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R version 3.0.3 RC (2014-02-27 r65086) -- "Warm Puppy"Copyright (C) 2014 The R Foundation for Statistical ComputingPlatform: x86_64-unknown-linux-gnu (64-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.> #### Simple integrity tests of the system datasets>> options(useFancyQuotes=FALSE)> env <- as.environment("package:datasets")> d <- ls(env) # don't want .names> for(f in d) {+ cat("\n** structure of dataset ", f, "\n", sep="")+ str(get(f, envir=env, inherits=FALSE))+ }** structure of dataset AirPassengersTime-Series [1:144] from 1949 to 1961: 112 118 132 129 121 135 148 148 136 119 ...** structure of dataset BJsalesTime-Series [1:150] from 1 to 150: 200 200 199 199 199 ...** structure of dataset BJsales.leadTime-Series [1:150] from 1 to 150: 10.01 10.07 10.32 9.75 10.33 ...** structure of dataset BOD'data.frame': 6 obs. of 2 variables:$ Time : num 1 2 3 4 5 7$ demand: num 8.3 10.3 19 16 15.6 19.8- attr(*, "reference")= chr "A1.4, p. 270"** structure of dataset CO2Classes 'nfnGroupedData', 'nfGroupedData', 'groupedData' and 'data.frame': 84 obs. of 5 variables:$ Plant : Ord.factor w/ 12 levels "Qn1"<"Qn2"<"Qn3"<..: 1 1 1 1 1 1 1 2 2 2 ...$ Type : Factor w/ 2 levels "Quebec","Mississippi": 1 1 1 1 1 1 1 1 1 1 ...$ Treatment: Factor w/ 2 levels "nonchilled","chilled": 1 1 1 1 1 1 1 1 1 1 ...$ conc : num 95 175 250 350 500 675 1000 95 175 250 ...$ uptake : num 16 30.4 34.8 37.2 35.3 39.2 39.7 13.6 27.3 37.1 ...- attr(*, "formula")=Class 'formula' length 3 uptake ~ conc | Plant.. ..- attr(*, ".Environment")=<environment: R_EmptyEnv>- attr(*, "outer")=Class 'formula' length 2 ~Treatment * Type.. ..- attr(*, ".Environment")=<environment: R_EmptyEnv>- attr(*, "labels")=List of 2..$ x: chr "Ambient carbon dioxide concentration"..$ y: chr "CO2 uptake rate"- attr(*, "units")=List of 2..$ x: chr "(uL/L)"..$ y: chr "(umol/m^2 s)"** structure of dataset ChickWeightClasses 'nfnGroupedData', 'nfGroupedData', 'groupedData' and 'data.frame': 578 obs. of 4 variables:$ weight: num 42 51 59 64 76 93 106 125 149 171 ...$ Time : num 0 2 4 6 8 10 12 14 16 18 ...$ Chick : Ord.factor w/ 50 levels "18"<"16"<"15"<..: 15 15 15 15 15 15 15 15 15 15 ...$ Diet : Factor w/ 4 levels "1","2","3","4": 1 1 1 1 1 1 1 1 1 1 ...- attr(*, "formula")=Class 'formula' length 3 weight ~ Time | Chick.. ..- attr(*, ".Environment")=<environment: R_EmptyEnv>- attr(*, "outer")=Class 'formula' length 2 ~Diet.. ..- attr(*, ".Environment")=<environment: R_EmptyEnv>- attr(*, "labels")=List of 2..$ x: chr "Time"..$ y: chr "Body weight"- attr(*, "units")=List of 2..$ x: chr "(days)"..$ y: chr "(gm)"** structure of dataset DNaseClasses 'nfnGroupedData', 'nfGroupedData', 'groupedData' and 'data.frame': 176 obs. of 3 variables:$ Run : Ord.factor w/ 11 levels "10"<"11"<"9"<..: 4 4 4 4 4 4 4 4 4 4 ...$ conc : num 0.0488 0.0488 0.1953 0.1953 0.3906 ...$ density: num 0.017 0.018 0.121 0.124 0.206 0.215 0.377 0.374 0.614 0.609 ...- attr(*, "formula")=Class 'formula' length 3 density ~ conc | Run.. ..- attr(*, ".Environment")=<environment: R_EmptyEnv>- attr(*, "labels")=List of 2..$ x: chr "DNase concentration"..