwyhRB+7waXZ+llQPMtgbQ847UzOZicGlRw1RcC1SOwgGpRjUCYJvXx0 WzQ4VP1XDhW5cZkGijIGzpZQAKgIyhW1H240mgHitIuBr10cWUP0ccSkLEjM QblkLA91ZOkisXxHUvxIG+jDVUy+ZjFHiVRMSYoTStMgcbiharAzB2stqJmp HdB8P40gsEpLmRKNR47QUBAYmG+ZFQLQPm9pOSi4BMwf+liohSz0CZSIUvQO nrPCVVZzCEesFsjBkjJzZAQWFhaVvWp+oirykYPAxrvAZkKmfRGnho2oYRUI /qZ9fqRWDiO6SoSYjW4K95VRwhCOhJoXwOIaHprrbfZlGXhFHlWgDeQjPDL4 gdIUgkxkwVFWSMgqYwuGLqDHqoY1/9ISQgimvQ0HwJXsMewQ8XDFDo/j5bQ3 pwEXJP4ppgYGyZoz719ywVpyGcLH6G/xffNAcTt6XUgD2VmlLc+/7ixgIG1q KrJfUgEcop4AJVsGWIE1kAqlkyO1I3BIi+dsjB03OPbG6tid04p/LsU4lXq0 xiaNcSTw0Axcihicx5EIM3LAnawkLaxAsAYY4CdkF3pRxdtCPCqeNnaCVfOy KbVJ7rm1i5OM2HtOJS3kbScOZNGkbGZOTszhImOXgkLCiAgKGESBUUBPBqP3 AKbvbQaI8w1e3IM/awgYNRBgVszwDwjxlQ18wYoZgBT/qvyAgqipscIu8t31 NXgyCxI1PfZeHcCLbZHb4YchhVAlkG6rd/o5DW6UGIGsDG4h1Ldey8KpyqH6 0iThhpgkxTyGm42Gpr6GMr6YUvbTBjhihIQ526U98cpKAlT58nUHYO1mFqLA lAZcXIg/qJWf2DoHmCMFaXch+iF/ErW5Fmsth8nrGb6rp9OzqTZITb6anSBG IYaWKsigXDiHhkVqd60tExqW2nIbW++LtlWPG0tR9iIpOR0E55FQgCFFLanc Mvys3QJ3dw/IpATN6wxMcghMAKMyVMl+GirNDnrWQ2TIzIx0U3Zv0HKK76WV JP4oHkHSs7V01mOrTcitS4X67JtdSJBb5jEO2H+yV82DC9joMIjIrb5r22zR PGSgwNZrDEWGA/rlmL9nZIJuZBVrrVKyDqjpDQZUUBc6w4oAr8YCpvcx0rG7 MOmvI+pKSqceHnKhEBNqiHHHrSL7g5KDbBqzkeEapyV3ZDI7WrCaR7I0G8El y6ccjqKGnJpkndBBVrzlT1BGxI4S491yhLtz8Pet5wW1KgCHdwU7dkRfWoNO /kyDEdAqeZoqiLgBLHduKcyjyaEs6kQZeqAWH1Ogq4WWJAYZn6L9W/5cgogY jCCGqSBpLqfu6WWXHHBGtXfV0j312tE8sknAo5mHHR0VoSXXM1MblNtd5Uzk JsXnVPe+LXJrdGtlWtADnDfVNKGydE/f5NSzq3xsmmWYaFmVbLEmnQ25IXqV qF3FSXPX4DK51VJKB7m98peI8VNuLCnQlvblp4O9f5tLS26xtp+id845BjhX OfFElaBpm8VZESUmP+jKZdT7MYnvRt45/hO5zVxtk+C/7gs97nBaQU7WAQga puJX1hidA6OgolFTcwQ4OXIrLIZ0sJ7xhjOp+DxQ5XLkGSN5b6SBsG7G2hfj DSZidxRvBFPMGzhIRpsoDj+suxHlYkTLb+ZJN0DHbfFqaAFaOl/yCyl2n3CI ODhTN+cNv2dsAlCdJrLWpS+6YzBL/xK5yhfuICBpJ4WIExU09WjG1cyahDcg zBKpdO9AfcAMxscjPIYsPPXlFTsa/WKEQXsLIevq1hpQL5UuChKZNpMZYHY9 6+hWdRBS3evlzBXH4RzDSiMQ8wsz7FKpZoPATyGpUUaqhFztfVzENHNjS0db IsiMfK1PBanWLSwFLGRpexZSJMQJqotEKaGGJscslIy8n4DX7dgOsgDTtcDJ zY5BeOkY2H4B3yLD1l0LackPDpvYqZgspAVOPkBkUngUIQ8BkmWSscGiKYVP Y65oIlGrXQJio47DHdRZrraQZLPq55uJnNqm9/7YjnUKAUKSQ2lxFVAqo2Ht EESFl0MxyqViHB+eaQlJYk6WcrA7hQHLQtDHQQj5M6MMwMYB3v/Puyo2+sbq X7+AulCA+GZzn/RMB5+HvsDdY8MYkjApKTyMYZrGdHAzGmHGtut4nquNPN+3 D0miczrW1vZMbavCNE6uVAP1mLHaSK2zGeJvwyNChZ6hf/W87OG45DI8InSb LTOTHKJ1z7njtgKWCVNibsrW9VIwYr628vQzUvYBavRA6jMcE2AgFfM1sZEg fsdJSH4H0hpKMo9VuQ+lqE65CY1jtGgrOcYqm4PrNY1jae0scHDlS6haGpZs kJFci/hNxCENN0hNWfMvnBExLBCyP6eyBW5B9pb4p9+cHDD/5uciswxzh/mv wgtd92t9uzJyQYhK1v6wSpmZyjGYYCefHoFH+eN3YYlGk8YWWtM8M5XqHOaA ncqwZHbG3GYBRQj4W81R6Q6vhh5tyqlZcJUU+8jzeAjjqBpF2voabaaacLR2 k6yY1WyTVrxjGB4Ow+CQaC/1jB7sqL+etMOzVL8ZDYe5XMhxq+wOJNSVR6pD VZnfQecUHiEoJN58TbdxDdlT7+yl3IvOadxtfhluPdPzT0kek+GTveliKOXm vpR9GFbSct/3WMouGI/Utf4pqlXQQtAIWbCRASBkYT78dv4hhth4gdAD7iyW AQxA8tfNcAU3d4kJP3XKfHRzHcXSS8tumJIBOE0njZVAFVFXXb0B0vvQqhVG QzYfpjl6cKupnkxmxHjGfijWdNP+/gn+72Fi3IF+GMSUQgNUtj5bVdbQLrAR mQJH5pUP1bwiJVuQV2i7KA3yUvNItPGClHyE/z9JrpGUfPg1qLxwLNmHU+O3 qTxnFq5YqKa++61sYzb86cBIZNHkCf+foUhzMr/13HxkjXwIKQtwyTrNQ0Vi JvyDhbMqtiS/nHws7rzreMElHyenLgfaiGWfq0yRlaLPU1/xs1yRL178UcAl V+AqsPlRACcNOXB9qGuIxpqdU0/3I4kl8bTZKRxsmVnTbmSeC/usvxynLVln