POLI 277 MEASUREMENT THEORY
First Assignment
Due 16 April 2008
TORSCA Method to get initial starting configuration PRE-ITERATIONS=3 Number Iterations to Improve starting config. DIMMAX=2,DIMMIN=1 Maximum & Minimum Number of Dimensions COORDINATES=ROTATE Rotate Coordinates so Principal Components lie along axes ITERATIONS=50 Maximum Number of Iterations REGRESSION=DESCENDING Monotone Regression for Similarities -- NONMETRIC MDS DATA,LOWERHALFMATRIX,DIAGONAL=PRESENT,CUTOFF=.01 Anything below .01 is Missing Data U. S. SUPREME COURT AGREEMENT SCORES Title 32 1 1 32 = # of Justices, Always set the next two numbers = 1 (12X,101F3.0) Format Statement For Dataset BURGER 100 BLACKMUN 81100 POWELL 86 80100 REHNQUIS 87 72 83100 STEVENS 71 77 74 67100 OCONNOR 88 72 86 87 71100 SCALIA -99 66 85 89 65 85100 KENNEDY -99 70-99 88 70 86 87100 -99 is the Missing Data Code SOUTER -99 72-99 78 75 81 77 84100 THOMAS -99 55-99 86 56 81 92 82 72100 GINSBURG -99 67-99 73 80 75 70 79 87 67100 BREYER -99-99-99 70 78 77 64 75 84 63 84100 RUTLEDGE -99-99-99-99-99-99-99-99-99-99-99-99100 MURPHY -99-99-99-99-99-99-99-99-99-99-99-99 86100 VINSON -99-99-99-99-99-99-99-99-99-99-99-99 63 64100 HARLAN 81 78-99-99-99-99-99-99-99-99-99-99-99-99-99100 BLACK 67 69-99-99-99-99-99-99-99-99-99-99 85 85 63 58100 DOUGLAS 39 42 42 33-99-99-99-99-99-99-99-99 78 79 59 50 77100 STEWART 77 75 80 74 75-99-99-99-99-99-99-99-99-99-99 78 67 58100 MARSHALL 54 65 57 46 65 51 50 50 53-99-99-99-99-99-99 70 66 70 69100 BRENNAN 53 64 56 46 65 52 51 52100-99-99-99-99-99-99 66 76 76 70 91100 WHITE 80 76 79 77 69 77 79 80 76 74-99-99-99-99-99 74 73 56 76 59 64100 WARREN -99-99-99-99-99-99-99-99-99-99-99-99-99-99-99 60 81 79 71 90 91 79100 CLARK -99-99-99-99-99-99-99-99-99-99-99-99-99-99 91 74 67 61 77-99 77 83 77100 FRANKFUR -99-99-99-99-99-99-99-99-99-99-99-99 58 61 70 86 60 55 79-99 67-99 63 71100 WHITTAKE -99-99-99-99-99-99-99-99-99-99-99-99-99-99-99 81 57 52 82-99 66-99 62 75 80100 BURTON -99-99-99-99-99-99-99-99-99-99-99-99 62 58 83 77 60 56-99-99 65-99 66 81 72 80100 REED -99-99-99-99-99-99-99-99-99-99-99-99 65 62 84 67 60 60-99-99 69-99 71 82 67-99 82100 FORTAS -99-99-99-99-99-99-99-99-99-99-99-99-99-99-99 63 68 76 72 89 87 75 85 74-99-99-99-99100 GOLDBERG -99-99-99-99-99-99-99-99-99-99-99-99-99-99-99 59 78 80 77-99 90 78 87 71-99-99-99-99-99100 MINTON -99-99-99-99-99-99-99-99-99-99-99-99-99-99 87 72 62 57-99-99-99-99 75 84 68-99 82 83-99-99100 JACKSON -99-99-99-99-99-99-99-99-99-99-99-99 57 57 75-99 57 53-99-99-99-99 75 78 80-99 74 73-99-99 73100 COMPUTE These two Lines STOP Must Always be IncludedYou must run the program from a DOS Window. To run the program type:
supremesnames <- read.table("C:/class2000/kystsupremes/supreme_names.txt",header=F,row.names=1)This tells R to read in the file you just created. (Be sure to correctly type in the correct path statement!) The "header=F" tells R that we do not have labels for the columns and the "row.names=1" tells R that the first column are row labels. Now type:
supremesnames2 <- read.table("C:/class2000/kystsupremes/supreme_names2.txt",row.names=1)Replicate (a) and (b) above and turn in the plots.