$ y: chr "Optical density"- attr(*, "units")=List of 1..$ x: chr "(ng/ml)"** structure of dataset EuStockMarketsmts [1:1860, 1:4] 1629 1614 1607 1621 1618 ...- attr(*, "dimnames")=List of 2..$ : NULL..$ : chr [1:4] "DAX" "SMI" "CAC" "FTSE"- attr(*, "tsp")= num [1:3] 1991 1999 260- attr(*, "class")= chr [1:3] "mts" "ts" "matrix"** structure of dataset Formaldehyde'data.frame': 6 obs. of 2 variables:$ carb : num 0.1 0.3 0.5 0.6 0.7 0.9$ optden: num 0.086 0.269 0.446 0.538 0.626 0.782** structure of dataset HairEyeColortable [1:4, 1:4, 1:2] 32 53 10 3 11 50 10 30 10 25 ...- attr(*, "dimnames")=List of 3..$ Hair: chr [1:4] "Black" "Brown" "Red" "Blond"..$ Eye : chr [1:4] "Brown" "Blue" "Hazel" "Green"..$ Sex : chr [1:2] "Male" "Female"** structure of dataset Harman23.corList of 3$ cov : num [1:8, 1:8] 1 0.846 0.805 0.859 0.473 0.398 0.301 0.382 0.846 1 .....- attr(*, "dimnames")=List of 2.. ..$ : chr [1:8] "height" "arm.span" "forearm" "lower.leg" ..... ..$ : chr [1:8] "height" "arm.span" "forearm" "lower.leg" ...$ center: num [1:8] 0 0 0 0 0 0 0 0$ n.obs : num 305** structure of dataset Harman74.corList of 3$ cov : num [1:24, 1:24] 1 0.318 0.403 0.468 0.321 0.335 0.304 0.332 0.326 0.116 .....- attr(*, "dimnames")=List of 2.. ..$ : chr [1:24] "VisualPerception" "Cubes" "PaperFormBoard" "Flags" ..... ..$ : chr [1:24] "VisualPerception" "Cubes" "PaperFormBoard" "Flags" ...$ center: num [1:24] 0 0 0 0 0 0 0 0 0 0 ...$ n.obs : num 145** structure of dataset IndomethClasses 'nfnGroupedData', 'nfGroupedData', 'groupedData' and 'data.frame': 66 obs. of 3 variables:$ Subject: Ord.factor w/ 6 levels "1"<"4"<"2"<"5"<..: 1 1 1 1 1 1 1 1 1 1 ...$ time : num 0.25 0.5 0.75 1 1.25 2 3 4 5 6 ...$ conc : num 1.5 0.94 0.78 0.48 0.37 0.19 0.12 0.11 0.08 0.07 ...- attr(*, "formula")=Class 'formula' length 3 conc ~ time | Subject.. ..- attr(*, ".Environment")=<environment: R_EmptyEnv>- attr(*, "labels")=List of 2..$ x: chr "Time since drug administration"..$ y: chr "Indomethacin concentration"- attr(*, "units")=List of 2..$ x: chr "(hr)"..$ y: chr "(mcg/ml)"** structure of dataset InsectSprays'data.frame': 72 obs. of 2 variables:$ count: num 10 7 20 14 14 12 10 23 17 20 ...$ spray: Factor w/ 6 levels "A","B","C","D",..: 1 1 1 1 1 1 1 1 1 1 ...** structure of dataset JohnsonJohnsonTime-Series [1:84] from 1960 to 1981: 0.71 0.63 0.85 0.44 0.61 0.69 0.92 0.55 0.72 0.77 ...** structure of dataset LakeHuronTime-Series [1:98] from 1875 to 1972: 580 582 581 581 580 ...** structure of dataset LifeCycleSavings'data.frame': 50 obs. of 5 variables:$ sr : num 11.43 12.07 13.17 5.75 12.88 ...$ pop15: num 29.4 23.3 23.8 41.9 42.2 ...$ pop75: num 2.87 4.41 4.43 1.67 0.83 2.85 1.34 0.67 1.06 1.14 ...$ dpi : num 2330 1508 2108 189 728 ...$ ddpi : num 2.87 3.93 3.82 0.22 4.56 2.43 2.67 6.51 3.08 2.8 ...** structure of dataset LoblollyClasses 'nfnGroupedData', 'nfGroupedData', 'groupedData' and 'data.frame': 84 obs. of 3 variables:$ height: num 4.51 10.89 28.72 41.74 52.7 ...$ age : num 3 5 10 15 20 25 3 5 10 15 ...$ Seed : Ord.factor w/ 14 levels "329"<"327"<"325"<..: 10 10 10 10 10 10 13 13 13 13 ...- attr(*, "formula")=Class 'formula' length 3 height ~ age | Seed.. ..