TQjtByW3W06ddzrl1PZ1QoibyCEWIBvhCpU0LUWZuU+RhwjcsLCVJRKiiPWH GkBy0BwgnSlkHPTi3Wp+9ST6RDZRirUbSvETLpkYLbD4g6ookwCmOXlb7jrz gWSP4hbNv11adSOnziZmAP0X52YDUedvHHcT/4qRfc6Q8ijrPFSXWBV8sao3 V5rxroVySbyrGpNhcYh1OA3RwOqHVKQt7E+bOVEppRJ5kYHzk712SkXzarJV hRpwSNWE/DKnf2UT21HJgU1cmRSgE/FSZBWdPWzmhNWgpNixH0G5vB+NSI4U pD0tXSMSMQ92fpj6pJf37JWOVoxM53YbSlY3kVsp+8KGDMMam8hHIkGBSJJf x5589p9PMfRnHEqM/MAbphBKWineqYF4BQk4fV8ceYuoaEO1uLDmcqnKMkuT wKm5QJjDZcCnBCY5VG1DGrADp9zDMUrO5Gf6lvWEqCNQEgn8ZArogSaUgPzy Mt2l3Kbbs9Am5dHaxxhLxtZ9uEuu8+9V/aMKbjU/s8IuKWjzHAjEFAJtfoTJ 3GpOX0LGliPS468TJAmKhoHE5h0HgV9WAtgseBM9aocByqgEt25NI9hA2l0d O0miF+NJ8mEZ2S9tXAYPw7EnD8Hg05yrK/NQZZISfFr6NBT1foxSc/pPFvS4 2eHe9Wvlqe5Zx79IDafvfhgPQ+6yZnMN3RNqwqrFuXBeJbizZY6jD6whdMLm LhGB1JJ4Nzhg6xqLQN06GV2EAFDYTagmkA+4sW8B0bPl2jH+DTmAwJLZpwxd YUnHPym3jXelaFPGQ6L/P03Y+HU/MHprlmuntu1lqbg1n39Vjy/BwGr3Y7db 233SkQdsv9CGcnGBuwZSdksLLKQNXvCvDBAVSSvP7xYQlMEzTr5ch49ne0G+ pAOrxhVA/5chWD661D8FAu1oHR+oO3TvvwLQkWN3aFf/8Rb/qwUvlFuYMVcM I3m2L/nwTeRWPlXcNs/bylbaUgaoQJP7PNymPAW4Uke40UCvZj9EoAdcujQD Rw1NoXgFw2ueAHpCTdF6+MAZCx+9VrRzzBKX911UEEHLDlqJTtUCIr41P447 glA1lDU01dUwVL8aqveQ20PGeAlpdqAk+LDHp5RI66y1/cmG6u83/ONjJmvS LX8caemWr5jPM9SBhTlz1ipiAUdGSqbBMQCmgJVcKP6xSaaGmY0LGbISSDbL 49rmjYJMuigNEkRuim13slKB4X0FbFzFgEDGVLZz1n8+A/LIg+bDoHzOHHAR 3oj4q5afPDywzsoaF4Htn6ha5zt3qX22tOexaFjgkLQZwnPAkOLfduNyANca 9EwhLhxZTmKxuWWBntXCyNQU1EqtZA21foyr8N5FJFNh5gvFRplQnndNUML5 gHoWQoWb/2CwimhYLJIyy7tEBNUxADkBmttcZ+kXijaRQT+BzTGD/TlQf0pM ZljdSWxWgg6ZmNSPtuAhhXhIn4Lx1TBooB0HdAxFqQbYkSV3Qv2uA4w4Rogy akhT3a8/YD7jagvgvpn+iEEHsUeq0hqIXBVNDhcsqJpz5BGKs0rcW/zEtjB9 LPJaoHu+GgaToy86lr1V2XVMSzUiRzWKzQL0ey+mOdZRl2a1DU2hXWPDBvKO nLjdzp43ZbCVpuo/fSbL5valdBypEvCNEkIwGEt15Qz3Iztj868wWKBhzA9M 6hp8IEtQcVIz0cCVADmygeuwptBs/5TwqvE7GaUgmm7Jgw6LjZmetQSBJY+Q nf5UZbVInbF+VoF9GvV9xuU5Cam4l5aXsMOjxVK1siJFCuWmIneWZ8Ii11AQ Tr7iOBYkPYF2XMLsK53Dm99tomfeEWjwGxLGEXJaAe3fJT+r60+pZngLyeIZ yCQRx9ACsqkhefpBM2ZWZ/BRrL1Zw79vpIkPCCw2qsk9aCIwn6X/J5tFfNcl /3ksYK4YR1x0iJFiiiIOMYyiSZtjIeyWYanvSu+3Zw9XNOw3wPPYRpNaUMYW bKIEBhIrM+5gWfNj3zVoIEFseAiDsFBgCwiI+C6xdeLyNL6IPaCHhYhPM6Vb jjaR64ZS7Moz9PYhZ1vm2z6ySUzHmt5NLvtoE0FdRS8oww7A+3IAD3COyFVV Qh3BYpQ6lrZcDSziKgqH/J9pxRrjlBTQtQtMGudHp4vPvKDId+G9JJCI7DOa kDPi4WbNT8Y43t731WRqTjGP8UiX/WYWGiGi8pFpGno99xjZawfgG4tu1sIl rq99P/ZlohI4BvsUQzXGptSkmxO/jwlOir3wseUe8GsP98uzNnEEViZlHPtp MmCI9E37ctAyi25ybE4CLbNcpoCQSkNMEuG7eirklqy9qTdE+qXr3HboV5zE 65wqZCulKLpguIdAwpISBUjYKxoOCc9hL7LdLFFcS+VsjeuTzNUspUWLuINi vE1tyYpCVTDfu0kjh30BBUSmCgkVBAaK5fluM1wspm0QuwmDVHKEOshV1UyJ 8SGBRTZ4XiBGkH6udZiGj0Lkz65D3d+T3Kp4p8LTU8TUgln0uAnrRVLUL/sq SLG9PPdIVn0ZCuSLwKbU7/YtnbqdhdPRxp6OqGHDBdbHNNZdxXRsii1n7XI6 jVkzJuSh/IysMf/5uc0CrPU39AuObpgijaC8MkIkDyohsKzGZXSHVIzkaCDx HbDJ12Zqk4utx5PtNrJDagCDCg4tOj4LdGUSYrICrwRZTxy3FI6Vk2mzwQHV BFZB37UTyZbC7gf1X/4rEUUd5Hjnv5Jh+L30oy+Tbb3RuhSdvNlRzlT7YLlz CcmKMg3Sy9hYSp6AWlbrq1QEAEBwNIg5ELCsn9DLhBRg82sfVos3oxY6Ttdi J5+VS2CCiCXMBURxNpOQivrEsKtm+BNqfKHKfCzTr0IfaaOklTFbzNGdGfOU haXNPlfxXWDVAo5a930sg5RYJJPZmsWYtxtuF54dyS2ipsjwJA18KHLlcwTq Y2t8ZDeGjAy1X94jkE3CuhAWpfnaBZqiM7sk1dVVIEFOGoAfENHuF+wbZWN8 