search for: 3.469447e

Hello! I have two matrices of equal dimension ll and lu that I want to do a ks.test on corresponding rows in these matrices (dim(ll) is [1] 101 100). If I do e.g. > ks.test(ll[50,],lu[50,]) just for testing, it displays a lot of numbers, and some more info: [116] -3.000000e-02 -4.000000e-02 -4.000000e-02 -3.000000e-02 -4.000000e-02 [121] -3.000000e-02 -4.000000e-02 -3.000000e-02 -2.000000e-02

Hi, I have a following vector: > smallch [1] 0.0652840 0.1181300 0.0319370 0.0155700 0.0464110 0.0107850 [7] 0.0158970 0.0375900 0.0603090 0.0310300 0.0105920 0.0540580 [13] -0.0177740 0.0039393 Pretty (R 1.5.1) has problems with zero: > pretty(smallch) [1] -2.000000e-02 -3.469447e-18 2.000000e-02 4.000000e-02 6.000000e-02 [6] 8.000000e-02 1.000000e-01 1.200000e-01

Hi, I have a following vector: > smallch [1] 0.0652840 0.1181300 0.0319370 0.0155700 0.0464110 0.0107850 [7] 0.0158970 0.0375900 0.0603090 0.0310300 0.0105920 0.0540580 [13] -0.0177740 0.0039393 Pretty (R 1.5.1) has problems with zero: > pretty(smallch) [1] -2.000000e-02 -3.469447e-18 2.000000e-02 4.000000e-02 6.000000e-02 [6] 8.000000e-02 1.000000e-01 1.200000e-01

I noticed the following peculiarity with `serialize()' when `ascii = TRUE' is used. In today's (svn r37299) R-devel, I get > set.seed(10) > x <- rnorm(10) > > a <- serialize(x, con = NULL, ascii = TRUE) > b <- unserialize(a) > > identical(x, b) ## FALSE [1] FALSE > x - b [1] -3.469447e-18 2.775558e-17 -4.440892e-16 0.000000e+00

Hi Everyone, I am uncertain that I am writing the contrast statements correctly. Basically, I'm unsure when to use a -1 and a 1 when writing the contrasts. Specifically I am interested in comparing the slopes between different temperature regimes. Temperature is therefore a factor. Time and percent are numerical. Using the gmodels package I made the following model:

I have a simple system of linear equations to solve for X, aX=b: > a [,1] [,2] [,3] [,4] [1,] 1 2 1 1 [2,] 3 0 0 4 [3,] 1 -4 -2 -2 [4,] 0 0 0 0 > b [,1] [1,] 0 [2,] 2 [3,] 2 [4,] 0 (This is ex Ch1, 2.2 of Artin, Algebra). So, 3 eqs in 4 unknowns. One can easily use row-reductions to find a homogeneous solution(b=0) of: X_1