- attr(*, ".Environment")=<environment: R_EmptyEnv>- attr(*, "labels")=List of 2..$ x: chr "Age of tree"..$ y: chr "Height of tree"- attr(*, "units")=List of 2..$ x: chr "(yr)"..$ y: chr "(ft)"** structure of dataset NileTime-Series [1:100] from 1871 to 1970: 1120 1160 963 1210 1160 1160 813 1230 1370 1140 ...** structure of dataset OrangeClasses 'nfnGroupedData', 'nfGroupedData', 'groupedData' and 'data.frame': 35 obs. of 3 variables:$ Tree : Ord.factor w/ 5 levels "3"<"1"<"5"<"2"<..: 2 2 2 2 2 2 2 4 4 4 ...$ age : num 118 484 664 1004 1231 ...$ circumference: num 30 58 87 115 120 142 145 33 69 111 ...- attr(*, "formula")=Class 'formula' length 3 circumference ~ age | Tree.. ..- attr(*, ".Environment")=<environment: R_EmptyEnv>- attr(*, "labels")=List of 2..$ x: chr "Time since December 31, 1968"..$ y: chr "Trunk circumference"- attr(*, "units")=List of 2..$ x: chr "(days)"..$ y: chr "(mm)"** structure of dataset OrchardSprays'data.frame': 64 obs. of 4 variables:$ decrease : num 57 95 8 69 92 90 15 2 84 6 ...$ rowpos : num 1 2 3 4 5 6 7 8 1 2 ...$ colpos : num 1 1 1 1 1 1 1 1 2 2 ...$ treatment: Factor w/ 8 levels "A","B","C","D",..: 4 5 2 8 7 6 3 1 3 2 ...** structure of dataset PlantGrowth'data.frame': 30 obs. of 2 variables:$ weight: num 4.17 5.58 5.18 6.11 4.5 4.61 5.17 4.53 5.33 5.14 ...$ group : Factor w/ 3 levels "ctrl","trt1",..: 1 1 1 1 1 1 1 1 1 1 ...** structure of dataset Puromycin'data.frame': 23 obs. of 3 variables:$ conc : num 0.02 0.02 0.06 0.06 0.11 0.11 0.22 0.22 0.56 0.56 ...$ rate : num 76 47 97 107 123 139 159 152 191 201 ...$ state: Factor w/ 2 levels "treated","untreated": 1 1 1 1 1 1 1 1 1 1 ...- attr(*, "reference")= chr "A1.3, p. 269"** structure of dataset Seatbeltsmts [1:192, 1:8] 107 97 102 87 119 106 110 106 107 134 ...- attr(*, "dimnames")=List of 2..$ : NULL..$ : chr [1:8] "DriversKilled" "drivers" "front" "rear" ...- attr(*, "tsp")= num [1:3] 1969 1985 12- attr(*, "class")= chr [1:2] "mts" "ts"** structure of dataset TheophClasses 'nfnGroupedData', 'nfGroupedData', 'groupedData' and 'data.frame': 132 obs. of 5 variables:$ Subject: Ord.factor w/ 12 levels "6"<"7"<"8"<"11"<..: 11 11 11 11 11 11 11 11 11 11 ...$ Wt : num 79.6 79.6 79.6 79.6 79.6 79.6 79.6 79.6 79.6 79.6 ...$ Dose : num 4.02 4.02 4.02 4.02 4.02 4.02 4.02 4.02 4.02 4.02 ...$ Time : num 0 0.25 0.57 1.12 2.02 ...$ conc : num 0.74 2.84 6.57 10.5 9.66 8.58 8.36 7.47 6.89 5.94 ...- attr(*, "formula")=Class 'formula' length 3 conc ~ Time | Subject.. ..- attr(*, ".Environment")=<environment: R_EmptyEnv>- attr(*, "labels")=List of 2..$ x: chr "Time since drug administration"..$ y: chr "Theophylline concentration in serum"- attr(*, "units")=List of 2..$ x: chr "(hr)"..$ y: chr "(mg/l)"** structure of dataset Titanictable [1:4, 1:2, 1:2, 1:2] 0 0 35 0 0 0 17 0 118 154 ...- attr(*, "dimnames")=List of 4..$ Class : chr [1:4] "1st" "2nd" "3rd" "Crew"..$ Sex : chr [1:2] "Male" "Female"..$ Age : chr [1:2] "Child" "Adult"..$ Survived: chr [1:2] "No" "Yes"** structure of dataset ToothGrowth'data.frame': 60 obs. of 3 variables:$ len : num 4.2 11.5 7.3 5.8 6.4 10 11.2 11.2 5.2 7 ...$ supp: Factor w/ 2 levels "OJ","VC": 2 2 2 2 2 2 2 2 2 2 ...