8XTVD10U63BbusXYjeZbYjSWfByTslNcxabE7jaa7S6xdKSyjL4qYO63WfME Ec46ZMzjHzKWAidQgw5pC91RbOGwCEMUHg7dA5aH237vN88O1BNUACqlw5TA ZM6oEXwsazawnQIVkpaUuDUIVQO9gzqCQi4uTmgPK9dKGFZ2mHtWHQNwngJx XGsaviJHKB9n5GE+bLw+jNQv1iBTRtuWXov9CG2fAjeiyKwsgvayOcVa0d9e TjIWuZiHS5GuY+Gy5onMwtZdbowGDxMnlA6T3BxIITsb3XCFKdYlss8vIyiy R7BAOGH6FYSYcJliRHQHXVWLd8XPYl6/vTAuJMelFTtUDHP0HUmdrmI26p5B /U6BtbsOwo/z2Qt2ZLUv7VVjFmbkKcGGss3aBeTGbdSia45H+a1wTgq8WAlz r7KD+YgYF/3jOI4C1kZm9Ec+ziebGIqdK/gYCtEkIB+uXNrCJdclN9m74uG/ DO7woYUOJeYeo8QAJfoyFT+uReZeVW1oEoFtr887EKSYqUzFI9VYhI4tFnlG Wa26CsnG4myM/Ww7R4rbxoLEfkczYSWPwmPBq1kMlP00gll8n/GSXSsqYBSS XhMqIUuQaLcotDuxuRrJYkIWUkAA8m47Zw9Lfha5jKGM17y/OHv460N5kOPE 2VeR/z4mkiipc6XQboeVHT6Up6f9iLmYh4oerO5IUhuoFo3GCS0Kl3wsTLZt L1emEqL5GhlGrnzEpuIWTG+n8coACcOEFBkMUsn4sENKK4bfGBmh3CB3eQcs tcG07IodliA1cWPNW7C8SxezygrkFZKWVCCv1mwaoKOJUgi5xaaGb4ZJvS1o YnO8vsvnVeOVkhYmR03GdVoB3ckC6WWE00F2WoOwuyVVjBR7UK24C9yBYvj1 TKvTMAxIUQtQouoFDV7JAhtzAFDgODNG0+sEgTVn9clZlSxUjm4OuX3ybYYx EgFZwKfqy5XbyaK9KK/EmTyK1yePO2T484dlWdqDdIwtRzc2QFxMOqT92uJp pb9iW1VFTFK+k6iqONGqbi5n54M/JGBGGtZ26pwNK49zOB2viq/HLtMEWJGm +GNxucODhTUIkXS96J84aly1dlbnl2f+KazMMwjHibIed7gbY/Ui+Zqshwms +vKwqaFKgoPA+l0y5otGyt63vMyO9mHfJWncwYV9ZBVJqUgwuop6mZKgBXbM 0IDsFqzE7s4IyMe5ck5K0uD4EihmlLc7wrmM1Ozab7YGisSLL9PIKuWMwTA6 OxquWTc+CpLjQ5CgVSXOVUov7xL0URNhTFkwIXFMmUy9KnRhOnglf4g7/mAU MUa01/nRRgPulh4aUq80UzGYCEs0QBleluGYwGJF2weg3Rh4hC7deICXDJqr tCvSjEwuELo3PtpF9l6EfIysA6gt18j4NDm7uGFxI79NnK7mRSDvyUU+hnQ0 hVEwWgTxznffCa52UeiK/5fDo8vODPq8wU1v0mZ9AXIIDJpjQkbKbWOAyBEO Fo4DgUqJckvvm4ujb9voAHJ3IxisGSNCMZvIhwu+zHXTDwOTrCBgCgNYGfOS /VCgcUrisBWqqnMxys/qZINhJAchitbvh2F0h+pZo8TqzombQcuqyWykkcfa 7gKK6T6TkGIYhgQZtBIJFRXUZ93oxx4mhpA2dsa74ODSUqDopMBsL9GYcK4+ 20oDVZENfhctw0PYqNWXB9rGsMFErAcqY8oLHi/0BcZ8OC/PJdmOtjH5PUhh uUwoZU6cS2YRy1iQP4UZZbeNnIck0a3VJbxPcTV4mrt7MmaCbAegbCEScKQQ CNyd88tgx7zpkqKJi2HCUqNUaBhTKGkgvbaD3yEFjrjN1D/SFMGcagA6wjYN MF+vuAcKtyo3IG4tYDQ5hribqYzz75NnZAN/IiQETiS3yCXrWLlGkU3c48K/ n+3uUpEse1rmJm1YczZmJtwsd04vGw0o1Zs8O80cUjRzmQ0PyqF/euDEAkcj TBXma5ieeRMyPAQIgX4w5aTv4HhU4tAEfC9+DNXLsCcBCVmHYobdxWJNeEjx h1qYcRep3Gh7y54XL+thLBglAmdm5+H07c5wUefJ3fFxzg8+ZMXBuAgspxLi xfn7B3AqTaEtnzDBFNBwGtAIXUwHSMLrIkibzSZGounG11MNsl1pcQ6LwYZx 1dU7izWFUL9AhQLHw1jlKcaL4GFx6E5odQlk7RTbbX1dZZzeSCSYo5IysQBl C1RZhDsmWGU2sVqDy23j5u4lsn20vgyPHuSWVh0DOIj4StRoTs0qg2ow2Ig0 nMLIliSnwCmEAyt4WQNOu+iipb8O6+m6m6sMiDeYxIuiAV68slEP17vKICn5 R+lkAqRzyi01+AO2OpbNUTaDK8tBbF4joFWxyoG+0enbFub31x+0tvvondr3 va7zJA7XttymfagGkhpfJYfRJxKLKHEKgB0BicIbZ/S3eLEPD3qX3T3dch34 9pJoVrS5mYEgO6FJEqXYyCe4MAbWPHvP6zcHB10LEHCFyuQKGVls486+v1ey ILOPoVkaTkLPZXUsJAUYb5+zv4dRuUUr7uplfzB1Mwe5yfqfwxCArPFxMeqq CdS9npNZJHGjHwcFRJf7dA8xaBPfK5yxrSzMuclWyjUWiubX3fW8kSz8Vi/z KnnxN2sdAih9InwttzhrKuPdWMmfRZJejtmIr3fILoi0tpUp6hCsJbsmOkpR fRKEm+dpx+t+kONE9DVP20ZZW9yzVzrzUEPpSwEcvjcOY7akBk2l2mOQoWxw bX4XHx5qXRBHBsNhd1GOXa6JGke2TiTaudA+0RdvnyX/vsHdQaEbzLIEkA6d Ij0G+sg8kiT8dWoSTTpQkUdCwPoQFXxMOtwZnAS5gRO3Zmu7LWBtNZW2TE4q jolsm9I9FPDYXu7imqvgBuOlrcvp5SVJdsKAZls8fmQc4m6NaYDfGVrSGEsm 3MsC9QAkFf7JHBqpd0FlLJhOKF7QueKf0tF90KGq421EaA4bpZIxBjUoXls5 AQ2lMJpaszbfTfg8vmRGQaGry3fYSPL1dWNfdx0PrKYe87JKQKX67oZR58OD