# The cross-hatch is used as a comment marker -- R ignores the line # plot_supremes.r -- Does a graph of the 32 Supremes using KYST output # file supreme_names.txt Always put the name of the program at the top # # Burger -0.847 -0.193 This is not necessary but I have no memory # Blackmun -0.532 -0.729 so I always put in the file if its small so # Powell -0.990 0.019 I do not forget what I am doing! # Rehnquis -1.182 0.342 # Stevens -0.087 -0.940 # Oconnor -0.898 0.317 # Scalia -1.099 0.630 # Kennedy -0.726 0.589 # Souter -0.082 0.513 # Thomas -1.297 0.942 # Ginsburg 0.194 0.238 # Breyer 0.084 -0.065 # Rutledge 0.904 0.877 # Murphy 0.646 1.104 # Vinson -0.312 -0.224 # Harlan -0.208 -1.194 # Black 0.680 0.972 # Douglas 1.589 0.690 # Stewart -0.043 -0.423 # Marshall 1.310 -0.505 # Brennan 1.095 0.102 # White -0.305 0.191 # Warren 0.884 0.217 # Clark -0.068 0.013 # Frankfur 0.155 -1.235 # Whittake 0.356 -1.110 # Burton -0.560 -0.419 # Reed -0.566 -0.013 # Fortas 1.138 -0.210 # Goldberg 0.766 0.382 # Minton -0.433 0.105 # Jackson 0.434 -0.982 # # # Remove all objects just to be safe # rm(list=ls(all=TRUE)) This is not strictly necessary but I do not trust R # library(MASS) This is a standard R library # # # # %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% The next set of commands read the file. # Read supreme_names.txt This is admitedly clunky way of doing things # %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% but it is bulletproof if you are careful. # rcx.file <- "c:/ucsd_homework_1/supreme_names.txt" Path to the File -- You need the quotes. # # Standard fields and their widths -- OC output Legislators # rcx.fields <- c("name","dim1","dim2") You need to name the columns. rcx.fieldWidths <- c(8,11,7) You need to give it the exact widths of the columns # # Input Legislator Coordinates # T <- read.fwf(file=rcx.file,widths=rcx.fieldWidths,as.is=TRUE,col.names=rcx.fields) The Read Statement dim(T) This Turns it into an R dataframe (which looks like a matrix) #T <- as.matrix(T) If you do not have any text in the dataset this command # is handy because it makes your input data a true matrix and not a dataframe names <- T[,1] dimension1 <- T[,2] These three commands just make life easier -- they are dimension2 <- T[,3] not necessary # # nrow <- length(T[,1]) Here is how you can figure out the number of variables ncol <- length(T[1,]) and the number of columns # # # This puts more white space # on the Right-Hand-Side Margin # par(mar=c(4.1,5.1,4.1,5.1)) This controls the margins on all 4 sides of the plot # # plot(dimension1,dimension2,type="n",asp=1, The "n" says no visible plot; asp=1 means main="", maintain the aspect ratio xlab="", ylab="", xlim=c(-2.0,2.0),ylim=c(-2.0,2.0)) These have to be the same for asp=1 to work points(dimension1,dimension2,pch=16,col="red") Plot the Points axis(1,font=2) Horizontal axis in bold font axis(2,font=2,cex=1.2) Vertical axis in bold font # Main title mtext("U.S. Supreme Court 