$ dose: num 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 ...** structure of dataset UCBAdmissionstable [1:2, 1:2, 1:6] 512 313 89 19 353 207 17 8 120 205 ...- attr(*, "dimnames")=List of 3..$ Admit : chr [1:2] "Admitted" "Rejected"..$ Gender: chr [1:2] "Male" "Female"..$ Dept : chr [1:6] "A" "B" "C" "D" ...** structure of dataset UKDriverDeathsTime-Series [1:192] from 1969 to 1985: 1687 1508 1507 1385 1632 ...** structure of dataset UKgasTime-Series [1:108] from 1960 to 1987: 160.1 129.7 84.8 120.1 160.1 ...** structure of dataset USAccDeathsTime-Series [1:72] from 1973 to 1979: 9007 8106 8928 9137 10017 ...** structure of dataset USArrests'data.frame': 50 obs. of 4 variables:$ Murder : num 13.2 10 8.1 8.8 9 7.9 3.3 5.9 15.4 17.4 ...$ Assault : int 236 263 294 190 276 204 110 238 335 211 ...$ UrbanPop: int 58 48 80 50 91 78 77 72 80 60 ...$ Rape : num 21.2 44.5 31 19.5 40.6 38.7 11.1 15.8 31.9 25.8 ...** structure of dataset USJudgeRatings'data.frame': 43 obs. of 12 variables:$ CONT: num 5.7 6.8 7.2 6.8 7.3 6.2 10.6 7 7.3 8.2 ...$ INTG: num 7.9 8.9 8.1 8.8 6.4 8.8 9 5.9 8.9 7.9 ...$ DMNR: num 7.7 8.8 7.8 8.5 4.3 8.7 8.9 4.9 8.9 6.7 ...$ DILG: num 7.3 8.5 7.8 8.8 6.5 8.5 8.7 5.1 8.7 8.1 ...$ CFMG: num 7.1 7.8 7.5 8.3 6 7.9 8.5 5.4 8.6 7.9 ...$ DECI: num 7.4 8.1 7.6 8.5 6.2 8 8.5 5.9 8.5 8 ...$ PREP: num 7.1 8 7.5 8.7 5.7 8.1 8.5 4.8 8.4 7.9 ...$ FAMI: num 7.1 8 7.5 8.7 5.7 8 8.5 5.1 8.4 8.1 ...$ ORAL: num 7.1 7.8 7.3 8.4 5.1 8 8.6 4.7 8.4 7.7 ...$ WRIT: num 7 7.9 7.4 8.5 5.3 8 8.4 4.9 8.5 7.8 ...$ PHYS: num 8.3 8.5 7.9 8.8 5.5 8.6 9.1 6.8 8.8 8.5 ...$ RTEN: num 7.8 8.7 7.8 8.7 4.8 8.6 9 5 8.8 7.9 ...** structure of dataset USPersonalExpenditurenum [1:5, 1:5] 22.2 10.5 3.53 1.04 0.341 44.5 15.5 5.76 1.98 0.974 ...- attr(*, "dimnames")=List of 2..$ : chr [1:5] "Food and Tobacco" "Household Operation" "Medical and Health" "Personal Care" .....$ : chr [1:5] "1940" "1945" "1950" "1955" ...** structure of dataset VADeathsnum [1:5, 1:4] 11.7 18.1 26.9 41 66 8.7 11.7 20.3 30.9 54.3 ...- attr(*, "dimnames")=List of 2..$ : chr [1:5] "50-54" "55-59" "60-64" "65-69" .....$ : chr [1:4] "Rural Male" "Rural Female" "Urban Male" "Urban Female"** structure of dataset WWWusageTime-Series [1:100] from 1 to 100: 88 84 85 85 84 85 83 85 88 89 ...** structure of dataset WorldPhonesnum [1:7, 1:7] 45939 60423 64721 68484 71799 ...- attr(*, "dimnames")=List of 2..$ : chr [1:7] "1951" "1956" "1957" "1958" .....$ : chr [1:7] "N.Amer" "Europe" "Asia" "S.Amer" ...** structure of dataset ability.covList of 3$ cov : num [1:6, 1:6] 24.64 5.99 33.52 6.02 20.75 .....- attr(*, "dimnames")=List of 2.. ..$ : chr [1:6] "general" "picture" "blocks" "maze" ..... ..$ : chr [1:6] "general" "picture" "blocks" "maze" ...$ center: num [1:6] 0 0 0 0 0 0$ n.obs : num 112** structure of dataset airmilesTime-Series [1:24] from 1937 to 1960: 412 480 683 1052 1385 ...** structure of dataset airquality'data.frame': 153 obs. of 6 variables:$ Ozone : int 41 36 12 18 NA 28 23 19 8 NA ...$ Solar.R: int 190 118 149 313 NA NA 299 99 19 194 ...$ Wind : num 7.4 8 12.6 11.5 14.3 14.9 8.6 13.8 20.1 8.6 ...$ Temp : int 67 72 74 62 56 66 65 59 61 69 ...