RazDI+RBTiqbmBmxhWDSOpXcmSHkN8Ht7rX9OsOmhE7qPGQWIN+LsWRVhlTU VeU2SJn5VQFgphEJ02z1UbE7SZRNF25Vq35o5Bw43vYd6b8NNrM0u35J/dO6 KISbNu4muMjumLzv27YM3i979oFJpc/bVgLZU9kRKFsHyjCyHTa/XGeUxrJz hD5Ct/gCGsdhewSNK3vR2/Xz0+do8iP8P6B5nIyXwTHTB8QmLVDrY7Niu47e r+sMl2v3iw9ACemQLpFJrmjHmgoweZtM1C4rSWof61iJksHOH/PLlND+PFCb 0h2SxXVNAS8RqZDlULEuAJ0N0hrBSK6DPwhgbQxMFnY+4Hnd99r9jJAL/NGL DeJVTC0ZCgNlYSl7NzlY3UmfhUGFi7Xjeq3da9I3o67eHJwlTpYT2TK7fpvG LSHl/Y7PwxO4UnUkuHoBsRSswVcNVb1OU1/emFsdMymrQhaffwd4q/jwjMca RVq86WAR1bLjFohmQa+5nO6qVPhnoBowpgE+Evwh4tJGTEseDKtjFhYjyutC +LyMBM9QNkzZ9qtX/Fk+RAcmlU0T4Js5jl02PvY0Jt7/43ks/tfff5Y+GCxl zbpOZgfZfDO7bQubZEyAWJAOppGAx5m3lpMEfI/zwyPgErQu+f434j/BOgbM VcFjZsjDBRbs5lsK4PDSpeEJMH/IuDGFSYdlNDcUWqcJ09OSzxl+wgOL37jZ fMzOJcsVjJnx8GRw4140CefyJ0LPKbLTSMw1nkWCSIoNQeSpZrKFXCczgi3N rumNOWnxeylnoRrG71HzgB3QNCWHSQVxJ/KyOiHsd8peOE06vImFGE4O83uz eDGo2c7arLiZ/opGMkScZiSz/iHBGLPkUCQcpMrvmgNNVc2qj+cSqXGi1CI1 e1XVTIjfGFEs/HQsSohDN4cPlKipzzJbENlI8Gm2Y1yH7QMSVkoqZrg3DnKx nDpbMRvl22JpAWDItEoIRj6H1HVhEdL06OgzKhlZ2xfMZBVcKIYynWTgBBiE dThlEgvKCBL18JGStAqhzKbYltMP1pGpBkK6RcVuV1igbMOSms3d1I1lb41M 88zrlvHR2ox5KLiOwdJSqynW1okkZrPuCvd1h6uZxiJiOqFhrfvVq9yGtw9H NwZtyoErskx2SdS19vKxm811uYACcRcnKi0HtKiwmOnSYrFKWkmpdveMTbGH +TOxvUBPnZyN3VHHRW4dHUUIt552yrqzkEXnHj5autlpu8ptt8VbfdRxLHKr Hv2PiVlC38CI3o0B451OIJSwMWMnqZRxQNgJv5RFByWzsOjisBN/TKEFnYsZ OYE/eLY15g+dhGvmFsjg8I9MtMUBKJG/vNwP5VBeT3E6+4C+Fd9cLV/PbLtq 2MP/0mExtcDImHEloVx6n3E15aW9FDWdDi7KK/mQq7LPc1xDjXAzUpk881mc kKRiCbsbyIJmnmozQh4OeWcfNBOV6LFa/hJ3ALHfQgS2oZuzoKs0jBu8CUUq QpEw5Gq8YihCOqtIbXDkjiSpYmMiQyLMxcM0RqDIPXS9u0LTD6SXV/Rnl+uh 3GINRYRPOsHMd6d23UsSwsfSPeBvTbVM143Dq3kPfzGPCkrAZhyNHHDJgiim hnklJcaPHiHrT2k6whSw5JtMnBvGlkww6cImBFayAYhw4whn72tHAOdbsW3Q mN1WFRVbv1vzBX1sHKNMoPTwiQwqNPgPjHp6WOBafSfJKa86QX8T2mbx4yXg 76Zlrcz/WyLHgj60ZnvthhsIEr87pkPTM3COBJfP8TbC8NFJxZ26kWhQluCf yCxqZSF8Jymf0fwNjJVpKpE8pwIVoCQRrihHprmq7RZoIejIYRFy9eXvcpYe LLGpF33L0Kz1QyWbbRhIp8DWRcjUs9mfMYTCOPY1eMxtQ0F7THZqsWmo4J8q bDzVSTSOC9I2U7tiAC8Kj5vRIx/JpkqgtEE/VoLwnNLzCNfp0ZlOxBGTyMoo eeIsvKxxpJj18BvbzW+saIo2vSfXag/A1BQ+3Lil0JmaTR9V5ZSxCn8Pzpm7 vYrJ9P2rG9Q/xWZT+m4XW2izemvHZKwGTXNSeN506OkBfxBY/IcD/axYdSNZ G4ZFDQyWcQ8NMzXkYpavBQdX21We2SpC2aatW6uT3ZJQJXuLGw0oJSJckdVd balhhPmr2PIpgcXlT3qPcWzosW/syzGdguBdFwOI2zLEJb8ws6zonKRH9jjf eiRvLKNOH66pHouO9YPyqrsAky/HHOFGBpam+QBNz6mL8wmZmvnwbIQfKWTW y/KfMKlxmZLkfcxmZQboWBmvFVq9i2FMLwPdAtjF3I4BC7s4EPNuyMd3a9mi SRwhdqywd7tT2df8bHMztFAWDn3VouMpMm0inLNR0ye82DurS6/p1KcgOY8b 56gJ3UruykKq9ECRVGN8EauRS3LoTOdyLjWKfePxjK0zJWCRcUbxksqhb+JA /My2ykDmv8EcN9Qh2CwaFqZR0fCwgyCjjTNS6AzROnKsNRzk7kg0wjfDy/h2 49k8kg2BqTa54H/aqIk9vSnabCHUdT6zELM4s4y9aH3XUR8bqpzil3VDWIIo 22ICZIRZAhSiRUQL0R/J50bvNIrZmVdwDWkLUgrDv7g95gC8X9iDcVMnC65p ZcxxavG1aoroRn32BrFZfnNFiWNo215O84HEGLBGenV7uTObNfoFAtFZE2+p 9GxbkUC9pX0vKwSC5VpFMICsLriCjNEtIYsZWIX5FCHuMFZsiFWFamEsSKTW 5UgdiShXFCdimgb2FOGosEPkRsUKQ0oSSsAvCLYR5b8NRpjY1RaW66V9sZNw Ud6d9Y1rfkLQyJl/1rec1ByeUrM9CFVZKXe+TGKPMv9vUTG3iN1CP5StAjuk eNsZp0loKrY5vT8w6MzbP1CFCUOHE2i2yTmgcapSuZxfFn3Y4ZlBOfjIfgyL WdeiaVkzadIQOsw9Z7/3ODM4bGxDT911coEabDsgNBT2Ko5sJVQlUG2+YWLN