1945-2000",side=3,line=1.00,cex=1.2,font=2) Side 3 is the top # x-axis title line= controls position mtext("Liberal-Conservative",side=1,line=2.75,cex=1.2) # y-axis title mtext("Who the Heck Knows",side=2,line=2.5,cex=1.2) # # pos -- a position specifier for the text. Values of 1, 2, 3 and 4, # respectively indicate positions below, to the left of, above and # to the right of the specified coordinates # namepos <- rep(2,nrow) This generates a nrow-length vector of 2's # #namepos[1] <- 2 # Burger #namepos[2] <- 2 # Blackmun I stuck in the Supremes' Names so #namepos[3] <- 2 # Powell You can control their positions #namepos[4] <- 2 # Rehnquis #namepos[5] <- 2 # Stevens #namepos[6] <- 2 # Oconnor #namepos[7] <- 2 # Scalia #namepos[8] <- 2 # Kennedy #namepos[9] <- 2 # Souter #namepos[10] <- 2 # Thomas #namepos[11] <- 2 # Ginsburg #namepos[12] <- 2 # Breyer #namepos[13] <- 2 # Rutledge #namepos[14] <- 2 # Murphy #namepos[15] <- 2 # Vinson #namepos[16] <- 2 # Harlan #namepos[17] <- 2 # Black #namepos[18] <- 2 # Douglas #namepos[19] <- 2 # Stewart #namepos[20] <- 2 # Marshall #namepos[21] <- 2 # Brennan #namepos[22] <- 2 # White #namepos[23] <- 2 # Warren #namepos[24] <- 2 # Clark #namepos[25] <- 2 # Frankfur #namepos[26] <- 2 # Whittake #namepos[27] <- 2 # Burton #namepos[28] <- 2 # Reed #namepos[29] <- 2 # Fortas #namepos[30] <- 2 # Goldberg #namepos[31] <- 2 # Minton #namepos[32] <- 2 # Jackson # text(dimension1,dimension2,names,pos=namepos,offset=00.00,col="blue") This Plots the Names. #Run the program in R and you should get this:
PRINT HISTORY, PRINT DISTANCES This Option Prints out Some Useful Intermediate Output DIMMAX=3, DIMMIN=1 TORSCA REGRESSION=POLYNOMIAL=1 METRIC MDS DATA,LOWERHALFMATRIX,DIAGONAL=PRESENT,CUTOFF=0.0 U.S. MAP EXAMPLE 10 1 1 (10f5.0) 0000 2340 0000 1084 2797 0000 715 1789 976 0000 481 2018 853 301 0000 826 1661 1868 936 988 0000 1519 891 2008 1017 1245 797 0000 2252 908 3130 2189 2292 1431 1189 0000 662 2974 1547 1386 1143 1394 2126 2885 0000 641 2480 443 696 498 1414 1707 2754 1096 0000 COMPUTE STOPRun this data set through KYST and get the coordinates.
TORSCA PRE-ITERATIONS=3 DIMMAX=2,DIMMIN=2 PRINT HISTORY,PRINT DISTANCES COORDINATES=ROTATE ITERATIONS=50 REGRESSION=DESCENDING DATA,LOWERHALFMATRIX,DIAGONAL=PRESENT MORSE CODE DATA -- SIMILARITIES EXAMPLE 36 1 1 (1X,36F3.0) A 92 4 6 13 3 14 10 13 46 5 22 3 25 34 6 6 9 35 23 6 37 13 17 12 7 3 2 7 5 5 8 6 5 6 2 3 A B 5 84 37 31 5 28 17 21 5 19 34 40 6 10 12 22 25 16 18 2 18 34 8 84 30 42 12 17 14 40 32 74 43 17 4 4 B C 4 38 87 17 4 29 13 7 11 19 24 35 14 3 9 51 34 24 14 6 6 11 14 32 82 38 13 15 31 14 10 30 28 24 18 12 C D 8 62 17 88 7 23 40 36 9 13 81 56 8 7 9 27 9 45 29 6 17 20 27 40 15 33 3 9 6 11 9 19 8 10 5 6 D E 6 13 14 6 97 2 4 4 17 1 5 6 4 4 5 1 5 10 7 67 3 3 2 5 6 5 4 3 5 3 5 2 4 2 3 3 E F 4 51 33 19 2 90 10 29 5 33 16 50 7 6 10 42 12 35 14 2 21 27 25 19 27 13 8 16 47 25 26 24 21 5 5 5 F G 9 18 27 38 1 14 90 6 5 22 33 16 14 13 62 52 23 21 5 3 15 14 32 21 23 39 15 14 5 10 4 10 17 23 20 11 G H 3 