$ Month : int 5 5 5 5 5 5 5 5 5 5 ...$ Day : int 1 2 3 4 5 6 7 8 9 10 ...** structure of dataset anscombe'data.frame': 11 obs. of 8 variables:$ x1: num 10 8 13 9 11 14 6 4 12 7 ...$ x2: num 10 8 13 9 11 14 6 4 12 7 ...$ x3: num 10 8 13 9 11 14 6 4 12 7 ...$ x4: num 8 8 8 8 8 8 8 19 8 8 ...$ y1: num 8.04 6.95 7.58 8.81 8.33 ...$ y2: num 9.14 8.14 8.74 8.77 9.26 8.1 6.13 3.1 9.13 7.26 ...$ y3: num 7.46 6.77 12.74 7.11 7.81 ...$ y4: num 6.58 5.76 7.71 8.84 8.47 7.04 5.25 12.5 5.56 7.91 ...** structure of dataset attenu'data.frame': 182 obs. of 5 variables:$ event : num 1 2 2 2 2 2 2 2 2 2 ...$ mag : num 7 7.4 7.4 7.4 7.4 7.4 7.4 7.4 7.4 7.4 ...$ station: Factor w/ 117 levels "1008","1011",..: 24 13 15 68 39 74 22 1 8 55 ...$ dist : num 12 148 42 85 107 109 156 224 293 359 ...$ accel : num 0.359 0.014 0.196 0.135 0.062 0.054 0.014 0.018 0.01 0.004 ...** structure of dataset attitude'data.frame': 30 obs. of 7 variables:$ rating : num 43 63 71 61 81 43 58 71 72 67 ...$ complaints: num 51 64 70 63 78 55 67 75 82 61 ...$ privileges: num 30 51 68 45 56 49 42 50 72 45 ...$ learning : num 39 54 69 47 66 44 56 55 67 47 ...$ raises : num 61 63 76 54 71 54 66 70 71 62 ...$ critical : num 92 73 86 84 83 49 68 66 83 80 ...$ advance : num 45 47 48 35 47 34 35 41 31 41 ...** structure of dataset austresTime-Series [1:89] from 1971 to 1993: 13067 13130 13198 13254 13304 ...** structure of dataset beaver1'data.frame': 114 obs. of 4 variables:$ day : num 346 346 346 346 346 346 346 346 346 346 ...$ time : num 840 850 900 910 920 930 940 950 1000 1010 ...$ temp : num 36.3 36.3 36.4 36.4 36.5 ...$ activ: num 0 0 0 0 0 0 0 0 0 0 ...** structure of dataset beaver2'data.frame': 100 obs. of 4 variables:$ day : num 307 307 307 307 307 307 307 307 307 307 ...$ time : num 930 940 950 1000 1010 1020 1030 1040 1050 1100 ...$ temp : num 36.6 36.7 36.9 37.1 37.2 ...$ activ: num 0 0 0 0 0 0 0 0 0 0 ...** structure of dataset cars'data.frame': 50 obs. of 2 variables:$ speed: num 4 4 7 7 8 9 10 10 10 11 ...$ dist : num 2 10 4 22 16 10 18 26 34 17 ...** structure of dataset chickwts'data.frame': 71 obs. of 2 variables:$ weight: num 179 160 136 227 217 168 108 124 143 140 ...$ feed : Factor w/ 6 levels "casein","horsebean",..: 2 2 2 2 2 2 2 2 2 2 ...** structure of dataset co2Time-Series [1:468] from 1959 to 1998: 315 316 316 318 318 ...** structure of dataset crimtab'table' int [1:42, 1:22] 0 0 0 0 0 0 1 0 0 0 ...- attr(*, "dimnames")=List of 2..$ : chr [1:42] "9.4" "9.5" "9.6" "9.7" .....$ : chr [1:22] "142.24" "144.78" "147.32" "149.86" ...** structure of dataset discoveriesTime-Series [1:100] from 1860 to 1959: 5 3 0 2 0 3 2 3 6 1 ...** structure of dataset esoph'data.frame': 88 obs. of 5 variables:$ agegp : Ord.factor w/ 6 levels "25-34"<"35-44"<..: 1 1 1 1 1 1 1 1 1 1 ...$ alcgp : Ord.factor w/ 4 levels "0-39g/day"<"40-79"<..: 1 1 1 1 2 2 2 2 3 3 ...$ tobgp : Ord.factor w/ 4 levels "0-9g/day"<"10-19"<..: 1 2 3 4 1 2 3 4 1 2 ...$ ncases : num 0 0 0 0 0 0 0 0 0 0 ...$ ncontrols: num 40 10 6 5 27 7 4 7 2 1 ...** structure of dataset euroNamed num [1:11] 13.76 40.34 1.96 166.39 5.95 ...- attr(*, "names")= chr [1:11] "ATS" "BEF" "DEM" "ESP" ...