YrWMNTjaPo7FhdWcfZxLlcNgg1B1rnBy8yIB/obEpqFrRrL3yrgMaqffrvt2 40dyUnTI1+J8+hJn1W+maHZedxD4Cw0jK9Y3oOEg8MFuwovMmOKh5CnuQLBG jUZCYlICQyl7MclhxjkwDDP0e6GKsR2hF08Tum6JPCiz993HfwAvbmAX1KRU tW1z06dpmRxz+1xLH7lJpaK0m5sLTO9MmF2gCoe2R4QdNSyq0PZQDCd7OBAM CaULtEg1uoGr2LdzSdrK+mZOmtO2LPTDO4zKinTcUNQgh80XOwcOv/1Z6icT 6S7mUFRvuMDknNwm0rtTVVNNaU2ke/bYoxYb1dhdwb2kaUFhIm+HPV7gjain xx21iciJYtD40YBix+wIC4c0G7Pm/G6SvANbRjQqXczdBRYm/wo8SOLFpLNs 7M1hSq1pc9hmH7doaS/DWvAk7yraRgOKLC3LOqpxo56Vci+2WTzbtf+iXHDG AFrpIjNwBsSXHQacLusGrS7jPEj5ATiklajaiNPXIoHOaXHA7BaGCCfYVEzV CpPFoe4fGgltQoYaafQLcoVUAPmtPcDoqTIgTnmAtmPl4Yequll8wkRK6cY5 ESI0pWUzl7ZLri8M4hyoUifq2nG31vM6wSDkZC1jZ0X/0pQb+EfvrkXauw0L qH56uAYyn66E86sdLMaMIeUqvlQK2WnxUPoBbwDn2NdIkRyDjxwetah8aP4s LAAiR0Qukx2gYDtuzt55BMtIroHNDTCZLfl0tOr8CMspH2L2lcOTqXCSC943 xwvMkY5yrNqWcqdv07k8ZhV9Lk9Wc1ECyUWJWRYXF3OEIEMro6KYLafHGuEx 1jnjcqYYjOwqIm9ZlLMhgqG1+xRAhiQcwUi584ZQPy9Oe9Xa7A0Dp93OHE8b Uf3UQzDSzF9SyFbP1N9RVN+xK1GP4963bT6ap7Qj19W3YTZPnTid9YGSdqU7 WTc0z6MPSt830Tkp7Ta0//UdX7LFGD/sqgbiz6jfEzOaSguMfF5JgtBAVPyM gzTXScWJOY+CRnLlIu8Ww3vwKOHh2n/AQ0VSyOHoWxBaqJ/5iABPV6dZ2WfP E4CrS/PMkqbtumOp9zWGHPRrVRM1ehFdlmXqlLX42ZjVGBXSWeLIxD0Su0aG W9AzX+zJ1C2yEDL1TDSa2Xry2+7te+9aI1aVQT9zchHZBQgBB9oX+Xj1aeAa ImKaw5LPwhq194EWtOAkn8yOvNqjlsdSjNH5Ye2m5Clxv+JPtc3m3qBlnGrQ qo4C0cOS3dRtlrMZ74PNKyo5G35hIYiyeYjWtCCiGrJUDAOAnqEgilcSDu0O IoA2VgLnv/ZeQIkaSpk+yz5+wLVdygyUtwRtL9t2M0I/CJKuZ4rksN2/vOoZ uBAYEeNvVLsz78pcd/zMHowMDXre9GwSR0QcrZe2Wsayd+pZmTSfysofnIkE ljoSpbnlUYEO0B/lteL3q4fMDM2fEcmHabwwwSk4oHcb6pMF8USohV3KK8T2 V+3SOIbc8TXj0+Xb+8s9W9bXGLn7LC+qj221U/Pw7ZZzFdbCAHCU8SHOclQ9 6/dB/wSxBNDt45j1mog6Zi+hnaa2N2wLpKa11xJCGnplt0ZCyEy8nYT4WBiL 67HekJEUG0dDbZtLecVPhn4y0Aw+atpl6ktotL4wQiDtgSqvR1GuaTlOddR5 jqEkA0xkCSFxxBbqlUFHmsM+x5c8PSi+/o7wX6crRb/GiRSyg1xbZWDgN4sI Y3ufd5Mb1TEzsmsuvOq0Mob+wZUZ1h8mZJc4Ldt7sC3TGKiisRzmDSn34WMF PsxNdQn9PYFUDCq4ThUtfsE6yiyQVuIQhuxtPV60KddSGpDaFPaDJWJ8eqot /ofcPs5/EYhxr2NbdQ6bR2SxfLWY1xh/cWy7hibNLZdj4b5TVyRcYW5CDJni GKyNslmIu15ejBUrK1rrzAuLxMztNyKJF+xe8l8SWRKUjbVuvJn99QqHiFNA 6XcPk8xLCJiSj/3LHEa0doQi1XxrmuneiOgj6LIvPr4vgs6gSKDe/dhaXyQ3 WvZhqrXPq10SbpChlCZ3vLx6g5qnjsRHdkQijgZPkT8X6QU5X+9E5ACFWWAF 9HOOeeSKzqB1q7Ws9GDoImWEch1DUsNluqG0A8z43x+ZP4t4HUVQJ9f8HqS4 7t6gCDsBc46q8ESwrLofNzJzyuNodU9Lol0c8x91HkjbAdng2g5L3osVZlC7 0TRb0kCYpgGFVAqtYZER0AqzKkBC4x0J/doqMSSIZAtnlEU/EoU7/KAmDDC0 VMgL6MwNEN2Y0cka0VKktcdR+vN9hxuPUKcxGOfpv5QMobTQLOvkHl1RLaoQ w3+2XkxaVNe5ZPN/i8x68eE9bZvmodryAylXDI+EJZj0HZ5uS8wBWL27o4lS vKCODWxxhOpai4FFXMbihBl1yqtIDi1yUzwXsV31zKSRQ7zJKlKh2l2q1+1F yNivSwxlmKSXYu3dC7c+TjWNmGc36pnH0onjm/MUGL3a/iHPFpltMm9p/m8B IzO2x+RNKcQDNeNABheUErjVQJyp209AjeiMSHz/Hmzgsu7HB/oyZ3Oa4IVx gD4Cll1DF8UlkoQGhYiEmCOpJclf47YbbrnnhsjhBHDacd/49XAHigk+S0SC lns7lo7WoSbadaHnwznGPhH1dim8MnS2re4Lja65V5utoNIvDxsxrJlHRFVs 2CmaPQdg5AbXT+i/BeJjxprmFRzJYUYd4upoNd1GIh7kpNTr5MeL5EDyZ8gY ZsCwbAC+sR5GMfEgNo0QwMcJKKihoW2m37XN2NmietrZe0hsoDCyQyXa1/5p VLhUSNP83xJLesPTGY+cV1jDLp8DQ+eETXKAYN9ZvhlOUAwTPAxIZPzo8Qgr +HEGVfQbYfh0RuFlA4lZ+9PI52UdlOhiga0CP/wyfk4hEnBIMkprA1Hlbsm+ GjtC/9EyVL07msK8rT4+XuGNSGrQuzDr2qfaBbnVD5M7pXl+OrBy9DRnCgYv d5TCTEBWJjQWaA5clnCBwFxlz5pYTLbbVtymOBDXenUDTpTidpK4waTZK/By