Dear R users: I am trying to create a function that will loop over three dependent variables in my aov model, and then get the HSD.test for each variable. I like to store the results from each loop in a data frame.
When I run my function (funx) on my data (dat), results from only yield gets populated in all three columns of the dataframe. I am not able to store the results for each variable in a dataframe. Any help will be highly appreciated. function (x) { trait_names <- c("yield", "lp", "lnth") d = data.frame(yield = rep(0, 6), lp = rep(0, 6), lnth = rep(0, 6)) for (i in trait_names) { mod <- aov(formula(paste(trait_names, "~ PEDIGREE + FIELD + PEDIGREE*FIELD + FIELD%in%REP")), data = x) out <- HSD.test(mod, "PEDIGREE", group = TRUE, console = FALSE) d[, i] <- out$means[, 1] } d } structure(list(FIELD = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L), .Label = c("FYLS", "HKI1", "KIS1", "LMLS", "SELS", "SGL1"), class = "factor"), REP = structure(c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L), .Label = c("1", "2", "3"), class = "factor"), PEDIGREE = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L, 3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L), .Label = c("A", "B", "C", "D", "E", "F"), class = "factor"), yield = c(1003L, 923L, 1268L, 1226L, 1059L, 1150L, 900L, 816L, 1072L, 1158L, 1026L, 1299L, 1083L, 1038L, 1236L, 1287L, 1270L, 1612L, 1513L, 1676L, 1504L, 1417L, 1932L, 1644L, 1293L, 1542L, 1452L, 1180L, 1248L, 1764L, 1326L, 1877L, 1788L, 1606L, 1809L, 1791L, 2294L, 2315L, 2320L, 2083L, 1895L, 2284L, 2000L, 2380L, 1952L, 2414L, 2354L, 2095L, 2227L, 2093L, 2019L, 2505L, 2410L, 2287L, 2507L, 2507L, 2349L, 2162L, 2108L, 2319L, 2028L, 1947L, 2352L, 2698L, 2369L, 1798L, 2422L, 2509L, 2234L, 2451L, 2139L, 1957L, 799L, 787L, 701L, 781L, 808L, 582L, 770L, 752L, 801L, 865L, 608L, 620L, 677L, 775L, 722L, 1030L, 606L, 729L, 1638L, 1408L, 1045L, 1685L, 1109L, 1210L, 1419L, 1048L, 1129L, 1549L, 1325L, 1315L, 1838L, 1066L, 1295L, 1499L, 1472L, 1139L), lp = c(NA, NA, 46.31, NA, NA, 43.8, NA, NA, 43.91, NA, NA, 44.47, NA, NA, 45.16, NA, NA, 43.57, 40.65, NA, NA, 40.04, NA, NA, 41.33, NA, NA, 40.75, NA, NA, 42.04, NA, NA, 40.35, NA, NA, 43.682, NA, NA, 41.712, NA, NA, 42.566, NA, NA, 43.228, NA, NA, 43.63, NA, NA, 42.058, NA, NA, NA, 45.19, NA, NA, 41.91, NA, NA, 43.86, NA, NA, 44.48, NA, NA, 44.34, NA, NA, 43.03, NA, NA, NA, 44.08, NA, NA, 41.39, NA, NA, 42.48, NA, NA, 44.13, NA, NA, 43.39, NA, NA, 42.82, 42.18, NA, NA, 41.42, NA, NA, 41.25, NA, NA, 42.31, NA, NA, 43.22, NA, NA, 40.52, NA, NA), lnth = c(NA, NA, 1.151, NA, NA, 1.135, NA, NA, 1.109, NA, NA, 1.117, NA, NA, 1.107, NA, NA, 1.196, 1.255, NA, NA, 1.229, NA, NA, 1.158, NA, NA, 1.214, NA, NA, 1.152, NA, NA, 1.194, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 1.2, NA, NA, 1.219, NA, NA, 1.115, NA, NA, 1.205, NA, NA, 1.238, NA, NA, 1.244, NA, NA, NA, 1.096, NA, NA, 1.021, NA, NA, 1.055, NA, NA, 1.058, NA, NA, 1.026, NA, NA, 1.115, 1.202, NA, NA, 1.161, NA, NA, 1.168, NA, NA, 1.189, NA, NA, 1.204, NA, NA, 1.277, NA, NA)), .Names = c("FIELD", "REP", "PEDIGREE", "yield", "lp", "lnth" ), row.names = c(NA, -108L), class = "data.frame") R version 3.2.1 (2015-06-18) Platform: i386-w64-mingw32/i386 (32-bit) Running under: Windows 7 x64 (build 7601) Service Pack 1 locale: [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 [3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C [5] LC_TIME=English_United States.1252 attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] agricolae_1.2-1 asreml_3.0 lattice_0.20-31 ggplot2_1.0.1 dplyr_0.4.2 plyr_1.8.3 loaded via a namespace (and not attached): [1] spdep_0.5-88 Rcpp_0.12.1 cluster_2.0.2 magrittr_1.5 splines_3.2.1 MASS_7.3-41 [7] munsell_0.4.2 colorspace_1.2-6 R6_2.0.1 stringr_1.0.0 tools_3.2.1 parallel_3.2.1 [13] grid_3.2.1 gtable_0.1.2 nlme_3.1-122 coda_0.17-1 DBI_0.3.1 deldir_0.1-9 [19] lazyeval_0.1.10 assertthat_0.1 digest_0.6.8 Matrix_1.2-1 reshape2_1.4.1 sp_1.2-1 [25] stringi_1.0-1 klaR_0.6-12 LearnBayes_2.15 scales_0.3.0 boot_1.3-17 combinat_0.0-8 [31] proto_0.3-10 Thanks. Nilesh Nilesh Dighe (806)-252-7492 (Cell) (806)-741-2019 (Office) This e-mail message may contain privileged and/or confidential information, and is intended to be received only by persons entitled to receive such information. If you have received this e-mail in error, please notify the sender immediately. Please delete it and all attachments from any servers, hard drives or any other media. Other use of this e-mail by you is strictly prohibited. All e-mails and attachments sent and received are subject to monitoring, reading and archival by Monsanto, including its subsidiaries. The recipient of this e-mail is solely responsible for checking for the presence of "Viruses" or other "Malware". Monsanto, along with its subsidiaries, accepts no liability for any damage caused by any such code transmitted by or accompanying this e-mail or any attachment. 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