** structure of dataset euro.crossnum [1:11, 1:11] 1 0.3411 7.0355 0.0827 2.3143 ...- attr(*, "dimnames")=List of 2..$ : chr [1:11] "ATS" "BEF" "DEM" "ESP" .....$ : chr [1:11] "ATS" "BEF" "DEM" "ESP" ...** structure of dataset eurodistClass 'dist' atomic [1:210] 3313 2963 3175 3339 2762 .....- attr(*, "Size")= num 21..- attr(*, "Labels")= chr [1:21] "Athens" "Barcelona" "Brussels" "Calais" ...** structure of dataset faithful'data.frame': 272 obs. of 2 variables:$ eruptions: num 3.6 1.8 3.33 2.28 4.53 ...$ waiting : num 79 54 74 62 85 55 88 85 51 85 ...** structure of dataset fdeathsTime-Series [1:72] from 1974 to 1980: 901 689 827 677 522 406 441 393 387 582 ...** structure of dataset freeny'data.frame': 39 obs. of 5 variables:$ y : Time-Series from 1962 to 1972: 8.79 8.79 8.81 8.81 8.91 ...$ lag.quarterly.revenue: num 8.8 8.79 8.79 8.81 8.81 ...$ price.index : num 4.71 4.7 4.69 4.69 4.64 ...$ income.level : num 5.82 5.83 5.83 5.84 5.85 ...$ market.potential : num 13 13 13 13 13 ...** structure of dataset freeny.xnum [1:39, 1:4] 8.8 8.79 8.79 8.81 8.81 ...- attr(*, "dimnames")=List of 2..$ : NULL..$ : chr [1:4] "lag quarterly revenue" "price index" "income level" "market potential"** structure of dataset freeny.yTime-Series [1:39] from 1962 to 1972: 8.79 8.79 8.81 8.81 8.91 ...** structure of dataset infert'data.frame': 248 obs. of 8 variables:$ education : Factor w/ 3 levels "0-5yrs","6-11yrs",..: 1 1 1 1 2 2 2 2 2 2 ...$ age : num 26 42 39 34 35 36 23 32 21 28 ...$ parity : num 6 1 6 4 3 4 1 2 1 2 ...$ induced : num 1 1 2 2 1 2 0 0 0 0 ...$ case : num 1 1 1 1 1 1 1 1 1 1 ...$ spontaneous : num 2 0 0 0 1 1 0 0 1 0 ...$ stratum : int 1 2 3 4 5 6 7 8 9 10 ...$ pooled.stratum: num 3 1 4 2 32 36 6 22 5 19 ...** structure of dataset iris'data.frame': 150 obs. of 5 variables:$ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...$ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...$ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...$ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...$ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...** structure of dataset iris3num [1:50, 1:4, 1:3] 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...- attr(*, "dimnames")=List of 3..$ : NULL..$ : chr [1:4] "Sepal L." "Sepal W." "Petal L." "Petal W."..$ : chr [1:3] "Setosa" "Versicolor" "Virginica"** structure of dataset islandsNamed num [1:48] 11506 5500 16988 2968 16 ...- attr(*, "names")= chr [1:48] "Africa" "Antarctica" "Asia" "Australia" ...** structure of dataset ldeathsTime-Series [1:72] from 1974 to 1980: 3035 2552 2704 2554 2014 ...** structure of dataset lhTime-Series [1:48] from 1 to 48: 2.4 2.4 2.4 2.2 2.1 1.5 2.3 2.3 2.5 2 ...** structure of dataset longley'data.frame': 16 obs. of 7 variables:$ GNP.deflator: num 83 88.5 88.2 89.5 96.2 ...$ GNP : num 234 259 258 285 329 ...$ Unemployed : num 236 232 368 335 210 ...$ Armed.Forces: num 159 146 162 165 310 ...$ Population : num 108 109 110 111 112 ...$ Year : int 1947 1948 1949 1950 1951 1952 1953 1954 1955 1956 ...$ Employed : num 60.3 61.1 60.2 61.2 63.2 ...** structure of dataset lynxTime-Series [1:114] from 1821 to 1934: 269 321 585 871 1475 ...