QEID0Aio+GNsEsaMkzsOpl1AuSD5EE2yV3mnuYNne4LkSeKdc7QKwG47mO7Y UQfuupMVkInwTD/K7bD1x2cocpS1iSYXaF22ZhmU5ZUtnV9OoZNzg7BLszXh I5Olw2bm6OkCnJpDzA/k/2I74zFF+S/wUTvs5aUKAAlWYyTG3Dtk4ZfohEEk TYo1EvPUhaYtzEgJHW3sovESEWkJFXKbYy5kpUK2mHKU+w7sz6XtVpAF5KrE 40yJGdRjoIjcuEoul2EkOcyzJSmnxJKwt6Jd4v8IqedokxxLMcOrMT2MW9Cg O+YPTDUndNKbBU0jBmYkY7vWnbW3jd8mxsTF4VQfU/HWGEq05ApSVvAvpKk3 RY3L417jZK2TLMQ4eu4LcytvBeDyrhFKA+9sGNXFGg0PBHsceqmCPfxO6xwj qww8kq+6C+P6l1nHQX41th5WWMoGLDuvLu46bO0u72Y9AFhzycubmdnJZTa0 rCmRyzdBRivAcprIb5k1qMX+UOAOQyp2s0DCS5hPVW5Lo+EbtNykI6a2bSni lIQ2qCruraqZdHQyqzWQ1FuA/w48T3I6oZocKOxosm5B5yP5tLZYYow7Z8Lq +BSDEzbzeZdErGqFpVf3YaXXxMHXU+T0Dx0iiQmDxIxQMSwRHvdqRyY/KyRx mcrmCFCy7ofze2WO7Fehycl/T+KG9WGXfat5kVnzmf350H1vO8N6UMA7GV2M KfvLym4bwsmWXajaAdXeIOTIJyleaMRjDmAgi6ONjo18khVFvjw0tmagDhDG wdz8RkflagA7b3k5Y49LfChn19corGYynpBLLcerB7lF8vibugXQZBjl/wwm +9q/1kbxDclZqgFF2RjO4jPtERPL9l3v6/VaQXVz1liLi+vvwij4pSQQxkjm GiTJNKmBzp1ZLyXK+IkfonAmeAkhLWA0Q3Cy+7UO4CVe+H4i0A3NkSHcPZwt +MfTDzx6Tpy/Iv4NbCDZkFBuRunKpmSBrGbr4RpSDnSylTHTl2KU4+ZWY7eL sqUYnBHji+VLSLl0yYbhXw+wt6KGhaT8srGL4ZvDZHbr5c8RTlaZfAwpL5pH vsJH/hAQykDBsNiYaajHjsSx5t05vCHjpgzXKTteEOBK2en6kIV4U3ZDP+za UZ+8DNd6LcuUmLaXsF9Nhm3t6N8d6EvawGHogCW35Fq37bhW5L961S2Q/0ta 9IraFYnanR6PlKDAUgC5rX5sBMgvCzRCe81KDgqwF4LMw7BZ306T9dLhoy+A qptA400elzlaIE+luiiu35EZWsqgyDkITSQn5Zztjlx+6lydvaMX0GuvoeGm TPls4CYr4TW9LAppDLvSyysDDbooLs68urzl4ahlDq30WO7ycJGlsIttabhB yZTbQhXrYOfMJy5XqJWDQc1Z1SEAJSsFCU/b3IC0Gr6xj0SEwRCbeDgA/e1C mowNVZYt6eF9Zs3izMnJLX4fEN98AdRWRl+rArlmVt92uf8AHDp6GgS8PoDG 04RqFyIiN9JTFAVvcSJ8XHm6VkYeCC4jrIcKwI5Kd+hCvFM1yI6z6sPIOibf GbKD2Db0nGsXory2zrOn+ebutN37vr6hYtoMI324ZiaDmB6iEpJyy4zIKTFn wd1WTIXzeObdaaW5loERMXXXnhvfMZ7iLNbh+2nahbs8zdcACK74WJBZHAsT EwKvkTDP9oFiz+VSJeA/EJRwlqHvp7jXMvbcFIQioeWXMmPLb3dJHax216Aq sWLaYe0OV0FNAkBQRHkDSUAzzZTMjVhJfy1roFaM6/MIi9qq93BMOtcuCunm hamY1k1BT+beAuEtZwiUUyU18VFS12UpF9173PMatx4EannWuqKnbMBmOD3k nV/i3FhiOPIBLCXIb2yQW/GzoRscjQ7pZezFrUVHN14IJi81AYVtA7+Ee9e6 twXMuxOqOf0DS0GYQdKqXUtuSyWudqbdbXjRpqJ9iMuuO7qYfLa/qFS2wbqA pryuwzQgbpkP1bgcsIgcR1pw9qwoVrB5LOmwS5SSQ4MUK96qbKi5hfmQ7OYx 0MoZvhKLiOeOdbhYzXFNdKwLfu3wm5MCA12tpLcwPqsSXk3jpBp2fNC4IQNZ 55CzM11bqgF1q6E7cUgtx7o3ku1et6CkGDJZX+YKfH6CocoN9bJiuvdYa6bl jbWQ1l3YvC/ebGunITDFmYeBM5IuDmtN3wpZd8UPFoVMeqUy8bYXA2RxA9F6 w7aj+9VrOfmaAsi5tr/yRCiWXs50KzLpp9pO7Khx71jXbsuGWmvbKrzTWgKg 3KZZKSYZ0A8OS8mMMcTuRWUt17UxAAl4jx0363QYnsY4PTMu+yLrUFfLgFfC wUrXNWzUI4A3GkISa0FOd22SQ820X6gywRDkOGvb5yYimLwrodYE5QtdHRUA 7VDkpDvALCfmHqiUcbrHmQZs62iLrQ5mAofw6xBs9N21rGO+jNbhEFdK/6ky 5tB23ozl8XDLvkzUjVlBGFqXI7Njw0HNFimn0MvBORcf698b+LNhwc6lRaBB 3NV73RIWvCgUG6sXoesks9d891TnJoXbqXmcONu8a/Nps/5tUKvcx/dBW0VW Rk2bOdpaieuAK321OXJoD7DE+hdr/EOJUdng85o56bMhputv/MMSR7E6+MXU e39TQ2A0DbmXwlwDKvTJ05UbX8YdpWRSZvSt6tYyKy0mlEYYW4ZFPGFgk6Xe 1zn/QFqTt6S6FVG/MT2JjCFsDpokPZ/vMcrmPcI1jbX2PUrdKLukBfKXuQsp 3wtfQbzdDihJ6qqbEVxKaO5UJMweHp6DLxOtw+jMEsZ8xg2XIZyu2DGgwRO6 Pj4P8Ewvn2giqspqIcIcfR/jSzmd4AjpYTWWEo14RA2Ct/PRODc6Z8aYpqS8 UFuWjlNtfAltp+9jL5rFKXmkWpYSwagVQ7cOqTqEQI6JdUELYwb+zcRKq09s MTPP9PD6my0oiLzXqGnJroUOj0XjBrQkNEBB9T5ClVeR4lmQHCoPCT0eGlXj