45 23 25 9 32 8 87 10 10 9 29 5 8 8 14 8 17 37 4 36 59 9 33 14 11 3 9 15 43 70 35 17 4 3 3 H I 64 7 7 13 10 8 6 12 93 3 5 16 13 30 7 3 5 19 35 16 10 5 8 2 5 7 2 5 8 9 6 8 5 2 4 5 I J 7 9 38 9 2 24 18 5 4 85 22 31 8 3 21 63 47 11 2 7 9 9 9 22 32 28 67 66 33 15 7 11 28 29 26 23 J K 5 24 38 73 1 17 25 11 5 27 91 33 10 12 31 14 31 22 2 2 23 17 33 63 16 18 5 9 17 8 8 18 14 13 5 6 K L 2 69 43 45 10 24 12 26 9 30 27 86 6 2 9 37 36 28 12 5 16 19 20 31 25 59 12 13 17 15 26 29 36 16 7 3 L M 24 12 5 14 7 17 29 8 8 11 23 8 96 62 11 10 15 20 7 9 13 4 21 9 18 8 5 7 6 6 5 7 11 7 10 4 M N 31 4 13 30 8 12 10 16 13 3 16 8 59 93 5 9 5 28 12 10 16 4 12 4 16 11 5 2 3 4 4 6 2 2 10 2 N O 7 7 20 6 5 9 76 7 2 39 26 10 4 8 86 37 35 10 3 4 11 14 25 35 27 27 19 17 7 7 6 18 14 11 20 12 O P 5 22 33 12 5 36 22 12 3 78 14 46 5 6 21 83 43 23 9 4 12 19 19 19 41 30 34 44 24 11 15 17 24 23 25 13 P Q 8 20 38 11 4 15 10 5 2 27 23 26 7 6 22 51 91 11 2 3 6 14 12 37 50 63 34 32 17 12 9 27 40 58 37 24 Q R 13 14 16 23 5 34 26 15 7 12 21 33 14 12 12 29 8 87 16 2 23 23 62 14 12 13 7 10 13 4 7 12 7 9 1 2 R S 17 24 5 30 11 26 5 59 16 3 13 10 5 17 6 6 3 18 96 9 56 24 12 10 6 7 8 2 2 15 28 9 5 5 5 2 S T 13 10 1 5 46 3 6 6 14 6 14 7 6 5 6 11 4 4 7 96 8 5 4 2 2 6 5 5 3 3 3 8 7 6 14 6 T U 14 29 12 32 4 32 11 34 21 7 44 32 11 13 6 20 12 40 51 6 93 57 34 17 9 11 6 6 16 34 10 9 9 7 4 3 U V 5 17 24 16 9 29 6 39 5 11 26 43 4 1 9 17 10 17 11 6 32 92 17 57 35 10 10 14 28 79 44 36 25 10 1 5 V W 9 21 30 22 9 36 25 15 4 25 29 18 15 6 26 20 25 61 12 4 19 20 86 22 25 22 10 22 19 16 5 9 11 6 3 7 W X 7 64 45 19 3 28 11 6 1 35 50 42 10 8 24 32 61 10 12 3 12 17 21 91 48 26 12 20 24 27 16 57 29 16 17 6 X Y 9 23 62 15 4 26 22 9 1 30 12 14 5 6 14 30 52 5 7 4 6 13 21 44 86 23 26 44 40 15 11 26 22 33 23 16 Y Z 3 46 45 18 2 22 17 10 7 23 21 51 11 2 15 59 72 14 4 3 9 11 12 36 42 87 16 21 27 9 10 25 66 47 15 15 Z 1 2 5 10 3 3 5 13 4 2 29 5 14 9 7 14 30 28 9 4 2 3 12 14 17 19 22 84 63 13 8 10 8 19 32 57 55 1 2 7 14 22 5 4 20 13 3 25 26 9 14 2 3 17 37 28 6 5 3 6 10 11 17 30 13 62 89 54 20 5 14 20 21 16 11 2 3 3 8 21 5 4 32 6 12 2 23 6 13 5 2 5 37 19 9 7 6 4 16 6 22 25 12 18 64 86 31 23 41 16 17 8 10 3 4 6 19 19 12 8 25 14 16 7 21 13 19 3 3 2 17 29 11 9 3 17 55 8 37 24 3 5 26 44 89 42 44 32 10 3 3 4 5 8 45 15 14 2 45 4 67 7 14 4 41 2 0 4 13 7 9 27 2 14 45 7 45 10 10 14 10 30 69 90 42 24 10 6 5 5 6 7 80 30 17 4 23 4 14 2 11 11 27 6 2 7 16 30 11 14 3 12 30 9 58 38 39 15 14 26 24 17 88 69 14 5 14 6 7 6 33 22 14 5 25 6 4 6 24 13 32 7 6 7 36 39 12 6 2 3 13 9 30 30 50 22 29 18 15 12 61 85 70 20 13 7 8 3 23 40 6 3 15 15 6 2 33 10 14 3 6 14 12 45 2 6 4 6 7 5 24 35 50 42 29 16 16 9 30 60 89 61 26 8 9 3 14 23 3 1 6 14 5 2 30 6 7 16 11 10 31 32 5 6 7 6 3 8 11 21 24 57 39 9 12 4 11 42 56 91 78 9 0 9 3 11 2 5 7 14 4 5 30 8 3 2 3 25 21 29 2 3 4 5 3 2 12 15 20 50 26 9 11 5 22 17 52 81 94 0 COMPUTE STOPThis is the famous morse code data. If you compare this file to MORSEKYSTSU.DAT they are exactly the same except the matrix is transposed.