[R] statistical modeling language and basic operation

  . 1  # VEC <- REP (SEQ (l, 5, by = 0.5),. 3) 
  2  
  . 3  # VEC <- SEQ (. 1, 10, by =. 1) 
  . 4  # min (VEC) # Min 
  . 5  # max (VEC ) # maximum 
  . 6  # range (VEC) # range 
  . 7  # length (VEC) # length 
  . 8  # sUM (VEC) Total # 
  9  # all product prod (vec) # vector element 
10  # median (VEC) # median 
. 11  # mean (VEC) mean # 
12 is  # var (VEC) sample variance # 
13 is  # Sort (VEC) Sort # 
14  # Order (-vec) Sort # is the index does not change the actual position of the vector 
15  # vec
 16 
 17 # vec <- 1:5
 18 # Logic_vec <- vec > 3 
 19 # Logic_vec
 20 
 21 # str = c( "x" , "y" , "z" , "w" )
 22 # paste("result.",str,sep="")
 23 
 24 # x <- -5 : 5
 25 # y <- numeric( length(x) )
 26 # y[x<0] <- 1 - x[x<0]
 27 # y[x>=0] <- 1 + x[x>=0]
 28 # x;y
 29 
 30 # sex <- c("M","F","M","M","F");sex
 31 
 32 # sexf <- factor(sex) ; sexf 
 33 
 34 # sex.level <- levels(sexf) ; sex.level
 35 
 36 # sex.tab <- table( sexf ) ; sex.tab 
 37 
 38 # sex <- c("M","F","M","M","F")
 39 # sexf <- factor(sex);
 40 # sex.level <- levels(sexf);
 41 # height <- c(174,165,180,171,160)
 42 # tapply( height , sex , mean )
 43 
 44 
 45 # A <- matrix( 1:9 , nrow = 3 , ncol = 3 , byrow = TRUE ) ; 
 46 # A[3,3] = 10;A;
 47 # B <- matrix( 1 , nrow = 3 , ncol = 1 , byrow = TRUE ) ; B 
 48 
 49 # A <- matrix( 1:9 , nrow = 3 , ncol = 3 , byrow = TRUE ) ; 
 50 # A[3,3] = 10;
 51 # det(A)
 52 
 53 # A <- t( array( c(1:8,10) , dim=c(3,3) ) );A
 54 # Inv_A <- solve(A) ; Inv_A
 55 
 56 # A <- t( array( c(1:8,10) , dim=c(3,3) ) );A
 57 # Inv_A <- solve(A) ; Inv_A
 58 # E = A %*% Inv_A ; E 
 59 
 60 # A <- t( array( c(1:8,10) , dim = c(3,3) ) );A
 61 #b <- c (1, 1, 1); b 
62  # x <- solve (A, b); x 
63   
64  # A <- t (array (c (1: 8.10), dim = c (3,3))); A 
65  # Sm <- tcrossprod (A, A); Sm 
66  
67  
68  # ev <- intrinsically (Sm); ev 
69  
70  # A <- t (array (c (1: 8.10), dim = c (3,3))); A 
71  # svdA <- SVD (A); svdA 
72  # u = svdA $ u u 
73  # v = svdA $ v v 
74  # d = svdA $ d d 
75  # u% *% diag (d)% *% t (v) 
76  
77  # A <- t( array( c(1:8,10) , dim = c(3,3) ) );A
 78 # apply( A , 2 , sum )
 79 
 80 
 81 # fzero <- function( f , a , b , eps = 1e-5 ){
 82 #     if( f(a) * f(b) > 0 )
 83 #         list( fail = "Unfound ")
 84 #     else{
 85 #         repeat{
 86 #             if( abs(b-a) < eps ) break 
 87 #             x <- (a+b) / 2 
 88 #             if( f(a) * f(x) < 0 ){
 89 #                 b <- x 
 90 #             }
 91 #             else{
 92 #                 a <- x
 93 #             }
 94 #         }
 95 #         list(root = (a+b)/2,fun = f(x) )
 96 #     }
 97 # }
 98 # 
 99 # f <- function( x ) { x^3 - x - 1 }
100 # fzero(f,0,10,1e-6)
101 
102 # area <- function( f , a , b , eps = 1e-6 , lim = 10 ){
103 #     fun1 <- function( f , a , b , fa , fb , a0 , eps , lim , fun ){
104 #         d <- ( a+b ) / 2 ;
105 #         h <- ( b-a ) / 4 ;
106 #         fd <- f(d) ;
107 #         a1 <- h * ( fa+fd )
108 #         a2 <- h * ( fd+fb )
109 #         if( abs(a0-a1-a2) < eps || lim == 0 ){
110 #             return ( a1 + a2 )
111 #         }else{
112 #             return ( fun(f,a,d,fa,fd,a1,eps,lim-1,fun)
113 #                     +fun(f,d,b,fd,fb,a2,eps,lim-1,fun))
114 #         }
115 #     }
116 #     fa <- f(a);
117 #     fb <- f(b);
118 #     a0 <- ((fa+fb) * (b-a))/2;
119 #     fun1(f,a,b,fa,fb,a0,eps,lim,fun1)
120 # }
121 # 
122 # f <- function(x) x
123 # quad <- area(f,0,10) ; quad