gLYwbTyHrS5ovAE8dIGZdSwbyzshzrRhBZsmdY+0VMHfAK8/GJZWc64H6zt9 LtmTOEt8yyGbVob25FcNRnTcEaaYHRNIC1Py5Qf2ARRXQJlzSOrQgE9xxZTX zkxWfdZD0nGXaSEpIYtSLFkp4FPodBxqWV5/A/zeMP7TiPT8ZtEoOB3NR6ql q6PL/l3fiF4gdOuyPV/dpivvb4cDSfbV97Qda30Aybjc8aYXuUuZMGtjvHxi NRjWSHs2FmOf2y+VRZpels3KHdYpLH3dTY/UYJmPHGsHUc6WvmU9RIpwy+0s MJb3lR2b5VHBJez0cUwmVsKJTm8S2Li9nMMQgqYlLfVKYnbg/JIaNDjMmNpl Y4erERJq5Zkf6E7LIgHDXbNHNbJQkw6rBWUuLTGtS/Rncim8qOosIhL4fBVk VqyPgJ1uKVITGedCv3dzhlWXpfC5nW/4s51pHagteb+xinjoawYROg3WIIX8 kw2InzbqGBhEm+CQUCSjeGaAPeh25fCOA4dQ70dNWsw5n+4iMxnicCezXVuG 54LmklK+AM3k5eWKYciINLyu6PMmdxdoL4vIKn5NvYOOwvCKxyNxlALjzRhj Bg8HzmzSgb7cSamDLWADb3viJDYRZyLwNyp319ydwY3w1feXbWqTAZNaaQsr e+OISXxX8Rr68qpuyHgtmRvmHhNbPJ/ly0ixIjrJe266PfZiS2Rb67Vf8GYM uD7m7Xc+EHo+fAmFTwwC4aMgxNMaNVpFfW4O0oDLCOtHMB24LpsPEq90d/Vl 8KN1muR/6ePEoEC4bFAqsq8ylA8QGrdbDnS62K6NSNKNRCbjEumlrcEJO/Di mh6rjD+STcSoxmD4k00mf6/GDZ8vuU+G1wo4Y8h1EVJrUfPXNhfIDk5QQs+F /lQMZn7ZuubKAg/7UFsc3/o2JrQEBL7E3druTuzqNwRpRP3LXfBIM0m0BY0D 19lcPA2SdEsCIHEXuENb5VGLuwLjzjZPcohaBoYX5vuB4VVtP+IwXWuee9/u R5Ti9bbncunSd9ikSR5d1J91gHg+odupCcS8jEvkHd8GgbH68/A6b3bfhedL 20D099uiiXYQJBzS8zv8tpePfJPk917DcZhJLkMMNhVdBBv4XWxBHZFOeVBk Ydz4sQDN7LqO4FgEmtusCvTJPdeVzTJCsNxMDJp4jFJIttLXEmouW0MN9ZiG r0aOCdZpS3F1ZxPEeFmWoOn8Cl4q0ikX2d9y7Vj1jhtKl8nljsdb3q1UPFRz GvLJDzPwnOCAmi8/IDBhGY7IKtLkFyyAl3rIsBZloXg57pjJjPl2wbgCLTtZ 3mLaKvW4Zhtk28c9pLvhk720oy55W857w2TypppWEBF2NEArQAnCOeeW6x89 /Mbo/TSfxxgyeDiMq3og0PJR0SxPcgV8Y2sVtYXNvms+HagKcHyZnD7glYH+ CtgkJDfkmMT2/OCeKnGr3Qf3UdMi/XWDptWwiyhPyeleRHcu75qWpbljjkrb t7Yax3a0MAVPNK1XaNru7YCSm3GJiFgQbUnd0efdXh45F5iDFoiSJc7ccTyE V3YQk4j9cNN86FGgP2WyfV/5dvprco2ssKqZYCUaCZTuv7mN2A//5x6T7TCq CotSMov6ylZA0SQFI5KMtQJNa5qxQWi3G+3Pv71Le2LZtpXMVQ4M4c1Nd+up K5FMTKSHPoEd1BMv1CSd6irv82kzbiPiVIUwJzROso477XMPChg4QbsfoDBV oa03/44TBC26jmCjdWSiLS4tuUazi3aL1jEUnjJru7uTm9YyDizPMqbWYBMz N02Ttu2PFW7zhZbb1nteIBLda//fNfIXQDmzkGh8anlW7aagH+Iw1kKJ0+Ng aYaIbsQhvKH1dlltE2c+peV18UZZrRb37emZ+QPR5aCRDSFtJbZ1yRUMx/Md Uubn4LXC9oYSW3MMRgoBJEdLgE7/SGjWejjRRNpOdQepkMKxO2opeu9zQYfs GtpO5Vtc25YLSm/bTNVs1pbm2wwLu9ekAqkKp2rA0XNVSpx6bWMy4+6GQGlL 4Z0pICgJzcvcIEWjlvnaG7LlPyXrC/BzhQfkgIZkSJwXMACcb2HzqK2y1yUp zgDFMMkttOeHYrcV3uxVC8+2Lz0MKrX2KYbMNnUy1zH2dXJhz6jdlP7VEwiS pCtY4b6AgRDVSsjKpIQ3MNB1gvIWrWRsFoi08gBQIujymyKNHY3kFRKECOW/ VQA8QALVof7nAKbqG4qmio8E6nTx+fgI/DNnz6QtqlrgBPkFOleqWCTyrBZD CkOh3KraZAEqezL1tl3mc2H6dRdXXI3VbeBcxkEsWFtj304Za92bO0i26tZf 8EjrgpSwMbZE7+7ttpRXwO+q/7lMPKO90n/CnlR6wFrkCd2mrLhBJbW5o/iB 9XGo4BcYj9CXNOu3jAbyHRoxDkRkNviVa/XxmHFJdulJyHDbny+DnMbe2xpM dswKLWOmltUmvVjDsx09qYlqLYoZqUQMZeV6gdxga8rCzsrqx5cgyEEnX8MO bowSsgDoABmL9PIrOLImATqvkwIT+TGjKv5P5uG7OSAfQCmpT9ywN0KI4oNA XXQ13YAjjLL2l8f/LaNRWNEsna12M991qtumq7NrvyzgqDmgI+eXaRZZWYBv Wa60hu9kW2QvqYmCbuBcSQt/YTIzArl3GakWxl3F5HohmVq51pdpMpFHYeKj kTzYGC5nDKDpRxqKUpTRwqLzQsPIN+w2hGnQlgWXjRpJ5EEojHpM3DHRtmLw jMpMTv/9Xm3ls7a+r7j/lr2D6rFpmUyrWmD5s3+7G1rh0ZkELNjUrEQdUYGB c9UD8FEiLJLMicMgxgnZyUdm2PdQdJoQNeCqj70cyuLqeEj4gEv4CIt5gIrA aHIvwY2FhnwMGUu+T+q6Ex1WNrIMk1Fu7MrnMLzncAe39HIsDu78Kv/yX+f/ L81TMsNwqtr5OaKPKjGLQhySk1XpyNo6+VuStWEARgcZyFYDhG0I5VNUEjol lk5q1BgG4kdulMpA72/NI1hCYaNUcqN4ZQ4BI+ios3lZGyYRcwQiHoDtRNfG