** structure of dataset mdeathsTime-Series [1:72] from 1974 to 1980: 2134 1863 1877 1877 1492 ...** structure of dataset morley'data.frame': 100 obs. of 3 variables:$ Expt : int 1 1 1 1 1 1 1 1 1 1 ...$ Run : int 1 2 3 4 5 6 7 8 9 10 ...$ Speed: int 850 740 900 1070 930 850 950 980 980 880 ...** structure of dataset mtcars'data.frame': 32 obs. of 11 variables:$ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...$ cyl : num 6 6 4 6 8 6 8 4 4 6 ...$ disp: num 160 160 108 258 360 ...$ hp : num 110 110 93 110 175 105 245 62 95 123 ...$ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...$ wt : num 2.62 2.88 2.32 3.21 3.44 ...$ qsec: num 16.5 17 18.6 19.4 17 ...$ vs : num 0 0 1 1 0 1 0 1 1 1 ...$ am : num 1 1 1 0 0 0 0 0 0 0 ...$ gear: num 4 4 4 3 3 3 3 4 4 4 ...$ carb: num 4 4 1 1 2 1 4 2 2 4 ...** structure of dataset nhtempTime-Series [1:60] from 1912 to 1971: 49.9 52.3 49.4 51.1 49.4 47.9 49.8 50.9 49.3 51.9 ...** structure of dataset nottemTime-Series [1:240] from 1920 to 1940: 40.6 40.8 44.4 46.7 54.1 58.5 57.7 56.4 54.3 50.5 ...** structure of dataset npk'data.frame': 24 obs. of 5 variables:$ block: Factor w/ 6 levels "1","2","3","4",..: 1 1 1 1 2 2 2 2 3 3 ...$ N : Factor w/ 2 levels "0","1": 1 2 1 2 2 2 1 1 1 2 ...$ P : Factor w/ 2 levels "0","1": 2 2 1 1 1 2 1 2 2 2 ...$ K : Factor w/ 2 levels "0","1": 2 1 1 2 1 2 2 1 1 2 ...$ yield: num 49.5 62.8 46.8 57 59.8 58.5 55.5 56 62.8 55.8 ...** structure of dataset occupationalStatus'table' int [1:8, 1:8] 50 16 12 11 2 12 0 0 19 40 ...- attr(*, "dimnames")=List of 2..$ origin : chr [1:8] "1" "2" "3" "4" .....$ destination: chr [1:8] "1" "2" "3" "4" ...** structure of dataset precipNamed num [1:70] 67 54.7 7 48.5 14 17.2 20.7 13 43.4 40.2 ...- attr(*, "names")= chr [1:70] "Mobile" "Juneau" "Phoenix" "Little Rock" ...** structure of dataset presidentsTime-Series [1:120] from 1945 to 1975: NA 87 82 75 63 50 43 32 35 60 ...** structure of dataset pressure'data.frame': 19 obs. of 2 variables:$ temperature: num 0 20 40 60 80 100 120 140 160 180 ...$ pressure : num 0.0002 0.0012 0.006 0.03 0.09 0.27 0.75 1.85 4.2 8.8 ...** structure of dataset quakes'data.frame': 1000 obs. of 5 variables:$ lat : num -20.4 -20.6 -26 -18 -20.4 ...$ long : num 182 181 184 182 182 ...$ depth : int 562 650 42 626 649 195 82 194 211 622 ...$ mag : num 4.8 4.2 5.4 4.1 4 4 4.8 4.4 4.7 4.3 ...$ stations: int 41 15 43 19 11 12 43 15 35 19 ...** structure of dataset randu'data.frame': 400 obs. of 3 variables:$ x: num 0.000031 0.044495 0.82244 0.322291 0.393595 ...$ y: num 0.000183 0.155732 0.873416 0.648545 0.826873 ...$ z: num 0.000824 0.533939 0.838542 0.990648 0.418881 ...** structure of dataset riversnum [1:141] 735 320 325 392 524 ...** structure of dataset rock'data.frame': 48 obs. of 4 variables:$ area : int 4990 7002 7558 7352 7943 7979 9333 8209 8393 6425 ...$ peri : num 2792 3893 3931 3869 3949 ...$ shape: num 0.0903 0.1486 0.1833 0.1171 0.1224 ...$ perm : num 6.3 6.3 6.3 6.3 17.1 17.1 17.1 17.1 119 119 ...** structure of dataset sleep'data.frame': 20 obs. of 3 variables:$ extra: num 0.7 -1.6 -0.2 -1.2 -0.1 3.4 3.7 0.8 0 2 ...$ group: Factor w/ 2 levels "1","2": 1 1 1 1 1 1 1 1 1 1 ...$ ID : Factor w/ 10 levels "1","2","3","4",..: 1 2 3 4 5 6 7 8 9 10 ...** structure of dataset stack.lossnum [1:21] 42 37 37 28 18 18 19 20 15 14 ...** structure of dataset stack.xnum [1:21, 1:3] 80 80 75 62 62 62 62 62 58 58 ...- attr(*, "dimnames")=List of 2..$ : NULL..$ : chr [1:3] "Air.Flow" "Water.Temp" "Acid.Conc."** structure of dataset stackloss'data.frame': 21 obs. of 4 variables:$ Air.Flow : num 80 80 75 62 62 62 62 62 58 58 ...$ Water.Temp: num 27 27 25 24 22 23 24 24 23 18 ...$ Acid.Conc.: num 89 88 90 87 87 87 93 93 87 80 ...$ stack.loss: num 42 37 37 28 18 18 19 20 15 14 ...** structure of dataset state.abbchr [1:50] "AL" "AK" "AZ" "AR" "CA" "CO" "CT" "DE" "FL" ...** structure of dataset state.areanum [1:50] 51609 589757 113909 53104 158693 ...** structure of dataset state.centerList of 2$ x: num [1:50] -86.8 -127.2 -111.6 -92.3 -119.8 ...$ y: num [1:50] 32.6 49.2 34.2 34.7 36.5 ...** structure of dataset state.divisionFactor w/ 9 levels "New England",..: 4 9 8 5 9 8 1 3 3 3 ...** structure of dataset state.namechr [1:50] "Alabama" "Alaska" "Arizona" "Arkansas" "California" ...** structure of dataset state.regionFactor w/ 4 levels "Northeast","South",..: 2 4 4 2 4 4 1 2 2 2 ...** structure of dataset state.x77num [1:50, 1:8] 3615 365 2212 2110 21198 ...- attr(*, "dimnames")=List of 2..$ : chr [1:50] "Alabama" "Alaska" "Arizona" "Arkansas" .....$ : chr [1:8] "Population" "Income" "Illiteracy" "Life Exp" ...** structure of dataset sunspot.monthTime-Series [1:2988] from 1749 to 1998: 58 62.6 70 55.7 85 83.5 94.8 66.3 75.9 75.5 ...** structure of dataset sunspot.yearTime-Series [1:289] from 1700 to 1988: 5 11 16 23 36 58 29 20 10 8 ...** structure of dataset sunspotsTime-Series [1:2820] from 1749 to 1984: 58 62.6 70 55.7 85 83.5 94.8 66.3 75.9 75.5 ...** structure of dataset swiss'data.frame': 47 obs. of 6 variables:$ Fertility : num 80.2 83.1 92.5 85.8 76.9 76.1 83.8 92.4 82.4 82.9 ...$ Agriculture : num 17 45.1 39.7 36.5 43.5 35.3 70.2 67.8 53.3 45.2 ...$ Examination : int 15 6 5 12 17 9 16 14 12 16 ...$ Education : int 12 9 5 7 15 7 7 8 7 13 ...$ Catholic : num 9.96 84.84 93.4 33.77 5.16 ...$ Infant.Mortality: num 22.2 22.2 20.2 20.3 20.6 26.6 23.6 24.9 21 24.4 ...** structure of dataset treeringTime-Series [1:7980] from -6000 to 1979: 1.34 1.08 1.54 1.32 1.41 ...** structure of dataset trees'data.frame': 31 obs. of 3 variables:$ Girth : num 8.3 8.6 8.8 10.5 10.7 10.8 11 11 11.1 11.2 ...$ Height: num 70 65 63 72 81 83 66 75 80 75 ...$ Volume: num 10.3 10.3 10.2 16.4 18.8 19.7 15.6 18.2 22.6 19.9 ...** structure of dataset uspopTime-Series [1:19] from 1790 to 1970: 3.93 5.31 7.24 9.64 12.9 17.1 23.2 31.4 39.8 50.2 ...** structure of dataset volcanonum [1:87, 1:61] 100 101 102 103 104 105 105 106 107 108 ...** structure of dataset warpbreaks'data.frame': 54 obs. of 3 variables:$ breaks : num 26 30 54 25 70 52 51 26 67 18 ...$ wool : Factor w/ 2 levels "A","B": 1 1 1 1 1 1 1 1 1 1 ...$ tension: Factor w/ 3 levels "L","M","H": 1 1 1 1 1 1 1 1 1 2 ...** structure of dataset women'data.frame': 15 obs. of 2 variables:$ height: num 58 59 60 61 62 63 64 65 66 67 ...$ weight: num 115 117 120 123 126 129 132 135 139 142 ...>