N7bCRkq9NVGb2GZrwKNGsbU7M7mbmazHfgkmS+JEtW3a8moEYbN8WS9ZwJCj uzwHmoSlmrChO00Hn1gB5AEQOUy4AqxwdXPBQGau9ynWzJfixLbuuvgxbVO/ 1fzXCghaHysF6tDAA9LKcEwlu10D4PxMHtC1tF3NGoV4xDPuhnhsQlzP7i7O CMb3PPP7PQ+lFXRQVV1s36Hr6qWrinLhTYJ70Wycn7nkwLZS3lZoa6tx75fP x77WRNZWcFdzCS0yFAhh5UdJhJVF7CVAGzRrNhkwl9ay+2uZ+FRDATCsNCgM mw4nqcXpM8hv07USXtCbn7TUtlFydymcaJ30Z9R0WW1fe3GwZE586oAgQYtM FvL7sF54Hh9JU9SZsFO6Gxj9SL7PLW7Cif1kGyWXY2kkQ3I+f9iDtQNad2ke XcV3oL9AZ1DCE4dF6Wgj0GwHzAT1ceIsQmUibzxrWP7oe4CvuQAL/SkuSmc1 QCc+FeuogtbdWcxuszBa2499pQIVTg06Zizio+bJVt4hIpAQwkqqaaUHjHtj RhAbTrEgPK2giGPJ0Y/Q2wEWlrApQ2kyyAof+XeD6UNxEbHhOwQp4DhwiaIY F0134giZ+I3DDMrbzhzewtg0lkL/xJwK+tWsVfhPxnrd37YZidaJvZwDe/va U4W5QafkesUCh+I65Kv3fOI8H5rbS8V42Ksm/2zXNG5p0A/B2sLjdsbGk249 kh8KMuvbGjeUsK3hZUJkE6hAZE52Px2CyWaUHvYt8CSPYDudtgReybhDl0lO yMRPKhr0hzInu0rOQoh3rfu896Ha3oec2oQpqy1pNidnUJDMo9TuxN1v5bBw zMeL4rWNCE+LE1/DsoBSKcsUK6gBrJR7HkhcMIGZTK5L4RpIyA4tvfQUZGpp XX5jgx/Y+ODz6GkrQodAToxSLsRJtdSm91TSgROtdYGuPR4muQ8T8nbvq8p5 rCwFHf1ko4NakRmxLycDidQMgCsGPlBMkjxJnxzgCm4LVkNZ40DD2AgXJ2G8 D+ti+io3fZAmgiAlUJhvSjoNEQiHA7HhOzR3IDMc5BV2/HMEc+5G4emJj/ed qA0JK+/NGBMrsx4KO7Jd26m0LiDYU1x5H8DKwwCvmo6+Al6teGdHazZWBlXb ijSgSugDyKmQLIA+W06lL4FjHph2Jc6ljGMvRtDJuM0EzW96G0ig4wPKaJf4 RJFMNn+Ay5XX9zGjU4AVApdD2zt9XHF7AMOXWRbwpR0Z98AMK09fQQIuBe/q enaZ07XGJcIG6jmtvTin3gHw2qZRKGEq3IjlNHd7YP5u1iXmyzzQNzOMEPtA Fh65kOummWd4zpiS+LLcgB2WkSHJ7cZZ/HMDBTA09dOnXRAUyeSSW0YNJ60g cuGU5FhXM4RP9Y87O5TZuTIbHEya5oSdHC6zlO8UbXg0ufW2X6zj4bS7tms3 9wb4Y0NeKjv8BnqaOlANDUnARalw+2YNIjsy9jXsvKYcXslxsGh1RdOQhM6J +NVamOEyh8YWYWRvXC2YoLgkeW5W4XbJGRmSkIB3ATzDYcNCoy1Yx2bJBTIG pSv65rvnBCgf3a2jbLV7a3mbDK5jSJm77StgUjdMeTolloCLaDewZEHy3TkB O7v+aZi8o1wH2sJurP2HVwRSD48RV45jMaI8PQE3wewN+lJcivmPw38MOtF4 BPTyUHxb8U3NPC3pTBhqq2cJRqKsi0Yw0PwaRJL4MkKENXCSp8ytCGeSs8an O3U7TN1G6Udfm7xTcaiyVtU3nVII+E4hk/7KYYaa7u4hWx/MX3ZLLNucYwoQ R9PH6VeRYMLEuyABu7ozNEcGk3e4VPLqtZggBJSMDU7o2qtoGdH8Jgfv5JHJ 072W+O8DRThCJtzOk7xI/vC7AmrQzLjnh6vsNtO6m105Qp6UKaKtjraq3t4Q SvYpI+u2EfclvThyQdIlNdDjsDfP2o7JAVMM33wC0U1EJSlWub0ZCbcCQB5d AguOFTUiDjTUWwxiwp2HG7CEhZa1Qr6XqEQCEqPvml2Jc1/jqrOxvJLJ3F0z 7+Kneal/26t2kI8vFbyKT9L4P5q3PIcb5tNwrn3eByd17WogQ2dpffnYaBm3 3NwesDVJ2i7Iuyo4t3FdMnhpTIbCAPFl1FMcsCBqZzx2P9HgU2Zy/ikMAGH1 QkxJ/lCIciIT0AELbHxjwcCBZXVbWteB7im65qhzCCoDi9LR1wD5hSGif5Lx QTrV8I1rcqpjFpG1PtZRJjlVXwRRxpdsHuBmc4JdgqNtAL3Vmoh8Oogd1c9a qMjVWH+L4WRZJBczOcQnCRBa530nfeHSPUUHlnHcUflmDhCYr4RMSPDd3NoM q5GQTefBPwxgDqWdOKTLyxAXVfMhIbpMoFgVdYw/ULW5rEdcWN1Gv8ht46iu ocOANMhIrmuH1YFLIAGxVqcUoVWWPhv8AcAkVlLL9XkKmfkiQxjIjVF9epnv 45DzO15XIFKCjhnmLzPrhsYOhGBKH7VaO+Mq77pEbVURshF1LZTirmOfqi/E kNYpmEhdVX8DLE/ukZD7T5mNC2P5qM4yr7L8uaDdzC7B40mfpby5JlaQX5kG NNzT5pRWmgl3ddSmw4oj1DJfufC0G62gJ8MSlkfvZAaBFPL+kXSTYRQUE+Sw zsALnKThVFdqnFyPjQ8wcool3e+N3UHndisNuN8wBzkjy4N2su+f3Zvk1ttx pLq4t1I5vXfTTlM9Itae4fi/fDx4XAzEdGlmXX9gDvKBclwswfkcVcaTkXES B1IDgAkTZdgAdyc//PO66RTJ+5UBi3xcDYUFCa5zsaErcHaz+25vhn4DKckA XcdIA0aqOsbkDDHNZlox5VoYOKxpsZc9LVOX/w+/ry5IfjwBAA=--1133331701-635408861-993124011=:10449-- -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-devel-request@stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._